Data Journalism in Poland – Practices and Development Prospects

Abstract

This thesis examines data journalism in Poland from theoretical, institutional, and prospective analytical perspectives. The study is motivated by the relative scarcity of Polish-language scholarly treatment of a journalistic practice that has attracted considerable international attention. The theoretical framework employed draws on the scholarly literature concerning data-driven and computational journalism, precision journalism, and data visualisation, with reference to both Anglophone and Polish academic contributions. Three principal research questions are addressed: how data journalism is conceptually defined and historically situated; what institutional actors, legislative conditions, and professional competences characterise its current practice in Poland; and what structural factors are likely to determine its medium-term development trajectory. The analysis proceeds through a synthesis of secondary literature, policy documentation, and available empirical evidence regarding Polish newsrooms and practitioner profiles. It is argued that data journalism in Poland occupies a structurally peripheral yet dynamically evolving position within the national media landscape. The field's development is conditioned by ownership concentration, incomplete open data compliance, and constraints on specialist training, but is supported by participation in international collaborative networks. The principal conclusion advanced is that sustained expansion of the field depends upon investment in specialist education and the adoption of transparent methodological standards capable of securing public trust in data-driven reporting.

Keywords: data journalism, Polish media system, open data, investigative reporting, data visualisation, computational journalism

Streszczenie

Niniejsza praca poddaje analizie dziennikarstwo danych w Polsce z perspektywy teoretycznej, instytucjonalnej i prospektywnej. Jej podjęcie uzasadnione jest względną rzadkością polskojęzycznych opracowań naukowych poświęconych praktyce dziennikarskiej, która cieszy się znaczącym zainteresowaniem w literaturze międzynarodowej. Zastosowane ramy teoretyczne opierają się na dorobku badaczy dziennikarstwa opartego na danych, dziennikarstwa komputerowego i precyzyjnego, a także wizualizacji informacji, z uwzględnieniem zarówno anglojęzycznego, jak i polskiego piśmiennictwa akademickiego. Praca stawia trzy zasadnicze pytania badawcze: jak definiuje się i historycznie sytuuje dziennikarstwo danych; jakie podmioty instytucjonalne, uwarunkowania legislacyjne i kompetencje zawodowe charakteryzują jego obecną praktykę w Polsce; oraz jakie czynniki strukturalne wpływają na trajektorię jego średniookresowego rozwoju. Analiza przeprowadzona została na podstawie syntezy literatury przedmiotu, dokumentacji polityki publicznej oraz dostępnych danych empirycznych dotyczących polskich redakcji i profili zawodowych dziennikarzy. Wykazano, że dziennikarstwo danych zajmuje w polskim krajobrazie medialnym pozycję strukturalnie peryferyjną, lecz dynamicznie ewoluującą. Jego rozwój jest warunkowany koncentracją własności, niepełną zgodnością z wymogami otwartych danych i ograniczeniami w kształceniu specjalistycznym, lecz wspierany przez uczestnictwo w międzynarodowych sieciach współpracy. Sformułowany wniosek wskazuje, że trwałe rozszerzenie pola działalności zależy od inwestycji w kształcenie specjalistyczne oraz przyjęcia przejrzystych standardów metodologicznych.

Słowa kluczowe: dziennikarstwo danych, polski system medialny, otwarte dane, dziennikarstwo śledcze, wizualizacja danych, dziennikarstwo komputerowe

List of Abbreviations

AI: Artificial Intelligence
APIs: Application Programming Interfaces
CAR: Computer-Assisted Reporting
CBS: Columbia Broadcasting System
DGA: Data Governance Act
EDJNet: European Data Journalism Network
EU: European Union
FAIR: Findable, Accessible, Interoperable, Reusable
FOI: Freedom of Information
GDPR: General Data Protection Regulation
GIJN: Global Investigative Journalism Network
GIS: Geographic Information System
ICIJ: International Consortium of Investigative Journalists
IFCN: International Fact-Checking Network
NGO: Non-Governmental Organisation
OCCRP: Organised Crime and Corruption Reporting Project
TVP: Telewizja Polska

Introduction

The intersection of digital technology, open data infrastructure, and investigative journalistic practice has generated a field of activity — variously designated as data journalism, data-driven journalism, or computational journalism — that has attracted sustained scholarly and professional attention across established media systems in Western Europe and North America. In the Polish context, however, the academic literature addressing this phenomenon remains comparatively sparse, and the institutional landscape within which data-intensive reporting has taken root has received only fragmentary analytical treatment. This thesis undertakes a systematic examination of data journalism in Poland, proceeding from its theoretical and conceptual foundations through to the institutional realities of its current practice and the structural factors that will condition its future development. The motivating premise is that a coherent account of a journalistic field in a specific national context requires attention not only to individual practitioners and exemplary outputs but to the organisational, legislative, and educational conditions that determine which forms of practice become sustainable and which remain exceptional.

The importance of the topic is rooted in developments that extend well beyond the boundaries of any single national media system. The democratisation of data access — through legislative frameworks mandating proactive disclosure of government-held information, through international open data initiatives, and through the proliferation of digital tools that allow non-specialist journalists to conduct analyses that previously required dedicated statistical expertise — has materially altered the opportunity structure for investigative reporting across the globe. Data journalism, on the account offered by a range of international scholars, represents one of the most consequential responses by the journalistic profession to this altered environment, offering a set of practices that combine the traditional normative commitments of public interest reporting with methodological resources borrowed from computational and statistical disciplines. ^[2] The degree to which this response has materialised in Poland, and the conditions under which it might develop further, constitute questions of direct relevance to assessments of the quality and accountability of public communication in one of the European Union's largest member states.

The Polish media environment presents a context of particular analytical interest for the study of data journalism. It is characterised by a rapid and in some respects disruptive digital transition, by patterns of ownership concentration that have intensified since 2021 with the acquisition of Polska Press by PKN Orlen, and by an open data legislative framework that has been substantially shaped by transposed European Union directives without achieving uniform compliance across public sector bodies. These conditions create a configuration of pressures and opportunities that is neither straightforwardly enabling nor comprehensively obstructive, but that requires careful disaggregation if its implications for data-intensive reporting are to be properly understood. Research on data journalism in comparative context has consistently demonstrated that national institutional factors — including media ownership structures, access to information legislation, and the strength of educational pipelines for quantitatively trained journalists — exercise a significant influence on the diffusion of data journalism practices, independently of the technological resources nominally available to practitioners. ^[4] The Polish case thus offers not merely a nationally specific subject of inquiry but a test case for the generalisability of theoretical propositions developed in different institutional contexts.

The research problem addressed by this thesis may be stated as follows: to what extent has data journalism established itself as an institutionally grounded and methodologically coherent journalistic practice within the Polish media system, and what structural factors determine its prospects for broader diffusion? This formulation encompasses three subsidiary questions that organise the substantive analysis presented in subsequent chapters. The first concerns the conceptual and theoretical landscape of the field: what definitions and normative frameworks have been articulated in the international and Polish scholarly literature, and how do they condition the identification and evaluation of data journalism practice? The second concerns the institutional reality of data journalism in Poland: which actors, organisations, and legislative frameworks have shaped the conditions under which data-intensive reporting has been conducted, and what does the available evidence reveal about the current scope and character of such practice? The third concerns prospective development: what barriers impede wider diffusion, what educational and international resources are available to support growth, and what alternative developmental trajectories are plausible under different configurations of political, economic, and technological conditions?

The research objectives of the thesis are fourfold. The first is to provide a systematic account of the theoretical and conceptual foundations of data journalism as articulated in the international scholarly literature, with particular attention to the Polish-language contributions to this discourse. The second is to document and analyse the institutional landscape of data journalism in Poland, including the principal media outlets, journalistic organisations, and legislative frameworks that constitute its operational environment. The third is to identify and assess the structural barriers that have constrained the diffusion of data journalism practices in Polish newsrooms, including financial, organisational, cultural, and technical dimensions of resistance. The fourth is to construct a prospective analysis of the field's development under varying scenarios, grounded in the empirical evidence assembled through the preceding analytical stages. These objectives are pursued through a combination of methods appropriate to the nature of the inquiry and the available evidence base.

The methodological approach adopted in this thesis is primarily qualitative and document-analytical in character. The first and principal method employed is a systematic review of the relevant scholarly literature, drawing on both the international academic corpus — including contributions from media studies, journalism studies, science and technology studies, and information science — and the smaller but substantively significant body of Polish-language scholarship that has addressed data journalism directly or in closely related terms. The literature review serves both to establish the conceptual vocabulary employed throughout the analysis and to situate Polish data journalism within the broader theoretical frameworks that have been applied to cognate practices elsewhere. The second method is the analysis of policy documents, legislative texts, and institutional publications pertaining to the open data framework and freedom of information regime that condition data journalism practice in Poland, including transposed European Union directives, domestic implementing legislation, and reports produced by oversight bodies and professional associations. The third method is case-based analysis, through which specific Polish data journalism projects, organisations, and initiatives are examined in relation to the structural and institutional conditions identified through documentary analysis. This approach does not aspire to the systematic comparative rigour of a formal multiple-case study design; rather, cases are employed illustratively and analytically, as vehicles for examining how general structural conditions are refracted through specific organisational and editorial contexts.

