| dc.contributor.author | Zapilko, Benjamin | |
| dc.contributor.author | Schaible, Johann | |
| dc.contributor.author | Wandhöfer, Timo | |
| dc.contributor.author | Mutschke, Peter | |
| dc.date | 2016-06-01 | |
| dc.date.accessioned | 2018-01-08T09:23:09Z | |
| dc.date.available | 2018-01-08T09:23:09Z | |
| dc.date.issued | 2016 | |
| dc.identifier.issn | 1610-1987 | |
| dc.identifier.uri | http://dl.gi.de/handle/20.500.12116/11519 | |
| dc.description.abstract | In recent years, Linked Open Data (LOD) has matured and gained acceptance across various communities and domains. Large potential of Linked Data technologies is seen for an application in scientific disciplines. In this article, we present use cases and applications for an application of Linked Data in the social sciences. They focus on (a) interlinking domain-specific information, and (b) linking social science data to external LOD sources (e.g. authority data) from other domains. However, several technical and research challenges arise, when applying Linked Data technologies to a scientific domain with its specific data, information needs and use cases. We discuss these challenges and show how they can be addressed. | |
| dc.publisher | Springer | |
| dc.relation.ispartof | KI - Künstliche Intelligenz: Vol. 30, No. 2 | |
| dc.relation.ispartofseries | KI - Künstliche Intelligenz | |
| dc.title | Applying Linked Data Technologies in the Social Sciences | |
| dc.type | Text/Journal Article | |
| mci.reference.pages | 159-162 | |
| gi.identifier.doi | 10.1007/s13218-015-0416-6 | |
