Open Data Platforms for a Data Commons, How to Support the Life of Data Beyond Release
Bibliographic Data
| ID | 22008880 |
|---|---|
| Authors | Hannah Hamilton (0009-0007-7864-0437, University of Stirling), Stefano De Paoli (0000-0003-1120-4773, Abertay University), Anna Wilson (0000-0002-5563-2318), A N Wilson (0000-0001-6928-1689, University of Stirling), Greg Singh (0000-0001-8044-3968, University of Stirling) |
| Year | 2020 |
| Publication date | 2020-10-05 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | AoIR Selected Papers of Internet Research (JOURNAL) |
| Journal identifiers | ISSN: 2162-3317 • E-ISSN: 2162-3317 |
| Publisher | University of Illinois Libraries (PUBLISHER) |
| DOI | 10.5210/spir.v2020i0.11226 |
| OpenAlex | W3091955845 |
| Language | EN |
| References cited | 6 |
In this paper we will discuss the challenges and opportunities of infusing in open data a life beyond its original public release. Indeed, it is often unclear whether open data has a life beyond the one it was initially collected for, to the extent that some authors have even described the public reuse of government data as no more than a “myth”. We will present the results of the project Data Commons Scotland launched with the idea of creating an Internet based prototype platform for creating a trustworthy common of open data, thus facilitating a life for data beyond the one of the original producer. We will discuss the results of our empirical research for the project based on 31 qualitative interviews with a number of actors, such as data producers or citizens. Moreover, we will present the results of the co-design conducted for the design of the Data Commons Scotland platform. With the results of our analysis we will reflect on the challenges of building Internet based platforms for open data supporting the generation of a common
Commons · Data science · Open data · Open government · Political science · Qualitative property · Reuse · The Internet · World Wide Web · Computer Science · Data Analysis and Archiving · Data Quality and Management · Engineering · Privacy-Preserving Technologies in Data
| Highly cited | No |
|---|