Data Provenance
| Authors |
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| Publication date | 2020 |
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| Book title | Towards Interoperable Research Infrastructures for Environmental and Earth Sciences |
| Book subtitle | A Reference Model Guided Approach for Common Challenges |
| ISBN |
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| ISBN (electronic) |
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| Series | Lecture Notes in Computer Science |
| Pages (from-to) | 208-225 |
| Publisher | Cham: Springer |
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| Abstract |
The provenance of research data is of critical importance to the reproduci-bility of and trust in scientific results. As research infrastructures provide more amalgamated datasets for researchers and more integrated facilities for processing and publishing data, the capture of provenance in a standard, machine-actionable form becomes especially important. Significant pro-gress has already been made in providing standards and tools for prove-nance tracking, but the integration of these technologies into research infra-structure remains limited in many scientific domains. Further development and collaboration are required to provide frameworks for provenance capture that can be adopted by as widely as possible, facilitating interoperability as well as dataset reuse. In this chapter, we examine the current state of the art for provenance, and the current state of provenance capture in environmental and earth science research infrastructures in Europe, as surveyed in the course of the ENVRIplus project. We describe a service developed for the upload, dissemination and application of provenance templates that can be used to generate standardised provenance traces from input data in accordance with current best practice and standards. The use of such a service by research infrastructure architects and researchers can expedite both the understanding and use of provenance technologies, and so drive the standard use of provenance capture technologies in future research infra-structure developments.
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| Document type | Chapter |
| Language | English |
| Published at | https://doi.org/10.1007/978-3-030-52829-4_12 |
| Downloads |
Magagna2020_Chapter_DataProvenance
(Final published version)
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