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The Principles of Data Reuse in Research Infrastructures
| Author(s): | Nikolay Skvortsov |
| Published: | Proceedings of the International Conference "Common Digital Space of Scientific Knowledge: Problems & Solutions" (CDSSK 2020), Moscow, Russia, November 10–12, 2020. CEUR Workshop Proceedings, Vol. 2990, pp. 62-74, 2021. |
| Abstract: | |
| The principles known by FAIR abbreviation have been applied for different kinds of data management technologies to support data reuse. In particular,
they are important for investigations and development in research infrastructures
but applied in significantly different ways. These principles are recognized as
prospective since, according to them, data in the context of reuse should be readable and actionable by both humans and machines. The review of solutions for
data interoperability and reuse in research infrastructures is presented in the paper. It is shown that conceptual modeling based on formal domain specifications
still has good potential for data reuse in research infrastructures. It allows to relate
data, methods, and other resources semantically, classify and identify them in the
domain, integrate and verify the correctness of data reuse. Infrastructures based
on formal domain modeling can make heterogeneous data management and research significantly more effective and automated. |
| Download: |
[ http://ceur-ws.org/Vol-2990/rpaper6.pdf ]
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