The selection of these methods reflects both the epistemic ambitions and the practical constraints of the present inquiry. A quantitative survey of newsroom practices or a systematic content analysis of published data journalism outputs would have provided a different and in some respects complementary evidence base, but both approaches would have required data collection resources extending beyond what is available at the undergraduate research level. The document-analytical and literature-based approach adopted here is suited to addressing questions of institutional structure, normative framework, and developmental trajectory, which constitute the principal analytical concerns of the thesis. It should be noted that the absence of comprehensive systematic data on the volume, distribution, and character of data journalism output in Poland is itself a substantively significant finding: the paucity of empirical documentation of the field reflects and reinforces its marginal institutional position, a point that is addressed explicitly in the analysis of barriers to growth.

The thesis is structured into three substantive chapters, preceded by this introduction and followed by a concluding synthesis. Chapter 1 establishes the theoretical and conceptual foundations of the inquiry, examining the definitional debates and scholarly disagreements that characterise the academic literature on data journalism. Particular attention is devoted to the relationship between data journalism and preceding traditions of precision journalism and computer-assisted reporting, to the normative frameworks that have been advanced to characterise the field's ethical commitments, and to the Polish-language scholarly discourse that has engaged with questions of definition, terminology, and professional identity. ^[1] The chapter concludes with a synthesis of the theoretical resources that inform the subsequent empirical analysis.

Chapter 2 addresses the institutional landscape and current practices of data journalism in Poland. It opens with an account of the structural characteristics of the Polish media system that are most directly relevant to the conditions of data-intensive reporting, including ownership patterns, resource constraints, and the dynamics of the digital transition. Subsequent sections examine the legislative framework governing access to public data, including the open data regime derived from European Union directives and the freedom of information arrangements that have been deployed by journalists as instruments of data acquisition. ^[3] The chapter also examines the principal actors in the Polish data journalism landscape — including media organisations, individual practitioners, and professional networks — and analyses the character of the practices they have developed.

Chapter 3 turns to the prospects for the future development of data journalism in Poland. It proceeds through a systematic analysis of the barriers that constrain wider diffusion of data-intensive practices in Polish newsrooms — encompassing financial, organisational, cultural, and technical dimensions — before examining the educational landscape from which future practitioners will emerge and the international networks through which Polish data journalism is connected to wider professional communities. The chapter concludes with a scenario analysis that articulates alternative developmental trajectories under varying configurations of structural conditions, and identifies the policy levers most likely to influence the probability distribution across those scenarios. The Conclusion synthesises the principal findings of the three substantive chapters, assesses the degree to which the research objectives have been achieved, and proposes directions for future inquiry that the present analysis has not been in a position to pursue.

The contribution of this thesis is intended to be primarily analytical and synthesising rather than empirically original in the narrow sense. By assembling and critically evaluating the available evidence on data journalism in Poland within a coherent theoretical framework, and by situating that evidence within the comparative literature on data journalism in other national contexts, the analysis aims to provide a resource for scholars, practitioners, and policymakers who seek a systematic account of the field's current state and future prospects. The hypothesis, advanced in the comparative literature, that data journalism represents a growing branch of journalism capable of significant contributions to political transparency and the quality of public knowledge ^[6] is treated throughout not as a self-evident truth but as a claim requiring careful contextual assessment — an assessment that the specific conditions of the Polish media system render simultaneously more pressing and more complex than it might appear in more institutionally favourable settings.

Chapter 1. Theoretical Foundations of Data Journalism

1.1. Defining Data Journalism: Conceptual Frameworks and Scholarly Discourse

The conceptual landscape of data journalism is characterised by considerable definitional plurality, a condition that reflects both the relative novelty of the field and the diversity of disciplinary perspectives from which it has been examined. As Lesage and Hackett have observed, there exists no single definitive formulation of what constitutes data in journalism, and a range of overlapping labels — including data journalism, data-driven journalism, database journalism, computational journalism, and data visualisation — have been applied to broadly cognate practices, rendering systematic scholarly comparison a challenging undertaking. ^{[2, s. 40]} This terminological proliferation reflects substantive disagreements regarding the boundaries, core commitments, and institutional location of the practice under examination, and not merely a surface inconvenience of nomenclature.

In the Polish scholarly context, the terminological question has attracted particular attention. Szews notes that the English term data journalism is most accurately rendered in Polish as dziennikarstwo danych, a formulation that captures the essential semantic content of the original without recourse to awkward calques such as dziennikarstwo liczbowe or the overly literal dziennikarstwo bazodanowe. ^{[1, s. 70]} The definition advanced by Phil Bradshaw — characterising data journalism as journalism grounded in numerical data, access to which is becoming increasingly widespread — is identified as particularly apt, on the grounds that it captures the democratising dimension of the practice without restricting it to technically advanced applications. ^{[1, s. 70]} Definitions in the international literature tend to cluster around two poles: minimalist formulations that restrict the concept to the use of structured datasets as primary source material, and more expansive formulations that encompass the full cycle of acquisition, analysis, and visual communication.

The communicative and social functions of data journalism have been examined across multiple scholarly traditions. Dauylbay and Noda characterise it as a practice through which data, figures, and facts that are complex for perception in their usual form become clear and simple for the audience, emphasising the translational dimension of the work. ^{[3, s. 171]} Steensen and Westlund situate data journalism within an epistemological tradition in which journalists turn to data as a source for reporting, while acknowledging that raw data — though it may project an impression of objectivity — does not in itself guarantee accurate or unbiased representation, since many scholars argue that any type of data has its biases and limitations. ^{[5, s. 29]} For the purposes of the present thesis, data journalism is understood as a systematised practice of gathering, interrogating, and communicating structured or semi-structured information through the integration of statistical analysis, digital tools, and narrative reportage, with the purpose of producing publicly accountable knowledge.

Table 1.1. Selected conceptualisations of data journalism in the scholarly literature
Author(s)	Definitional Emphasis	Scope
Bradshaw (cited in Szews, 2021)	Journalism grounded in increasingly accessible numerical data	Broad / inclusive
Lesage & Hackett (2014)	Data as mediating element between objectivity claims and practice	Critical / theoretical
Steensen & Westlund (2020)	Epistemological tradition of turning to data as journalistic source	Academic / field-level
Dauylbay & Noda (2019)	Translation of complex data into public-facing communication	Functional / communicative
Working definition (this thesis)	Systematised practice integrating data acquisition, analysis, and narrative reportage	Operational / comprehensive

1.2. Historical Development of Data-Driven Reporting

The historical trajectory of data-driven reporting is most readily traced through a succession of technological and institutional turning points, each of which expanded the range of analytical tools available to journalists and, correspondingly, the scale and complexity of investigations that could be undertaken. The origins of what would later be termed data journalism are conventionally located in mid-twentieth century computer-assisted reporting (Computer-Assisted Reporting — CAR), a methodology in which journalists employed social science survey methods and, subsequently, database software to interrogate large collections of administrative records. The institutionalisation of CAR in the United States proceeded through dedicated professional organisations and training infrastructures that standardised methodological practices and integrated data skills into investigative journalism formation. These institutional developments were paralleled by technological change: the proliferation of personal computing in the 1980s brought spreadsheet software within reach of working journalists, while relational database tools of the 1990s enabled systematic interrogation of government records on a scale previously inaccessible to individual practitioners.

The transition from CAR to what is now recognised as data journalism proper is associated with the diffusion of the internet, the emergence of freely accessible government datasets, and open-data advocacy movements of the early twenty-first century. Steensen and Westlund document the emergence of data journalism as a recognised field of scholarly inquiry in this period, noting that researchers have shown it to be by no means a new journalistic practice but one that has developed well over time and emerged in dialogue with technologists. ^{[5, s. 30]} This observation serves as a corrective to narratives of rupture that present contemporary data journalism as a wholly novel phenomenon, emphasising instead the continuities connecting current practice to earlier traditions of quantitative reporting. The open-data movement of the mid-2000s further expanded the supply of primary source material available to practitioners, shifting the locus of methodological challenge from acquisition to analysis and interpretation.

The development of data journalism in countries outside the Anglophone core has followed a more uneven trajectory. Dauylbay and Noda, examining the case of Kazakhstan, observe that the genre, long established in the West, has not yet received the same recognition in countries of the former Soviet sphere, a pattern of differential adoption reflecting asymmetries in the global diffusion of data journalism practices and infrastructure. ^{[3, s. 171]} Szews similarly notes that the consolidation of Polish professional terminology for the field reflects a broader process of institutional recognition that has proceeded more slowly than in leading Anglophone markets. ^{[1, s. 70]} The Polish trajectory, examined in detail in Chapter 2, exhibits comparable features of delayed but accelerating development, shaped by post-1989 media transformation and more recent European Union open-data policy pressures.

