This book explores provenance, the study and documentation of how things come to be. Traditionally defined as the origins, source, or ownership of an artifact, provenance today is not limited to historical domains. It can be used to describe what did happen (retrospective provenance), what could happen (subjunctive provenance), or what will happen (prospective provenance). Provenance information is ubiquitous and abundant; for example, a wine label that details the winery, type of grape, and country of origin tells a provenance story that determines the value of the bottle. This book presents select standards used in organizing provenance information and provides concrete examples on how to implement them. Provenance transcends disciplines, and this book is intended for anyone who is interested in documenting workflows and recipes. The goal is to empower readers to frame and answer provenance questions for their own work. Provenance is increasingly important in computational workflows and e-sciences and addresses the need for a practical introduction to provenance documentation with simple-to-use multi-disciplinary examples and activities. Case studies and examples address the creation of basic records using a variety of provenance metadata models, and the differences between PROV, ProvONE, and PREMIS are discussed. Readers will gain an understanding of the uses of provenance metadata in different domains and sectors in order to make informed decisions on their use. Documenting provenance can be a daunting challenge, and with clear examples and explanations, the task will be less intimidating to explore provenance needs.
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1 At the Intersection of Provenance and Metadata |
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2.4.1 Making Wine, Making Provenance: The Basic PROV Model |
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2.4.3 Composite Entities or Collections |
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2.4.4 PROV-Notation Revisited |
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3.4 Alternate and Specialization |
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3.6 Provenance of Provenance |
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3.7 Prospective Versus Retrospective |
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4.3 ProvONE Related Models |
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4.4 Prospective and Retrospective Provenance |
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4.5.2 Trace: Retrospective Provenance |
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4.5.3 Workflow: Prospective Provenance |
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5.3 PREMIS: A Brief History |
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5.4.1 PREMIS Semantic Units |
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5.4.3 Mini-Exercise: Objects |
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5.4.6 Mini-Exercise: Event and Agent |
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5.4.8 Mini-Exercise: Rights |
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6.2 PREMIS in a Complicated Digital World |
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6.3 Software Environments in PREMIS |
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7 Workflow Provenance with PREMIS |
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7.3 Nuclear Magnetic Resonance Spectroscopy |
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7.3.1 Spectral Reconstruction |
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7.4.1 CONNJUR Workflow Builder |
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8 More Provenance, More Problems |
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8.1 Provenance, Then and Now |
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8.4.2 Circularity, On Purpose and In Practice |
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8.4.3 Cross the Walk with Caution |
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8.5 Conclusion and a Call for Action |
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113 | |
Dr. Rhiannon Bettivia, Ph.D., is an Assistant Professor of Library and Information Science at Simmons University. She teaches in the areas of digital stewardship, media preservation, and metadata. Dr. Bettivias research blends information science with media, heritage, and cultural studies. She examines how political and governance concerns are built into technological infrastructures with a focus on digital cultural heritage, video games, semantic web platforms, and e-learning. Her current research interests include digital preservation of AV media; heritage metadata projects; feminist metadata analysis; digital provenance workflows; and digital education pedagogy. Dr. Bettivia received her Ph.D. in Information Science from the School of Information Sciences at the University of Illinois, Urbana-Champaign. Her grant work includes projects on video game preservation and digital forensics education. Her work has been published in the International Journal of Digital Curation, Digital Humanities Quarterly, the Journal of Qualitative Inquiry, and the Journal of Education for Library and Information Science.
Dr. Yi-Yun (Jessica) Cheng received her Ph.D. in Information Science from the School of Information Sciences, University of Illinois at Urbana-Champaign. Jessicas research lies at the intersections of metadata, knowledge organization, data curation, and biodiversity informatics. Jessicas work explores the use of a logic-based approach that draws on theories in first-order predicate logic and qualitative reasoning to align taxonomies. She works with systematists at the University of Illinois and Arizona State University to study how disagreements in biological taxonomies can have an impact on biodiversity informatics and how the reconciled taxonomies may lead to better biodiversity data integration. She will begin a faculty position at the School of Communication and Information at Rutgers, the State University of New Jersey in Fall 2022.
Michael R. Gryk, Ph.D., is an Associate Professor of Molecular Biology and Biophysics at UCONN Health, the Medical School of the University of Connecticut. At UCONN Health, he leads a technical research and discovery component of the NMRbox BTRR Center with the mission to foster the computational reproducibility and scientific data reuse of bioNMR data. Dr. Gryk is also the Associate Director of BioMagResBank, the international repository for bioNMR research data. He received his Ph.D. in Biophysics from Stanford University under the guidance of Dr. Oleg Jardetzky and worked as Postdoctoral Researcher at the European Molecular Biology Laboratory in Heidelberg, Germany. He has authored dozens of papers on the use of biomolecular NMR spectroscopy to investigate protein biochemistry including drug interactions and interactions with DNA. He is currently pursuing a second Ph.D. at the School of Information Sciences at the University ofIllinois, Urbana-Champaign, where his broad research interests include provenance, workflows, digital curation and preservation, reproducibility, and scientific data reuse.
