Social networks in spatial data infrastructures

• Published in: GeoJournal Vol. 75; no. 1; pp. 105 - 118
• Main Authors: van Oort, P. A. J., Hazeu, G. W., Kramer, H., Bregt, A. K., Rip, F. I.
• Format: Journal Article
• Language: English
• Published: Dordrecht Springer 01-02-2010; Springer Netherlands; Springer Nature B.V
• Subjects: Alterra - Centrum Geo-informatie; Centre Geo-information; CGI - Aardobservatie; CGI - Earth Observation; CGI - Geo-informatie Communicatie; CGI - Geo-information Communication; Community associations; Crop and Weed Ecology; Data analysis; Datasets; Environmental Management; Feedback; Geography; Human Geography; Hyperlinks; Information and communication technologies; Information sharing; Infrastructure; Internet; Laboratorium voor Geo-informatiekunde en remote sensing; Laboratory of Geo-information Science and Remote Sensing; Leerstoelgroep Gewas- en onkruidecologie; Metadata; New technology; Online social networking; PE&RC; Producers; Social network analysis; Social networking; Social networks; Social research; Social Sciences; Spatial data; Studies; User names; Social networks; User; Spatial data infrastructure; Producer
• ISSN: 0343-2521; 1572-9893
• DOI: 10.1007/s10708-009-9294-5

Data sharing over the internet is increasingly efficient and increasingly anonymous. This growing anonymity makes it difficult for data users to exchange feedback: interesting ideas, innovations, ancillary data, concerns about data quality, etcetera. For data producers not knowing the end-users makes it more difficult to collect end-user feedback and tailor the production process to users needs. Feedback can be exchanged through social networks, in other words contacts with other users. Very little is known about such social networks in the case of data sharing. In this paper we present an analysis of the social networks associated with two land cover datasets. We found that most users have zero to two links to other users and virtually no links to users in other organisations. Without these links, it seems almost impossible to identify users of a particular dataset. Internet technology can help but is currently not used to enhance exchange of feedback within the user community.