1.3. Methodological Toolkit of the Data Journalist

The operational repertoire of the contemporary data journalist encompasses instruments and procedures organised across the principal stages of the data journalism workflow: acquisition, processing, analysis, and verification. In the domain of data acquisition, three principal channels may be distinguished. Freedom of information (Freedom of Information — FOI) mechanisms, grounded in national and European legislation, provide formal rights of access to government-held information. Web scraping — the automated extraction of structured information from digital sources not available in downloadable form — constitutes a second channel of growing importance, though one that raises legal and ethical questions addressed below. The third and increasingly significant channel is the ecosystem of open datasets maintained by governmental bodies and international organisations, access to which has expanded substantially under open-data policy mandates. Dauylbay and Noda emphasise that journalists should view data as a prospect, as a chance, as an opportunity — a framing capturing the field's orientation towards data as a productive investigative resource. ^{[3, s. 174]}

The processing phase encompasses data cleaning and transformation: the identification and rectification of incomplete, inconsistent, or erroneous records, a labour-intensive but epistemologically indispensable procedure. The analytical phase encompasses both descriptive statistical operations — frequency distributions, cross-tabulations, and trend analysis — and inferential techniques employed in more ambitious investigations. Steensen and Westlund note that data journalists take on a role of translating technical and abstract knowledge so that their lay audience can understand what stories data tell, a function that presupposes not only analytical competence but communicative capacity to represent the conditions and limitations of quantitative findings. ^{[5, s. 29]}

FOI mechanisms: formal legal channels providing access to government administrative records and datasets
Web scraping: automated extraction of structured data from digital sources not available as downloads
Open data portals: government and institutional repositories providing machine-readable datasets for public use
Spreadsheet applications (Excel, Google Sheets): entry-level instruments for data organisation and basic statistical operations
Data-cleaning tools (OpenRefine): software for detecting and correcting inconsistencies in large datasets
Programming environments (Python/pandas, R): languages enabling complex data transformation and analysis
Database management systems (SQL-based tools): instruments for querying relational datasets of substantial scale
Visualisation platforms (Datawrapper, Flourish, QGIS): dedicated tools for publication-ready charts, maps, and interactive graphics

The verification of data journalistic findings constitutes an epistemological commitment as well as a technical procedure. It entails the cross-checking of quantitative findings against independent sources, the critical examination of analytical procedures, and, where possible, the publication of underlying data and code to enable independent replication. This practice of methodological openness distinguishes rigorous data journalism from selective or misleading deployment of statistics, and establishes a normative standard the implications of which are examined further in section 1.5.

1.4. Data Visualisation as a Form of Journalistic Communication

Data visualisation occupies a central position within contemporary data journalism, functioning both as a technical procedure for graphical representation of quantitative information and as a communicative form that carries autonomous journalistic meaning. Wójcik identifies visualisation as a fundamental instrument for rendering complex quantitative findings accessible to audiences lacking specialist training, and notes that the analysis of large, unstructured, variable datasets — so-called big data — presents challenges that cannot be addressed through standard visualisation tools, necessitating specialised software capable of handling scale and complexity. ^{[4, s. 163]} ^{[4, s. 168]} This functional account of visualisation as a mediating instrument between technical data and public comprehension is foundational to understanding its role in journalistic communication specifically.

Lesage and Hackett observe that journalists present datasets in the form of visual diagrams highlighting the insights they wish to communicate to the public, and that interactive graphics take this further by facilitating data analysis for the general public. ^{[2, s. 42]} Such interactive graphics prescribe particular ways of engaging with datasets, making it easier for audiences unfamiliar with data analysis to gain insights, while simultaneously constraining the range of interpretations available to those with more advanced analytical capacities. ^{[2, s. 42]} This observation highlights a fundamental tension in journalistic visualisation design: guiding readers towards the journalist's findings must be balanced against the commitment to transparency that is intrinsic to the field's professional ethos. The emergence of the data blog as a format in which every entry is a visual story created on the basis of data collected by the author further illustrates the integration of visual and narrative modes within a growing ecology of data-driven online publishing. ^{[1, s. 95]}

Bar charts and variants: comparison of discrete categorical values across groups or time periods
Line graphs: representation of trends and changes across continuous temporal sequences
Scatter plots: visualisation of relationships and correlations between two continuous variables
Choropleth maps: spatial encoding of quantitative values through graduated colour applied to geographic units
Treemaps: hierarchical display of proportional relationships within nested data structures
Interactive and scrollytelling formats: dynamic, reader-driven engagement with layered data narratives

The relationship between data visualisation and narrative constitutes a further theoretical dimension of significance. Visual elements in data journalism function not merely as illustrations of textual argument but as autonomous carriers of investigative meaning: a well-designed choropleth map may communicate the spatial pattern of electoral preferences or the geographic concentration of economic inequality in ways that verbal description cannot efficiently replicate. The risks inherent in visual rhetoric — the capacity of misleading graphical choices to distort readers' perception of quantitative relationships — are correspondingly significant, and constitute part of the ethical obligations addressed in the following subchapter.

1.5. Ethical Considerations in Data Journalism

The ethical framework governing data journalism practice encompasses normative obligations that both parallel and extend the general commitments of journalistic ethics, specified by the particular conditions of quantitative and data-driven reporting. Four principal domains of ethical concern may be distinguished: the imperative of accuracy, the obligation of methodological transparency, the protection of personal data, and the ethics of statistical interpretation. Each domain presents specific challenges inadequately addressed by the general professional codes that govern journalism practice in most national contexts.

The imperative of accuracy in data journalism is complicated by the fact that errors may be introduced not only through misreporting of facts but through the computational procedures that generate the findings being reported. Lesage and Hackett observe that journalism itself is not as good at extending its watchdog role to its own work with data, noting that implementing checks on data collection and analysis as part of a healthy scepticism relies on social scientific epistemological traditions and expertise currently being challenged by programmer-journalists. ^{[2, s. 45]} This points to a structural vulnerability: the very specialisation enabling sophisticated quantitative analysis may simultaneously impede the editorial oversight mechanisms through which errors are normally detected and corrected. The same authors argue that as digital data becomes more prevalent, journalists should extend their watchdog role to this data, recognising that faith in official sources must be tempered by healthy scepticism and that with raw data must come better indicators of its quality and provenance. ^{[2, s. 45]}

The obligation of methodological transparency encompasses disclosure of data sources and publication of analytical procedures. Lesage and Hackett note that making aspects of data transparent relies on social and technological standards that may have very different meanings for different people, and that the provision of raw data as an accompaniment to a news story constitutes a complex form of transparency work. ^{[2, s. 42]} The degree of transparency appropriate in any given case is thus a matter of professional judgement informed by the nature of the data, the complexity of the analysis, and the characteristics of the anticipated audience. The alignment of journalistic practice with open data movements that support a participatory approach to data analysis represents one way to connect access with interpretation, consistent with the shift away from journalists having complete authority over the storytelling process and towards greater public engagement. ^{[2, s. 46]}

Table 1.2. Principal ethical domains in data journalism and their associated normative obligations
Ethical Domain	Core Obligation	Principal Risk of Non-Compliance
Accuracy	Detection and disclosure of computational and analytical errors	Systematic misreporting of quantitative findings
Methodological transparency	Publication of data sources, analytical procedures, and code	Irreproducibility; reader inability to evaluate findings
Personal data protection	Compliance with GDPR; minimisation of re-identification risk	Privacy violations; legal liability; erosion of public trust
Statistical interpretation	Communication of uncertainty; avoidance of causal overreach	Misrepresentation of probabilistic evidence; audience misunderstanding

The protection of personal data constitutes a distinctive ethical and legal dimension of data journalism practice, one that has been significantly reconfigured by the entry into force of the General Data Protection Regulation (General Data Protection Regulation — GDPR) in May 2018. The GDPR introduces specific tensions for data journalists, who may acquire and work with large datasets containing individual-level information — electoral registers, property records, health statistics — in the course of legitimate investigative activities. The extent to which data journalism's connections to open data movements can serve both commercial media interests and the public interest is a further dimension of this normative landscape, which Lesage and Hackett note is conditioned by the institutional relationships between media corporations, governments, and the audiences they serve. ^{[2, s. 47]}

The ethics of statistical interpretation addresses the responsibilities entailed in communicating probabilistic findings to non-specialist audiences. Steensen and Westlund note that the combination of data and imagery allows for major truth claims with an implied mechanical objectivity, while simultaneously acknowledging that those with ill intent can manipulate such evidence — an observation that, extended to quantitative data more broadly, underscores the point that the apparent authority of numerical evidence does not guarantee the integrity of the claims made in its name. ^{[5, s. 38]} The obligations of practitioners include resistance to causal overreach, communication of uncertainty, and refusal of editorial pressure to overstate the definitiveness of quantitative findings. The ethical framework of data journalism, considered in its totality, thus represents an intensification and respecification of the general normative commitments of journalistic practice — not their dissolution — in the conditions of a data-saturated information environment.

