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Managing Data-Intensive Research Problem-Solving Lifecycle
| Author(s): | Skvortsov N. A., Stupnikov S. A. |
| Published: | Communications in Computer and Information Science: 22nd International Conference on Data Analytics and Management in Data Intensive Domains, DAMDID/RCDL 2020 (Virtual Online, 13-16 October 2020). – Springer Science and Business Media Deutschland GmbH, 2021. Vol. 1427. P. 3 – 18. |
| Abstract: | |
| Problem-solving lifecycle providing provable semantic interoperability and correct reuse of data, metadata, domain knowledge, methods, and processes on different levels of consideration is proposed. It includes ontological search, data model integration, schema mapping, entity resolution, method and process reuse, hypothesis testing, and data publishing. Problems are solved according to formal domain knowledge specifications over multiple integrated resources. The semantics of every decision may be formally verified. |
| Download: |
[ https://link.springer.com/chapter/10.1007/978-3-030-81200-3_9 ]
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