Freedom versus standardization: Structured data generation in a peer production community

Andrew Hall, Sarah McRoberts, Jacob Thebault-Spieker, Yilun Lin, Shilad Sen, Brent Hecht, Loren G Terveen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Scopus citations


In addition to encyclopedia articles and software, peer production communities produce structured data, e.g., Wikidata and OpenStreetMap's metadata. Structured data from peer production communities has become increasingly important due to its use by computational applications, such as CartoCSS, MapBox, and Wikipedia infoboxes. However, this structured data is usable by applications only if it follows standards. We did an interview study focused on OpenStreetMap's knowledge production processes to investigate how - and how successfully - this community creates and applies its data standards. Our study revealed a fundamental tension between the need to produce structured data in a standardized way and OpenStreetMap's tradition of contributor freedom. We extracted six themes that manifested this tension and three overarching concepts, correctness, community, and code, which help make sense of and synthesize the themes. We also offered suggestions for improving OpenStreetMap's knowledge production processes, including new data models, sociotechnical tools, and community practices (e.g. stronger leadership).

Original languageEnglish (US)
Title of host publicationCHI 2017 - Proceedings of the 2017 ACM SIGCHI Conference on Human Factors in Computing Systems
Subtitle of host publicationExplore, Innovate, Inspire
PublisherAssociation for Computing Machinery
Number of pages11
ISBN (Electronic)9781450346559
StatePublished - May 2 2017
Event2017 ACM SIGCHI Conference on Human Factors in Computing Systems, CHI 2017 - Denver, United States
Duration: May 6 2017May 11 2017

Publication series

NameConference on Human Factors in Computing Systems - Proceedings


Other2017 ACM SIGCHI Conference on Human Factors in Computing Systems, CHI 2017
Country/TerritoryUnited States

Bibliographical note

Funding Information:
We would like to thank our interviewees for volunteering to participate in this study. We would also like to thank Morten Warncke-Wang for his feedback on our work. This work was funded in part by the U.S. National Science Foundation (NSF IIS-1552955; NSF IIS-1526988; NSF IIS-0964695; NSF IIS-1218826; NSF IIS-1111201) and the U.S. Department of Education (USDE GAANN-p200A100195).


  • OpenStreetMap
  • Peer-production communities
  • Standardization
  • Structured data


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