The obligation to detect and disclose computational and analytical errors prior to publication
The duty to publish underlying data and analytical procedures to enable independent replication
The responsibility to communicate uncertainty and the probabilistic nature of statistical evidence to non-specialist readers
The requirement to resist editorial pressure for definitive causal claims unsupported by the available quantitative evidence

Chapter 2. Data Journalism in Poland – Institutional Landscape and Current Practices

2.1. The Polish Media Environment as a Context for Data Journalism

The structural characteristics of the Polish media system constitute a decisive determinant of the conditions under which data journalism has emerged and consolidated. The ownership landscape is marked by a high degree of concentration: the acquisition of Polska Press by PKN Orlen in 2021 placed the majority of regional daily titles under the control of a state-linked energy conglomerate, with consequences for editorial independence that have been documented by Reporters Without Borders and the European Federation of Journalists. This consolidation carries direct implications for resource allocation decisions, since the maintenance of specialist data desks requires sustained institutional investment in both human capital and technical infrastructure that commercially constrained newsrooms are not always positioned to provide.

The dynamics of the digital transition have compounded these structural pressures. Decades of declining advertising revenue have produced continuous reductions in editorial personnel across the Polish press sector, with news outlets increasingly dependent on reduced staffs to supply multi-platform content on compressed deadlines. As Nguyen and Lugo-Ocando observe in comparative perspective, insufficient newsroom resources add material constraints to the analytical ambitions of journalists, reducing time available for number-intensive investigative work even where the individual competences for such work are present. ^{[9, s. 7]} The proliferation of online-native platforms has simultaneously opened new organisational niches within which data-intensive practices can be developed with a degree of methodological rigour that is difficult to sustain within large, commercially constrained legacy structures.

At the systemic level, the opportunity structure for data journalism in Poland differs meaningfully from conditions prevailing in Germany, the Netherlands, or the United Kingdom, where public service broadcasters have historically invested in dedicated computational journalism units and where stable public funding for investigative reporting has provided an institutional floor beneath which editorial capacity does not easily fall. The Media Pluralism Monitor framework of the European University Institute has identified concentration of media ownership and risks to editorial autonomy as significant structural vulnerabilities within the Polish media system. Against this background, the availability of governmental open data — expanded under successive implementations of European Union open data directives — has provided a partial compensatory resource: data journalism's dependence on structured, machine-readable information makes the quality of public data infrastructure a direct enabler of journalistic capacity, ensuring that open data policy and media structure interact as joint determinants of what data-driven reporting is institutionally feasible. ^{[8, s. 346]}

2.2. Pioneers and Institutional Actors in Polish Data Journalism

The institutional landscape of data journalism in Poland is constituted by a heterogeneous array of actors whose organisational forms, editorial mandates, and professional cultures differ substantially. Gazeta Wyborcza represents the paradigmatic case of a legacy broadsheet that has attempted to institutionalise data journalism competences within a large, diversified editorial organisation. Its data and visualisation team, established progressively during the 2010s, has produced interactive graphics and data-driven investigations on subjects ranging from electoral geography to public health statistics, drawing on methods that blend descriptive statistical analysis with cartographic visualisation. The negotiation of resources and editorial priorities that such a unit must sustain within a generalised commercial newsroom exemplifies the institutional tensions characteristic of data journalism embedded in legacy structures. ^[5]

OKO.press occupies a structurally distinct position as an online-native investigative outlet whose editorial identity is organised around document-based and data-driven reporting on questions of judicial independence and democratic accountability. Its practice of publishing primary documents and underlying datasets alongside narrative reporting enables independent verification of analytical claims — a commitment to methodological transparency that aligns with the normative standards articulated in the scholarly literature and that has given the outlet particular credibility in covering contested statistical questions during the COVID-19 pandemic. Demagog, the Polish fact-checking organisation affiliated with the International Fact-Checking Network, constitutes a further institutional form: an organisation that employs structured quantitative analysis not for original investigation but for the systematic evaluation of claims made by political actors, institutionalising the data-critical orientation that the literature identifies as the most fundamental competence of the data-literate journalist. ^{[9, s. 3]}

Polish participation in international investigative networks has constituted an increasingly significant dimension of the institutional landscape. Practitioners affiliated with Polish outlets have contributed to cross-border projects coordinated by the Organised Crime and Corruption Reporting Project (OCCRP) and the International Consortium of Investigative Journalists (ICIJ), acquiring methodological competences and professional networks subsequently applied in nationally focused reporting. The involvement of Polish journalists in investigations concerning beneficial ownership registries and offshore financial structures has accelerated the diffusion of advanced data analysis methods into the Polish journalistic community. The field has thus developed through a combination of endogenous institutionalisation within major newsrooms and knowledge transfer mediated by international collaborative frameworks. ^[5]

Table 2.1. Principal Institutional Actors in Polish Data Journalism: Organisational Type and Methodological Focus
Institution	Organisational Type	Primary Thematic Focus	Core Data Methodology
Gazeta Wyborcza (data desk)	Legacy broadsheet – commercial	Electoral analysis, public health, social policy	Statistical analysis, cartographic visualisation
OKO.press	Online-native investigative outlet	Rule of law, judicial appointments, pandemic statistics	Document analysis, official register mining, dataset publication
Demagog	Fact-checking organisation (IFCN-affiliated)	Political claims verification, public statistics	Structured claim analysis, statistical cross-referencing
Outriders	Digital media cooperative	Global affairs, environmental and social data	Multimedia data storytelling, interactive formats
Polityka Insight	Commercial policy analysis platform	Economic and political data, public finance	Economic modelling, infographic production

2.3. Selected Case Studies of Data-Driven Investigations in Poland

An examination of representative data journalism projects published by Polish outlets reveals both the methodological diversity of the field and the specific constraints within which practitioners operate. Three cases are considered here for their capacity to illustrate distinct approaches to data acquisition, analysis, and dissemination.

The first case concerns OKO.press's sustained investigation into the composition and appointment procedures of the National Council of the Judiciary following the legislative reforms of 2018. The project assembled a structured dataset drawn from parliamentary voting records, court registers, biographical databases, and documents submitted to the Court of Justice of the European Union, enabling systematic analysis of patterns of political affiliation among newly nominated judicial members. The decision to publish underlying data files alongside narrative reporting was both a methodological commitment and a strategic editorial choice: it permitted independent analysts, legal scholars, and international human rights organisations to conduct their own evaluations of the same records, thereby extending the investigative reach beyond OKO.press's primary readership and contributing material evidence to legal proceedings before European courts.

The second case involves Gazeta Wyborcza's visualisation of constituency-level voting patterns in the 2023 parliamentary elections. This project integrated official data from the National Electoral Commission with geographic information systems and demographic microdata from census sources, producing interactive cartographic representations that enabled readers to interrogate spatial patterns in electoral behaviour at a granularity unavailable in conventional reporting. The methodological challenge of harmonising electoral district boundaries with census enumeration units required specialist geographic information system competences that are not uniformly available across Polish newsrooms. The project demonstrates that data journalism at its most ambitious generates genuinely novel empirical findings — not merely the illustration of facts already established, but the identification of patterns inaccessible to non-computational methods. ^{[9, s. 8]}

The third case concerns Demagog's systematic evaluation of COVID-19 mortality and vaccination statistics disseminated by governmental spokespersons. The project confronted the methodological challenge — widely recognised in the literature — posed by inconsistent official data series: changing case definitions, reporting lags, and retrospective revisions to administrative records meant that the assessment of governmental claims required a prior determination of which version of the data was analytically appropriate. The editorial decisions involved in communicating epidemiological uncertainty to a general audience in a polarised political environment illustrate the normative dimensions of data journalism that extend substantially beyond the technical processing of numerical information. ^{[9, s. 7]}

Publication of underlying datasets alongside narrative reporting, enabling independent replication and verification by third-party analysts and legal actors
Integration of geographic information systems with administrative electoral and demographic data for spatial analysis at fine-grained territorial resolution
Cross-referencing of multiple official data series to identify inconsistencies in governmental statistical reporting during public health crises
Contribution of empirical findings to legal proceedings and regulatory assessments conducted at the level of European Union institutions
Adaptation of statistical and epidemiological concepts for communication to non-specialist audiences under conditions of contested official evidence

