Item type:Conference Paper,

ReStoRunT: Simple Recording, Storing, Running and Tracing changes in Spreadsheets

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Gesellschaft für Informatik e.V.

Abstract

In addition to the ubiquitous big data, one key challenge indata processing and management in the life sciences is the diversity ofsmall data. Diverse pieces of small data have to be transformed intostandards-compliant data. Here, the challenge lies not in the difficulty ofsingle steps that need to be performed, but rather in the fact that manytransformation tasks are to be performed once or only a few times. Thislimits the time that can be put into automated approaches, which inturn severely limits the verifiability of such transformations.As much of the data to be processed is stored in spreadsheets, withinthis paper we justify and propose a lightweight recording-based solutionthat works on a wide variety of spreadsheet programs, from MicrosoftExcel to Google Docs.

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Wolfgang, Müller; Mertová, Lukrécia (2023): ReStoRunT: Simple Recording, Storing, Running and Tracing changes in Spreadsheets. BTW 2023. DOI: 10.18420/BTW2023-57. Bonn: Gesellschaft für Informatik e.V.. ISBN: 978-3-88579-725-8. pp. 865-877. Dresden, Germany. 06.-10. März 2023

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Provenance, Harmonisation, Spreadsheets

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Number of citations to item: 1

  • Sergio Alejandro Gómez, Pablo Rubén Fillottrani (2024): Analyzing Induced Functional Dependencies from Spreadsheets in the GF Framework for Ontology-Based Data Access, In: Communications in Computer and Information Science, doi:10.1007/978-3-031-62245-8_20
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