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Public records requests are a central mechanism for government transparency. In practice, they are slow, complex processes that require analyzing large amounts of messy, unstructured data. In this paper, we introduce RequestAtlas, a system that helps investigative journalists review large quantities of unstructured data that result from submitting many public records requests. RequestAtlas was developed through a year-long participatory design collaboration with the California Reporting Project (CRP), a journalistic collective researching police use of force and police misconduct in California. RequestAtlas helps journalists evaluate the results of public records requests for completeness and negotiate with agencies for additional information. RequestAtlas has had significant real-world impact. It has been deployed for more than a year to identify missing data in response to public records requests and to facilitate negotiation with public records request officers. Through the process of designing and observing the use of RequestAtlas, we explore the technical challenges associated with the public records request process and the design needs of investigative journalists more generally. We argue that public records requests represent an instance of an adversarialtechnical relationshipin which two entities engage in a prolonged, iterative, often adversarial exchange of information. Technologists can support information-gathering efforts within these adversarial technical relationships by building flexible local solutions that help both entities account for the state of the ongoing information exchange. Additionally, we offer insights on ways to design applications that can assist investigative journalists in the inevitably significant data cleaning phase of processing large documents while supporting journalistic norms of verification and human review. Finally, we reflect on the ways that this participatory design process, despite its success, lays bare some of the limitations inherent in the public records request process and in the ''request and respond'' model of transparency more generally.
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This content will become publicly available on March 12, 2026
Boundaries of data journalism in U.S. public radio newsrooms
The recent addition of data journalists to several dozen U.S. public radio newsrooms has created multiple new hybridities in the form. No longer are numbers and large datasets “audio poison.” Instead, they are an essential tool for these journalists, who prize journalism’s interpretive function, expressing information in new ways and challenging conventions of broadcast newsroom employment. This study, which relies on semi-structured interviews with 13 public radio data journalists, uses Carlson’s boundary work typology to analyze the ways in which data journalists are expanding the boundaries of U.S. public radio journalism, as well as ways in which they have pushed back against expulsionary pressures. This study’s findings problematize the idea that the results of boundary work must be expressed as in-or-out proposition. Rather, U.S. public radio data journalists suggest their boundaries are a continuum where they may be conditionally accepted by their colleagues, depending on deadlines and on the skills possessed by non-data journalists.
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- Award ID(s):
- 2129047
- PAR ID:
- 10594471
- Publisher / Repository:
- Sage
- Date Published:
- Journal Name:
- Journalism
- ISSN:
- 1464-8849
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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