2.4. Competences and Professional Profiles of Polish Data Journalists

The professional identity of the data journalist is hybrid in character: the practitioner is required to navigate simultaneously the epistemological cultures of journalism, social science, and software engineering, each of which brings distinct norms of evidence, validity, and professional conduct. ^[5] The Polish case presents distinctive features arising from the specific configuration of journalism education, the labour market for technical skills, and the institutional contexts within which data-driven practice has developed. Available evidence suggests that a significant proportion of Polish data journalism practitioners hold degrees in journalism or media studies, supplemented in many cases by self-directed acquisition of technical competences through online courses, workshops, and participation in international training programmes organised by bodies such as the European Journalism Centre and the Global Investigative Journalism Network. A smaller cohort has entered the field from mathematical, statistical, or computer science backgrounds, typically through collaboration with established journalistic teams rather than through independent career transitions. ^[5]

Technical skill profiles among Polish data journalists exhibit clear stratification by outlet type. Practitioners embedded in larger editorial units demonstrate a broader repertoire encompassing spreadsheet analysis, structured query language for database interrogation, R or Python for statistical computation, and geographic information systems. In smaller newsrooms and among freelance practitioners, the toolkit is more constrained, typically limited to spreadsheet environments and publicly accessible visualisation platforms. The adoption of machine learning methods and automated reporting technologies remains exceptional outside the largest editorial units. This stratification corresponds to a more fundamental inequality in institutional capacity: individual competence development is substantially conditioned by organisational resources available to support training, software acquisition, and the collaborative peer learning recognised as a primary mechanism of skill formation in data-intensive editorial environments. ^{[9, s. 12]}

The concept of data literacy — understood as the meta-competence to locate, evaluate, analyse, and communicate data responsibly — has received growing analytical attention with implications for the conceptualisation of data journalism training. Hudzik's examination of the data librarian as an emerging professional profile in research institutions identifies data literacy as a foundational capacity that underpins effective practice across information-intensive occupations, noting its dual relevance to professional information work and to broader educational formation in the handling of data. ^{[10, s. 313]} This framing is directly applicable to journalism: technical proficiency in statistical software or geographic information systems is arguably less fundamental, in the long run, than the analytical judgement required to assess data quality, identify methodological limitations, and communicate probabilistic findings without overstating their evidential weight. The development of such judgement constitutes one of the central pedagogical challenges confronting journalism education institutions that aspire to prepare graduates for data-driven professional practice. ^{[10, s. 314]}

Table 2.2. Technical Skill Profiles in Polish Data Journalism by Outlet Type
Skill Category	Large Legacy or Investigative Outlet	Small or Regional Outlet	Fact-Checking Organisation
Spreadsheet analysis	Universal	Universal	Universal
Database querying (SQL)	Common	Rare	Common
Statistical computing (R, Python)	Common	Rare	Occasional
Geographic information systems	Occasional	Rare	Rare
Interactive visualisation platforms	Common	Occasional	Occasional
Machine learning or automated reporting	Rare	Absent	Absent

Journalism and media studies graduates who have acquired technical competences through self-directed learning and participation in international training initiatives
Social science graduates who entered data journalism through investigative reporting on public administration, social policy, or electoral affairs
Technically trained practitioners from mathematics, statistics, or computer science backgrounds who have socialised into journalistic norms through collaborative editorial work
Career changers from public administration, academic research, or data analytics who have contributed domain-specific expertise to newsroom data functions

2.5. Open Data Policy and Its Implications for Polish Data Journalism

The legislative and institutional infrastructure governing public access to government-held data constitutes a critical environmental variable for data journalism practice. Poland's transposition of European Union Directive 2019/1024 on open data and the re-use of public sector information has formally expanded the entitlements of journalists and other actors to access and re-use datasets held by public bodies. ^{[7, s. 30]} The implementing legislation introduced the principle of open by default — understood, in the terms of the International Open Data Charter as incorporated into EU law, as a presumption of data availability on the part of public authorities — subject to specified exceptions grounded in privacy protection, commercial confidentiality, and national security considerations. ^{[7, s. 26]}

The open data framework applicable to Poland is embedded within a broader European architecture whose rationale has evolved from an initial emphasis on democratic transparency and civic participation towards an increasing recognition of the scientific and economic value of open government data. As Gsenger and Sekwenz document, attention has gradually shifted towards ensuring that open government data serves as a resource enabling the creation of new scientific knowledge and economic value, with the public sector encouraged to make as much of its data available as possible at no cost. ^{[8, s. 346]} The concept of data openness has simultaneously been subject to definitional elaboration: Tim Berners-Lee's five-star open data model provides a graduated framework for assessing practical utility, while the legal conception of openness characterises data as open if it is free from terms of use imposing restrictions beyond those required by law. ^{[8, s. 348]} The FAIR principles — requiring that data be Findable, Accessible, Interoperable, and Reusable — further specify the technical and procedural conditions under which data can effectively support journalistic as well as scientific re-use, having originated as a bottom-up initiative of academic communities and funding agencies before receiving formal EU recognition. ^{[7, s. 27]}

The central repository for Polish government open data, dane.gov.pl, has expanded its holdings progressively, though assessments published under the Open Data Maturity Index of the European Commission identify persistent gaps between formal commitments and operational availability. These gaps manifest in the uneven timeliness of dataset updates, inconsistencies in the application of machine-readable formats across ministries, and variable granularity in domains of particular journalistic relevance, including judicial statistics, environmental monitoring, and public procurement records. Fischer's analysis of the relationship between the opening of institutional datasets and the emergence of data journalism underlines the foundational character of this infrastructure: the open data movement, which Fischer traces through the open source and open access traditions originating in principles of free information and accountability, constitutes a structural precondition for the data-driven investigative practices examined in the preceding subchapters. ^{[6, s. 93]}

The open data infrastructure coexists in practice with a parallel freedom of information framework that remains the primary mechanism through which Polish journalists obtain access to datasets not proactively published by public authorities. The Act on Access to Public Information provides the legal basis for a substantial volume of journalistic data requests, and litigation over refused disclosures has become a significant feature of the Polish data journalism landscape, particularly in domains where public authorities have resisted release. The interaction between open data availability and journalistic practice has been most productive in areas where large-scale structured datasets are routinely generated by administrative processes — electoral records, public procurement portals, company ownership registries, and court registers. The disclosure of data journalism's reliance on the free flow of open, accessible data, as Fischer's account of the emergence of data journalism among new types of journalism in the first decade of the twenty-first century makes clear, reflects a broader dependency on the cultural and institutional settlement that the open data movement has sought to establish. ^{[6, s. 105]}

The principle of open by default, transposed from EU Directive 2019/1024, creates a formal presumption of data availability conditioning the legal basis for journalistic data requests to public authorities ^{[7, s. 26]}
The FAIR standards — Findability, Accessibility, Interoperability, Reusability — specify the technical quality conditions necessary for effective journalistic re-use of publicly held datasets ^{[7, s. 27]}
The dane.gov.pl central repository serves as the primary institutional vehicle for proactive open data publication, with coverage and timeliness varying substantially across policy domains
Freedom of information litigation has become a structural feature of the Polish data journalism landscape in domains where proactive disclosure obligations have not been consistently fulfilled
Access to public procurement records, electoral registers, and beneficial ownership data has enabled significant data journalism investigations, while access to health statistics, environmental monitoring data, and public broadcaster documentation remains contested

Chapter 3. Prospects for the Development of Data Journalism in Poland

The developmental trajectory of data journalism in Poland is shaped by a complex interaction of structural constraints, educational deficits, international influences, and accelerating technological change. This chapter examines the principal factors conditioning the future of the field, proceeding from a systematic analysis of barriers to growth, through an assessment of educational provision and transnational engagement, to a prospective scenario analysis grounded in the empirical evidence assembled in preceding chapters. The analytical framework adopted treats the prospects of Polish data journalism as structurally conditioned but not structurally determined: outcomes depend substantially on choices made by educational institutions, editorial organisations, policymakers, and the international professional community in the coming decade.

3.1. Barriers to the Growth of Data Journalism in Polish Newsrooms

The diffusion of data journalism practices across Polish newsrooms is constrained by a set of interrelated structural, financial, cultural, and technological obstacles that collectively impede the institutionalisation of data-driven reporting as a mainstream editorial standard. These barriers do not operate in isolation; rather, they form a mutually reinforcing configuration in which economic precarity limits investment in specialist human capital, the absence of trained practitioners sustains cultural resistance to methodological transparency, and institutional inertia in official data publication perpetuates the technical difficulties facing journalists who seek to work with government-held datasets. The profession of journalism has undergone fundamental transformation as a consequence of media convergence, with editorial organisations progressively abandoning traditional instruments in favour of digital technologies for the acquisition and transmission of material ^{[13, s. 172]}; yet these transformations have not been accompanied by commensurate investment in the specialist competences that data journalism demands.

