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Chapitre D'ouvrage Année : 2022

Using Provenance in Data Analytics for Seismology: Challenges and Directions

Résumé

We analyze data and meta-data modeling challenges to provide curated collections that can be easy to explore. Data exploration can use provenance tools to give insight into the conditions in which data are collected. We are concerned with data curation and exploration in seismic geophysics. We believe that the tasks involved in graph exploration depend highly on the knowledge domain. The discussion about possible solutions is driven by the hypothesis that graphs can be well-adapted data models to represent, explore and analyze seismic data. Given that data curation is done by human agents, it is essential to provide automatic tools to add provenance to seismic data.
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Dates et versions

hal-03776553 , version 1 (06-06-2023)

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Umberto Souza da Costa, Javier Alfonso Espinosa-Oviedo, Martin Musicante, Genoveva Vargas-Solar, José-Luis Zechinelli-Martini. Using Provenance in Data Analytics for Seismology: Challenges and Directions. Silvia Chiusano; Robert Wrembel; Kjetil Nørvåg; Barbara Catania; Genoveva Vargas-Solar; Tania Cerquitelli; Ester Zumpano. New Trends in Database and Information Systems. ADBIS 2022 Short Papers, Doctoral Consortium and Workshops: DOING, K-GALS, MADEISD, MegaData, SWODCH, Turin, Italy, September 5–8, 2022, Proceedings, 1652, Springer International Publishing, pp.311-322, 2022, Communications in Computer and Information Science, 978-3-031-15742-4. ⟨10.1007/978-3-031-15743-1_29⟩. ⟨hal-03776553⟩
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