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PIsCO: A Performance indicators framework for collection of bioinformatics resource metrics

, , ,
1 Earlham Institute, Norwich, Norfolk, United Kingdom
2 ELIXIR-Hub, Wellcome Genome Campus, Cambridge, United Kingdom
3 Repositive, Cambridge, United Kingdom
DOI
10.7287/peerj.preprints.3112v1
Published
Accepted
Subject Areas
Bioinformatics, Computer Architecture, Software Engineering
Keywords
metrics, sharing, automatic collection, registries, key perfomance indicators
Copyright
© 2017 Artaza et al.
Licence
This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Preprints) and either DOI or URL of the article must be cited.
Cite this article
Artaza H, Hancock JM, Jimenez RC, Corpas M. 2017. PIsCO: A Performance indicators framework for collection of bioinformatics resource metrics. PeerJ Preprints 5:e3112v1

Abstract

We present PIsCO, a server-side JavaScript framework for the collection, registration and sharing of metrics that can be used to evaluate the impact of bioinformatics-related resources such as software, repositories, training or databases. The metrics framework can be used to capture standard definitions of metrics, facilitate the collection of data, monitor resources and share data to be reused by other teams, laboratories or academic institutions. In addition, PIsCO is able to collect those metrics and present them in a visual way to allow their easy interpretation.

Author Comment

This is a submission to PeerJ Computer Science for review.

Supplemental Information

Additional Information

Competing Interests

Manuel Corpas is an employee of Repositive, Cambridge, CB4 2HY, U.K.

Author Contributions

Haydee Artaza conceived and designed the experiments, performed the experiments, analyzed the data, contributed reagents/materials/analysis tools, wrote the paper, prepared figures and/or tables, performed the computation work, reviewed drafts of the paper.

John M. Hancock analyzed the data, contributed reagents/materials/analysis tools, wrote the paper, prepared figures and/or tables, reviewed drafts of the paper.

Rafael C. Jimenez conceived and designed the experiments, analyzed the data, contributed reagents/materials/analysis tools, wrote the paper, reviewed drafts of the paper.

Manuel Corpas analyzed the data, contributed reagents/materials/analysis tools, wrote the paper.

Data Deposition

The following information was supplied regarding data availability:

https://github.com/BioPisCO/

Funding

PIsCO was supported by the ELIXIR Implementation Study “Metrics discovery and implementation in life sciences”. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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PIsCO: A Performance indicators framework for collection of bioinformatics resource metrics
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