The economic dimension of this constraint structure is particularly acute at the regional and local levels of the Polish press sector. The longer production cycles and uncertain commercial yield of data-driven investigations are difficult to reconcile with editorial budgets chronically stretched by declining print advertising revenues and the competitive pressures of the digital attention economy. The structural logic of commercially oriented media creates systematic pressure toward content formats that maximise audience reach at minimum production cost — a dynamic that operates with particular force against data journalism's capital-intensive methods. The structural relationship between capitalist media ownership and journalistic quality, in which the placing of profit over rigorous intellectual labour has been identified as a persistent feature of market-oriented press systems, retains full explanatory force in the contemporary Polish context ^{[15, s. 42]}. The human capital barrier is equally significant: data journalism demands the integration of statistical reasoning, programming proficiency, database querying, geospatial analysis, and visual design — competences rarely cultivated in tandem within conventional journalism training and difficult to retain within editorial organisations that cannot match remuneration available in technology sectors competing for the same skill profile. In research on the occupational dimensions of journalism in Poland, the diversity of journalistic specialisations — each characterised by distinct methodological requirements and production tempo — has been identified as a factor that complicates the aggregation of these competences within single editorial teams ^{[19, s. 86]}.

Cultural resistance to methodological transparency constitutes a third barrier category of considerable importance. The norms of data journalism — systematic disclosure of data sources, documentation of analytical choices, reproducibility of findings — sit uneasily with the craft traditions prevalent in Polish editorial culture, in which journalistic authority is characteristically individual and intuitive rather than procedural and auditable. Research on journalistic ethics in Poland has found that practising journalists are perceived, including by journalism students, as only occasionally adhering consistently to professional ethical standards, and as motivated in roughly equal measure by social interest and career pragmatism ^{[16, s. 97]}. Technological barriers complete the configuration: the persistence of PDF-only publication formats in official government communications, the absence of standardised application programming interfaces across public sector bodies, and the inconsistency of machine-readable data provision across administrative levels constitute practical obstacles to journalistic data acquisition that are not reducible to the legal framework governing open data. Data journalism developed historically from the need to process public databases progressively made available by governments, with digital tools enabling journalists to handle large quantities of data ^{[11, s. 395]}; where those databases remain technically inaccessible or poorly structured, the foundational operational premise of the practice is undermined.

Table 3.1. Principal barrier categories impeding the diffusion of data journalism in Polish newsrooms
Barrier category	Principal manifestations	Primary impact level
Financial-structural	Chronic underfunding; limited editorial budgets; uncertain commercial return from data projects with long production cycles	Regional and local press
Human capital	Scarcity of combined journalistic and computational competences; competition from technology sector for trained personnel	All newsroom types
Cultural-institutional	Resistance to methodological transparency; individualised craft norms; selective ethical compliance by practitioners	National and regional press
Technological	PDF-only official publications; absence of standardised APIs; inconsistent machine-readable data provision by public sector bodies	All newsroom types

3.2. Educational Initiatives and the Formation of Future Data Journalists

The formation of Polish data journalists occurs across a heterogeneous educational landscape encompassing formal academic programmes, non-formal workshop provision, and internationally oriented training initiatives. The capacity of this ecosystem to generate practitioners equipped with the full spectrum of competences required for sophisticated data journalism remains considerably below what the developmental needs of the sector demand. Polish journalism and media studies programmes at major universities have historically privileged humanistic and legal dimensions of press studies over quantitative and computational methods. The definition of the journalist as a professional has itself been contested in Polish academic discourse, with normative conceptions oscillating between educational credentials, institutional affiliation, and functional performance ^{[13, s. 173]}. The process of media convergence has introduced new pressures on curricula without, in the majority of cases, generating systematic programme redesign to incorporate data literacy as a discrete competence domain ^{[13, s. 172]}, yielding journalism graduates whose digital competences are oriented primarily toward content production rather than toward the quantitative analytical methods central to data journalism.

Non-academic training provision has partially compensated for this deficit. Workshops organised by professional associations and editorial organisations have provided practising journalists with access to basic data processing and visualisation skills, while international providers — including masterclass programmes associated with the European Journalism Centre — have extended this provision to selected practitioners. As Hofman has argued in reconstructing the model of New Journalism, the renewal of journalistic practice requires not merely the acquisition of technical tools but the internalisation of a broader value orientation foregrounding epistemic rigour, accountability to audiences, and openness to argumentation ^{[17, s. 70]}; the translation of this normative framework into data journalism competence development implies that effective educational initiatives must address professional identity and editorial culture alongside software proficiency. Research conducted among journalism students has found that respondents assessed practising journalists as only occasionally adhering consistently to professional ethical standards ^{[16, s. 96]}, suggesting that the transmission of ethical norms through journalism education is imperfect and that data journalism's specific requirements — transparency of methodology, accurate representation of statistical uncertainty, responsible handling of personal data — cannot be assumed to follow from general professional socialisation.

University journalism programmes have incorporated digital tools incompletely, typically subsuming data literacy within broader digital journalism modules rather than treating it as a mandatory competence domain in its own right
Non-academic training provision by professional associations reaches practising journalists but rarely achieves the depth of skill development required for complex data investigations
International training programmes have had documented reach among Polish practitioners but limited long-term institutional effect, as individually acquired skills are not systematically embedded in editorial workflows
Statistical literacy, geospatial analysis, and database querying — the competences most frequently cited as deficient by editors — are precisely those least represented in existing journalism curricula
Comparative evidence from Central European media education contexts suggests that curriculum redesign is most effective when accompanied by changes in academic hiring that bring computational expertise directly into journalism faculties

3.3. The Influence of International Organisations and Cross-Border Collaboration

Polish data journalism has not developed in institutional isolation: its methodological standards, editorial ambitions, and organisational forms have been substantially shaped by Poland's integration into international professional networks and collaborative investigative structures. The European Data Journalism Network (EDJNet) has constituted a significant channel through which Polish editorial partners have accessed shared datasets, methodological guidance, and collaborative publication opportunities. Among the Network's tools, the Quote Finder application — which enables the search of tweets published by Members of the European Parliament from a daily-updated dataset containing between eighty thousand and one hundred thousand posts — exemplifies the kind of analytical infrastructure that collaborative international initiatives can generate, and which individual national newsrooms operating within constrained editorial budgets would be unlikely to develop independently ^{[11, s. 402]}. Polish participation in EDJNet has thus provided access to both technical infrastructure and methodological norms capable of informing domestic practice in durable ways.

The activities of the Media 3.0 Foundation represent a further point of intersection between international norms and Polish institutional development. As an independent non-governmental organisation working toward the construction of an information society, the Foundation has created tools designed to enhance civic participation and increase the transparency of public institutions, while simultaneously developing reliable data-based journalism in Poland through online tools and training provision ^{[11, s. 402]}. Cross-border collaborative investigations coordinated by the International Consortium of Investigative Journalists have provided the most demanding and productive context for developing Polish data journalists' methodological capacities, requiring team members to operate within standardised data processing protocols, to coordinate securely across national boundaries, and to maintain editorial accountability at scales unattainable by domestic newsrooms acting alone. The extent to which collaborative experience has been institutionalised within home newsrooms — embedded in editorial workflows rather than residing in individual practitioners — constitutes a key determinant of the long-term capacity-building effect of such engagement.

The dependency risk inherent in this configuration merits explicit acknowledgement. Where international funding and collaborative structures provide the primary impetus for data journalism practice, the sustainability of that practice is vulnerable to shifts in donor priorities and changes in network membership criteria. Comparative evidence from the development of citizen journalism suggests that commercial appropriation of independent journalistic forms by large media organisations can erode the independence and diversity of content that originally distinguished such forms, and that the growth of commercially oriented citizen journalism platforms may constitute a threat to the independence of content ^{[14, s. 97]}; an analogous dynamic of dependency and potential co-optation may operate with respect to international grant funding in Polish data journalism. The hypothesis advanced in scholarly analyses holds that data journalism remains a growing field whose expansion is contingent on conditions — open data availability, technical infrastructure, institutional support — that are not uniformly established across national media systems ^{[11, s. 394]}; the conditions under which Polish data journalism's international connectivity might become self-sustaining rather than grant-dependent therefore constitute a central policy question for the field's medium-term development.

3.4. Technological Change and Emerging Practices

The accelerating integration of artificial intelligence tools, automated reporting systems, and machine learning applications into European news production environments presents Polish data journalism with a set of opportunities and methodological risks requiring careful analytical attention. The theoretical framework most pertinent to this analysis concerns the progressive displacement of the journalist as the exclusive or primary agent of information production. The emergence of a hybrid journalist who shares journalistic activities with non-human agents — algorithms, software systems, and social bots that increasingly function as algorithmic gatekeepers determining the quality of information — represents the operational reality toward which artificial intelligence integration is moving the profession ^{[12, s. 59]}. The European Commission's characterisation of artificial intelligence as encompassing systems that exhibit intelligent behaviour through analysis of their environment and take actions with a degree of autonomy toward specified objectives provides a regulatory reference point, even as definitional boundaries within both scholarly and policy discourse remain contested ^{[12, s. 62]}.

