3 Search Results for "Howison, James"

Document
Resource Paper
DOI: 10.4230/TGDK.2.2.4
FAIR Jupyter: A Knowledge Graph Approach to Semantic Sharing and Granular Exploration of a Computational Notebook Reproducibility Dataset

Authors: Sheeba Samuel and Daniel Mietchen

Published in: TGDK, Volume 2, Issue 2 (2024): Special Issue on Resources for Graph Data and Knowledge. Transactions on Graph Data and Knowledge, Volume 2, Issue 2

Abstract
The way in which data are shared can affect their utility and reusability. Here, we demonstrate how data that we had previously shared in bulk can be mobilized further through a knowledge graph that allows for much more granular exploration and interrogation. The original dataset is about the computational reproducibility of GitHub-hosted Jupyter notebooks associated with biomedical publications. It contains rich metadata about the publications, associated GitHub repositories and Jupyter notebooks, and the notebooks' reproducibility. We took this dataset, converted it into semantic triples and loaded these into a triple store to create a knowledge graph - FAIR Jupyter - that we made accessible via a web service. This enables granular data exploration and analysis through queries that can be tailored to specific use cases. Such queries may provide details about any of the variables from the original dataset, highlight relationships between them or combine some of the graph’s content with materials from corresponding external resources. We provide a collection of example queries addressing a range of use cases in research and education. We also outline how sets of such queries can be used to profile specific content types, either individually or by class. We conclude by discussing how such a semantically enhanced sharing of complex datasets can both enhance their FAIRness - i.e., their findability, accessibility, interoperability, and reusability - and help identify and communicate best practices, particularly with regards to data quality, standardization, automation and reproducibility.
Cite as

Sheeba Samuel and Daniel Mietchen. FAIR Jupyter: A Knowledge Graph Approach to Semantic Sharing and Granular Exploration of a Computational Notebook Reproducibility Dataset. In Special Issue on Resources for Graph Data and Knowledge. Transactions on Graph Data and Knowledge (TGDK), Volume 2, Issue 2, pp. 4:1-4:24, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@Article{samuel_et_al:TGDK.2.2.4,
  author =	{Samuel, Sheeba and Mietchen, Daniel},
  title =	{{FAIR Jupyter: A Knowledge Graph Approach to Semantic Sharing and Granular Exploration of a Computational Notebook Reproducibility Dataset}},
  journal =	{Transactions on Graph Data and Knowledge},
  pages =	{4:1--4:24},
  ISSN =	{2942-7517},
  year =	{2024},
  volume =	{2},
  number =	{2},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/TGDK.2.2.4},
  URN =		{urn:nbn:de:0030-drops-225886},
  doi =		{10.4230/TGDK.2.2.4},
  annote =	{Keywords: Knowledge Graph, Computational reproducibility, Jupyter notebooks, FAIR data, PubMed Central, GitHub, Python, SPARQL}
}
Document
DOI: 10.4230/DagMan.6.1.1
Engineering Academic Software (Dagstuhl Perspectives Workshop 16252)

Authors: Alice Allen, Cecilia Aragon, Christoph Becker, Jeffrey Carver, Andrei Chis, Benoit Combemale, Mike Croucher, Kevin Crowston, Daniel Garijo, Ashish Gehani, Carole Goble, Robert Haines, Robert Hirschfeld, James Howison, Kathryn Huff, Caroline Jay, Daniel S. Katz, Claude Kirchner, Katie Kuksenok, Ralf Lämmel, Oscar Nierstrasz, Matt Turk, Rob van Nieuwpoort, Matthew Vaughn, and Jurgen J. Vinju

Published in: Dagstuhl Manifestos, Volume 6, Issue 1 (2017)

Abstract
Software is often a critical component of scientific research. It can be a component of the academic research methods used to produce research results, or it may itself be an academic research result. Software, however, has rarely been considered to be a citable artifact in its own right. With the advent of open-source software, artifact evaluation committees of conferences, and journals that include source code and running systems as part of the published artifacts, we foresee that software will increasingly be recognized as part of the academic process. The quality and sustainability of this software must be accounted for, both a prioro and a posteriori. The Dagstuhl Perspectives Workshop on "Engineering Academic Software" has examined the strengths, weaknesses, risks, and opportunities of academic software engineering. A key outcome of the workshop is this Dagstuhl Manifesto, serving as a roadmap towards future professional software engineering for software-based research instruments and other software produced and used in an academic context. The manifesto is expressed in terms of a series of actionable "pledges" that users and developers of academic research software can take as concrete steps towards improving the environment in which that software is produced.
Cite as

