University of Illinois Urbana-Champaign

Explorations in provenance in the information sciences

Gryk, Michael Robert

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GRYK-DISSERTATION-2024.pdf

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https://hdl.handle.net/2142/127214

Description

Title
Explorations in provenance in the information sciences
Author(s)
Gryk, Michael Robert
Issue Date
2024-12-01
Director of Research (if dissertation) or Advisor (if thesis)
Bertram Ludaescher, Bertram
Doctoral Committee Chair(s)
Bertram Ludaescher, Bertram
Committee Member(s)
  • Bettivia, Rhiannon
  • Downie, J. Stephen
  • Twidale, Michael
Department of Study
Information Sciences
Discipline
Library & Information Science
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
Ph.D.
Degree Level
Dissertation
Keyword(s)
  • Provenance
  • FAIR Principles
  • Curation
  • Workflows
  • Information Modeling
Abstract
Provenance is important throughout Library and Information Science and is particularly important for the information infrastructures which support the computational aspects of the natural sciences. This is highlighted by the prominence of provenance as a plank in the FAIR principles for data stewardship (principle R1.2). While traditionally focused on the history/lineage of physical objects, provenance is now commonly accepted to apply to digital objects such as the results of computation as well as to the recipes for computing; in the case of recipes this prospective provenance is critical for reproducibility. This dissertation begins with background in provenance pertaining to data curation and computational reproducibility. The second part describes attempts to “FAIRify” the reporting and execution of workflows within a domain of natural science for better data stewardship to support data reusability. The next chapters argue that there remains a gap in our ability to fully document provenance as there are more story-telling tenses than just the past (retrospective) and future (prospective). There is also the subjunctive (conditional) and perhaps many others. Supporting new flavors of provenance requires new modeling constructs. The thesis concludes with novel information modeling techniques which exploit reification of sub-class relationships suitable for modeling these many sub-classes of provenance, as well as other domains.
Graduation Semester
2024-12
Type of Resource
Thesis
Handle URL
https://hdl.handle.net/2142/127214
Copyright and License Information
© 2024 Michael Robert Gryk

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