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Meaningful Data Interoperability and Reuse among Heterogeneous Scientific Communities
| Author(s): | Skvortsov N. |
| Published: | Selected Papers of the XX International Conference on Data Analytics and Management in Data Intensive Domains (DAMDID/RCDL 2018). CEUR Workshop Proceedings, Vol. 2277. P.14-15. 2018. |
| Abstract: | |
| FAIR data principles declare data interoperability and reuse through the use of machine and
human readable specifications. Adherence to these principles has some subsequences for data infrastructures
and research communities. Meaningful data exchange and reuse by humans and machines requires formal
specifications of subject domains accompanying data and allowing automatic inference. Development of
formal conceptual specifications in research communities might be stimulated by a necessity to reach
semantic interoperability of data collections and component, reuse of data resources. Data lifecycle hence
includes collecting domain knowledge specifications, classifying all data, methods and services by these
specifications, collecting and sharing them for reuse. Formal inference allows meaningful search and verified
reuse of data, methods and services from collections. |
| Download: |
[ http://ceur-ws.org/Vol-2277/paper05.pdf ]
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