Alice Allen, Cecilia Aragon, Christoph Becker, Jeffrey Carver, Andrei Chis, Benoit Combemale, Mike Croucher, Kevin Crowston, Daniel Garijo, Ashish Gehani, Carole Goble, Robert Haines, Robert Hirschfeld, James Howison, Kathryn Huff, Caroline Jay, Daniel S. Katz, Claude Kirchner, Katie Kuksenok, Ralf Lämmel, Oscar Nierstrasz, Matt Turk, Rob van Nieuwpoort, Matthew Vaughn, and Jurgen J. Vinju. Engineering Academic Software (Dagstuhl Perspectives Workshop 16252). In Dagstuhl Manifestos, Volume 6, Issue 1, pp. 1-20, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2017)

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@Article{allen_et_al:DagMan.6.1.1,
  author =	{Allen, Alice and Aragon, Cecilia and Becker, Christoph and Carver, Jeffrey and Chis, Andrei and Combemale, Benoit and Croucher, Mike and Crowston, Kevin and Garijo, Daniel and Gehani, Ashish and Goble, Carole and Haines, Robert and Hirschfeld, Robert and Howison, James and Huff, Kathryn and Jay, Caroline and Katz, Daniel S. and Kirchner, Claude and Kuksenok, Katie and L\"{a}mmel, Ralf and Nierstrasz, Oscar and Turk, Matt and van Nieuwpoort, Rob and Vaughn, Matthew and Vinju, Jurgen J.},
  title =	{{Engineering Academic Software (Dagstuhl Perspectives Workshop 16252)}},
  pages =	{1--20},
  journal =	{Dagstuhl Manifestos},
  ISSN =	{2193-2433},
  year =	{2017},
  volume =	{6},
  number =	{1},
  editor =	{Allen, Alice and Aragon, Cecilia and Becker, Christoph and Carver, Jeffrey and Chis, Andrei and Combemale, Benoit and Croucher, Mike and Crowston, Kevin and Garijo, Daniel and Gehani, Ashish and Goble, Carole and Haines, Robert and Hirschfeld, Robert and Howison, James and Huff, Kathryn and Jay, Caroline and Katz, Daniel S. and Kirchner, Claude and Kuksenok, Katie and L\"{a}mmel, Ralf and Nierstrasz, Oscar and Turk, Matt and van Nieuwpoort, Rob and Vaughn, Matthew and Vinju, Jurgen J.},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagMan.6.1.1},
  URN =		{urn:nbn:de:0030-drops-71468},
  doi =		{10.4230/DagMan.6.1.1},
  annote =	{Keywords: Academic software, Research software, Software citation, Software sustainability}
}
Document
DOI: 10.4230/DagRep.6.6.62
Engineering Academic Software (Dagstuhl Perspectives Workshop 16252)

Authors: Carole Goble, James Howison, Claude Kirchner, Oscar Nierstrasz, and Jurgen J. Vinju

Published in: Dagstuhl Reports, Volume 6, Issue 6 (2016)

Abstract
This report documents the program and the outcomes of Dagstuhl Perspectives Workshop 16252 "Engineering Academic Software".
Cite as

Carole Goble, James Howison, Claude Kirchner, Oscar Nierstrasz, and Jurgen J. Vinju. Engineering Academic Software (Dagstuhl Perspectives Workshop 16252). In Dagstuhl Reports, Volume 6, Issue 6, pp. 62-87, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2016)

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@Article{goble_et_al:DagRep.6.6.62,
  author =	{Goble, Carole and Howison, James and Kirchner, Claude and Nierstrasz, Oscar and Vinju, Jurgen J.},
  title =	{{Engineering Academic Software (Dagstuhl Perspectives Workshop 16252)}},
  pages =	{62--87},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2016},
  volume =	{6},
  number =	{6},
  editor =	{Goble, Carole and Howison, James and Kirchner, Claude and Nierstrasz, Oscar and Vinju, Jurgen J.},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagRep.6.6.62},
  URN =		{urn:nbn:de:0030-drops-67557},
  doi =		{10.4230/DagRep.6.6.62},
  annote =	{Keywords: Scientific Software, Data Science, Software Engineering}
}
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