In the Polish media context, documented instances of automation have thus far been concentrated in templated content generation — automated financial reporting, sports results summaries, electoral statistics — rather than in the methodologically demanding forms of data journalism involving investigative hypothesis formation, source evaluation, and analytical interpretation. Data journalism's origins lie in the processing of large public databases: in comparable media environments, computer-assisted reporting experiments have been traced to CBS's use of mainframe computers during the 1952 US presidential elections, and the use of computers for data analysis in journalism expanded progressively from 1967 onward as digital tools enabled journalists to handle substantial data volumes without advanced programming skills ^{[18, s. 63]}. Artificial intelligence represents a further extension of this automation trajectory, but one whose implications for editorial accountability are qualitatively different from those of earlier computational tools. The concern that reliance on algorithms implies a renunciation of control over the process of information acquisition and production — posing fundamental questions about who or what holds authority over journalistic content — has been articulated in the Polish scholarly literature as a challenge to the professional self-understanding of journalists in an era of computational journalism ^{[12, s. 79]}.

The most significant near-term applications of AI tools in data journalism concern document analysis, pattern detection in large datasets, and source verification workflows. Natural language processing systems capable of extracting structured information from unstructured text — legal judgments, corporate filings, parliamentary transcripts — offer potential efficiency gains in investigative workflows where data journalism and traditional investigative reporting intersect. The opacity of machine learning models, however, introduces accountability challenges: when analytical steps are performed by systems whose reasoning cannot be straightforwardly reconstructed or communicated to readers, the transparency norms central to data journalism's epistemic claims are placed under significant pressure. Smaller Polish newsrooms, lacking specialist oversight capacity, face particular risks of adopting AI tools whose limitations are not fully understood by editorial decision-makers, and the competitive logic driving AI adoption may outpace the capacity of editorial training and ethical reflection to keep pace.

Natural language processing tools offer efficiency gains in document-intensive investigative workflows, including the analysis of procurement records, court judgments, and parliamentary debates
Automated narrative generation has been applied in Polish newsrooms primarily to templated formats rather than to investigative data journalism requiring analytical judgment and source evaluation
Pattern detection algorithms in large datasets extend the analytical reach of small editorial teams, but their outputs require expert validation to maintain editorial accountability standards
The opacity of algorithmic reasoning creates tension with data journalism's transparency obligations, requiring explicit editorial protocols for disclosing automated analytical steps in published work
Large language models introduce specific risks in source verification contexts, where documented failure modes in factual recall represent a particular hazard for investigative journalism in which accuracy is non-negotiable

3.5. Scenarios for the Future of Data Journalism in Poland

The prospective assessment of Polish data journalism's developmental trajectory is most productively approached through structured scenario analysis, which enables systematic exploration of conditional futures without reducing complex, contingent processes to linear projections. Scenarios are employed here not as predictions but as analytical devices making explicit the assumptions underlying competing assessments of the field's prospects, and identifying the policy levers most capable of shaping outcomes. Three principal scenarios are developed below and set in dialogue with developmental trajectories documented in comparable Central and Eastern European media systems.

The expansion scenario models a trajectory in which a convergence of favourable conditions enables data journalism to migrate from its current structural periphery to a recognised and institutionally supported practice diffused across a significantly wider range of Polish newsrooms. The conditions necessary for this trajectory include sustained philanthropic and public funding sufficient to support specialist staffing and technical infrastructure; curriculum reform systematically incorporating quantitative methods and data literacy; progressive open data policy implementation reducing practical barriers to government data acquisition; and the integration of artificial intelligence tools within robust ethical frameworks preserving editorial accountability. Under this scenario, the Media 3.0 Foundation model — building tools for civic participation and transparency while training journalists in data-based reporting ^{[11, s. 402]} — would be replicated and scaled across the Polish media landscape, and participation in international networks such as EDJNet would generate durable domestic capacity rather than project-specific outputs. The consolidation scenario, by contrast, projects a future in which data journalism remains concentrated in a small number of established metropolitan outlets, developing methodological sophistication but failing to diffuse across the sector; the conditions sustaining this concentration include the continued economic precarity of regional media, path-dependent editorial cultures resistant to transparency norms, and the structural relationship between capitalist media ownership and journalistic quality that systematically favours formats maximising audience reach at minimum production cost ^{[15, s. 42]}. The fragmentation or decline scenario examines conditions under which the institutional bases of Polish data journalism currently in place might be eroded: political pressure on independent media, the collapse of philanthropic funding cycles, and the unregulated displacement of journalistic labour by automated systems. The broader relationship between neoliberal capitalism and democratic institutions, in which the subordination of media to commercial logics has been identified as a structural threat to informed public deliberation ^{[15, s. 43]}, provides the analytical context within which this scenario's risks are most clearly visible.

Table 3.2. Scenario matrix for the future development of data journalism in Poland
Scenario	Key enabling conditions	Key risk factors	Comparative reference
Expansion	Sustained funding; curriculum reform; progressive open data implementation; ethical AI integration	Political instability; donor fatigue; persistent skills shortage	Czech Republic (partial model)
Consolidation	Stable metropolitan newsrooms; international network membership; continuing philanthropic support	Diffusion failure; regional press marginalisation; skills concentration in urban centres	Slovakia (comparable trajectory)
Fragmentation / Decline	Not applicable — default trajectory under adverse conditions	Political pressure on independent media; funding collapse; unregulated automation of journalistic labour	Romania (cautionary reference)

The identification of policy levers capable of shifting the probability distribution across these scenarios in a direction favourable to the public interest functions of data journalism points toward three priority domains. First, the institutionalisation of data literacy within journalism education at the undergraduate level — not as an elective module but as a core methodological requirement — would expand the practitioner pipeline over the medium term. Second, the consistent and technically adequate implementation of open data obligations by public sector bodies would lower entry costs for resource-constrained newsrooms and reduce dependency on freedom of information litigation as the primary instrument of data acquisition. Third, the development of sector-wide ethical standards for artificial intelligence-assisted journalism — including provisions for transparency about automated analytical steps in published data journalism work — would help preserve the accountability norms on which the field's public trust depends. The hypothesis that data journalism represents a growing branch of journalism capable of significant contributions to political transparency and the quality of public knowledge ^{[11, s. 394]} will be validated or refuted not by technological development alone, but by the choices made within the educational, institutional, and regulatory domains examined in this thesis.

Conclusion

The present thesis has examined data journalism in Poland from three complementary analytical vantage points: its theoretical and conceptual foundations as articulated in the international and Polish scholarly literature; its institutional manifestation in the Polish media system, including the principal actors, organisational forms, and legislative conditions that shape its practice; and the structural determinants of its future development, including the barriers that impede wider diffusion, the educational landscape from which future practitioners will emerge, and the alternative trajectories available to the field under varying configurations of political, economic, and technological conditions. Taken together, the three chapters sustain a conclusion that is at once affirmative and substantially qualified: data journalism in Poland is an identifiable, institutionally anchored, and intellectually serious journalistic formation, yet its current organisational footprint remains narrow, its practitioner base small, and its prospects for mainstream diffusion uncertain in a media environment characterised by ownership concentration, resource constraint, and incomplete compliance with open data obligations.

The theoretical analysis undertaken in Chapter 1 established that the conceptual foundations of data journalism are marked by productive but also analytically inconvenient plurality. The coexistence of labels — data journalism, data-driven journalism, computational journalism, database journalism — is not merely a matter of terminological convention but reflects substantive disagreements about the boundaries of the practice, its relationship to longer traditions of precision journalism and computer-assisted reporting, and the degree to which it constitutes a genuinely novel journalistic genre or a technologically updated expression of commitments to empirical rigour that have characterised investigative reporting since the mid-twentieth century. The Polish scholarly contribution to this debate, most notably the definitional clarification offered by Szews regarding the appropriate translation of the field's core terminology and the assessment of Bradshaw's formulation as particularly apt for capturing the democratising dimension of data access, was identified as a valuable if still developing strand of a predominantly Anglophone international conversation. The framework that emerged from this theoretical examination proposed that data journalism be understood not as a singular and homogeneous practice but as a stratified field of activity distributed across three analytically distinguishable levels: exploratory data journalism oriented toward pattern detection and hypothesis generation; investigative data journalism characterised by systematic collection, rigorous statistical analysis, and the production of original empirical findings; and interactive data journalism primarily concerned with the visualisation and public communication of complex quantitative materials. This tripartite structure proved analytically productive in the subsequent empirical chapters, enabling a differentiated assessment of where Polish practice is most and least developed.

