TY - GEN
T1 - Is my:sameAs the same as your:sameAs? Lenticular lenses for context-specific identity
AU - Idrissou, Al Koudous
AU - Hoekstra, Rinke
AU - Van Harmelen, Frank
AU - Khalili, Ali
AU - Van Den Besselaar, Peter
N1 - Publisher Copyright:
© 2017 Copyright held by the owner/author(s).
PY - 2017/12/4
Y1 - 2017/12/4
N2 - Linking between entities in different datasets is a crucial element of the Semantic Web architecture, since those links allow us to integrate datasets without having to agree on a uniform vocabulary. However, it is widely acknowledged that the owl:sameAs construct is too blunt a tool for this purpose. It entails full equality between two resources independent of context. But whether or not two resources should be considered equal depends not only on their intrinsic properties, but also on the purpose or task for which the resources are used. We present a system for constructing contextspecific equality links. In a first step, our system generates a set of probable links between two given datasets. These potential links are decorated with rich metadata describing how, why, when and by whom they were generated. In a second step, a user then selects the links which are suited for the current task and context, constructing a context-specific "Lenticular Lens". Such lenses can be combined using operators such as union, intersection, difference and composition. We illustrate and validate our approach with a realistic application that supports researchers in social science.
AB - Linking between entities in different datasets is a crucial element of the Semantic Web architecture, since those links allow us to integrate datasets without having to agree on a uniform vocabulary. However, it is widely acknowledged that the owl:sameAs construct is too blunt a tool for this purpose. It entails full equality between two resources independent of context. But whether or not two resources should be considered equal depends not only on their intrinsic properties, but also on the purpose or task for which the resources are used. We present a system for constructing contextspecific equality links. In a first step, our system generates a set of probable links between two given datasets. These potential links are decorated with rich metadata describing how, why, when and by whom they were generated. In a second step, a user then selects the links which are suited for the current task and context, constructing a context-specific "Lenticular Lens". Such lenses can be combined using operators such as union, intersection, difference and composition. We illustrate and validate our approach with a realistic application that supports researchers in social science.
KW - Data integration
KW - Lens
KW - Linkset
KW - Owl:sameAs
UR - http://www.scopus.com/inward/record.url?scp=85040593681&partnerID=8YFLogxK
U2 - 10.1145/3148011.3148029
DO - 10.1145/3148011.3148029
M3 - Contribución a la conferencia
AN - SCOPUS:85040593681
T3 - Proceedings of the Knowledge Capture Conference, K-CAP 2017
BT - Proceedings of the Knowledge Capture Conference, K-CAP 2017
PB - Association for Computing Machinery, Inc
T2 - 9th International Conference on Knowledge Capture, K-CAP 2017
Y2 - 4 December 2017 through 6 December 2017
ER -