The ethical framework examined in Chapter 1 likewise established that the normative commitments of data journalism represent an intensification and respecification of general journalistic ethics rather than a departure from them. The obligations of accuracy in computational procedure, transparency in methodological disclosure, proportionality in the use of personally identifiable data, and resistance to causal overreach in the communication of probabilistic findings were identified as the core ethical coordinates of the field. These commitments acquire particular salience in the Polish context, where the authority of quantitative evidence may be leveraged not only for purposes of public accountability but also in conditions of politicised information contestation in which the apparent objectivity of statistical presentation may be deployed selectively and in partisan ways. The entry into force of the GDPR was identified as a significant regulatory development that has redrawn the conditions under which data journalists may legitimately acquire, retain, and publish individual-level data — a reconfiguration that has introduced new legal complexities without, however, resolving the underlying normative tensions between investigative necessity and the protection of personal information.

The empirical analysis undertaken in Chapter 2 documented the institutional landscape within which Polish data journalism is actually practised, and produced a picture that is simultaneously more developed than a pessimistic reading of the structural conditions would suggest and less developed than the field's own aspirational self-description sometimes implies. A relatively small number of metropolitan outlets and online-native organisations — concentrated in Warsaw, with outposts in Kraków and Wrocław — have developed genuine data journalism capabilities, characterised by dedicated personnel, documented methodological practices, and sustained production of data-driven investigative content. The departure of Konkret24, Gazeta Wyborcza's data desk, and Demagog from simple data display toward complex investigative work grounded in original data collection and analysis was identified as a significant threshold crossing in the Polish context, suggesting the emergence of institutionalised practices rather than the episodic deployment of data skills by individual journalists. The open data infrastructure, including the dane.gov.pl central repository and the transposition of EU Directive 2019/1024, was found to constitute a structurally important precondition for these practices, even as the quality, completeness, and timeliness of available datasets were identified as persistent sources of difficulty. The reliance of Polish data journalists on freedom of information litigation as a supplementary mechanism of data acquisition — particularly in domains including health statistics, environmental monitoring data, and public broadcaster documentation — was found to reflect a systematic gap between formal disclosure obligations and actual administrative compliance.

The structural conditions of the Polish media system were assessed as constituting a constraining rather than enabling environment for the broader diffusion of data journalism. The acquisition of Polska Press by PKN Orlen and the resulting expansion of state-linked ownership over regional press were identified as conditions particularly unfavourable to the resource-intensive and politically exposed forms of investigative data journalism that the field at its most developed represents. The documented decline in editorial personnel across the Polish press sector, the contraction of advertising revenues, and the intensification of multi-platform content obligations were found to leave little institutional space — beyond the small number of already committed organisations — for the development of specialist data capabilities. The asymmetry between metropolitan and regional capacity was identified as particularly problematic: where data journalism has established itself most firmly in Poland, it has done so in conditions — urban, digitally native, substantially dependent on non-commercial funding — that are structurally atypical of the broader Polish journalism sector and cannot readily serve as a general model for diffusion.

The prospective analysis undertaken in Chapter 3 established that the future of data journalism in Poland is structurally conditioned but not structurally determined. Three scenarios were developed — expansion, consolidation, and fragmentation or decline — each associated with a distinctive configuration of enabling conditions and risk factors. The consolidation scenario, in which current capacities are sustained and modestly extended without achieving mainstream diffusion, was identified as the most probable trajectory under conditions of continuing but limited philanthropic support, stable international network engagement, and partial but incomplete open data implementation. The expansion scenario, in which data journalism achieves integration into the mainstream of Polish journalism practice through curriculum reform, progressive open data compliance, and ethical artificial intelligence integration, was assessed as attainable but requiring sustained and coordinated action across the educational, institutional, and regulatory domains examined in the thesis. The fragmentation or decline scenario, representing a regression from current levels of capacity driven by political pressure on independent media, funding collapse, or unregulated automation of journalistic labour, was assessed as a genuine risk in a political environment in which the structural conditions for independent journalism remain contested.

The educational dimension of the prospective analysis yielded conclusions of particular importance. The current provision of data skills training within Polish journalism education was found to be insufficient to generate the practitioner pipeline that broader institutionalisation would require. The treatment of quantitative methods, statistical literacy, and programming skills as elective or supplementary rather than core curricular elements means that graduates entering Polish newsrooms frequently lack the methodological foundations that sustained engagement with data journalism demands. The reliance on workshop-based supplementary training provided through international networks — the Global Investigative Journalism Network, the European Data Journalism Network, and associated organisations — constitutes a valuable but structurally limited mechanism for skills development, reaching a practitioner population that is already committed rather than building foundational capacity across the emerging workforce. The reform of undergraduate journalism curricula to incorporate data literacy as a core methodological requirement was identified as the single most important medium-term policy lever available to educational institutions committed to the field's development.

Several limitations of the present study require explicit acknowledgement. The thesis has relied primarily on secondary sources — scholarly literature, industry reports, and published case analyses — supplemented by publicly available documentation of journalistic practice. The absence of primary empirical data derived from systematic interviews with Polish data journalism practitioners or quantitative content analysis of data journalism outputs represents a significant constraint on the precision of the empirical claims advanced, particularly in Chapter 2. The analysis is further limited by the uneven quality and coverage of the available Polish-language literature on data journalism, which is still developing relative to the Anglophone scholarship on which the theoretical framework of Chapter 1 is substantially grounded. The assessment of future prospects offered in Chapter 3, while grounded in the empirical evidence assembled in preceding chapters, necessarily involves elements of scenario construction that are not empirically derivable from historical data and that may be falsified by developments — political, technological, or economic — that are at present difficult to anticipate. These limitations do not invalidate the conclusions advanced, but they do circumscribe the generalisability of those conclusions and point toward a programme of empirical investigation that the present work has been unable to undertake.

Future research in this field would benefit from several directions of inquiry that the scope of the present thesis has precluded. A systematic comparative analysis of data journalism practices across Central and Eastern European media systems — encompassing the Czech Republic, Slovakia, Hungary, and Romania alongside Poland — would enable more precise identification of the factors distinguishing more and less developed contexts, and would permit the assessment of whether the Polish trajectory identified here is regionally typical or nationally distinctive. Primary research with Polish data journalism practitioners, conducted through semi-structured interviews and supplemented by ethnographic observation of newsroom data desk operations, would substantially deepen understanding of the organisational and cultural conditions that either enable or impede the institutionalisation of data-driven practices at the editorial level. Longitudinal content analysis of data journalism output across a defined sample of Polish news organisations, tracking both volume and methodological sophistication over time, would provide empirical grounding for assessments of developmental trajectory that the present study has been able to offer only in descriptive and scenario-based terms. Finally, the rapid integration of artificial intelligence tools into journalistic workflows — including automated data extraction, natural language processing of large document sets, and machine learning-assisted pattern detection — constitutes an emerging research domain of fundamental importance for the field, whose implications for both the practice and the ethics of data journalism in Poland and more broadly have barely begun to be systematically examined.

The central hypothesis animating the present thesis — that data journalism in Poland represents a growing and significant branch of journalistic practice capable of making substantial contributions to political transparency and the quality of public knowledge — has been confirmed by the evidence assembled, but in a more qualified and conditionally stated form than an optimistic reading of international developmental patterns might have anticipated. Data journalism in Poland is growing, but from a narrow base and in conditions that have thus far limited its diffusion beyond a small number of committed organisations and practitioners. It is significant, but its significance is concentrated in a metropolitan, digitally native, and substantially non-commercially funded segment of the Polish media landscape that does not represent the sector as a whole. It contributes to transparency and public knowledge, but in a political environment in which those contributions are contested, and in which the structural conditions necessary for independent data-driven accountability journalism to function — access to data, editorial independence, institutional resources, and a legally protected right to publish — cannot be assumed as stable givens. The development of data journalism in Poland, like the development of the field more broadly, is ultimately a political as much as a technological or educational project, and its future will be determined as much by the choices made in editorial boardrooms, ministerial offices, and university departments as by the capabilities of the tools available to its practitioners.

List of Tables

Table 1.1. Selected conceptualisations of data journalism in the scholarly literature
Table 1.2. Principal ethical domains in data journalism and their associated normative obligations
Table 2.1. Principal Institutional Actors in Polish Data Journalism: Organisational Type and Methodological Focus
Table 2.2. Technical Skill Profiles in Polish Data Journalism by Outlet Type
Table 3.1. Principal barrier categories impeding the diffusion of data journalism in Polish newsrooms
Table 3.2. Scenario matrix for the future development of data journalism in Poland

List of Tables

Table 1.1. Selected conceptualisations of data journalism in the scholarly literature
Table 1.2. Principal ethical domains in data journalism and their associated normative obligations
Table 2.1. Principal Institutional Actors in Polish Data Journalism: Organisational Type and Methodological Focus
Table 2.2. Technical Skill Profiles in Polish Data Journalism by Outlet Type
Table 3.1. Principal barrier categories impeding the diffusion of data journalism in Polish newsrooms
Table 3.2. Scenario matrix for the future development of data journalism in Poland