Opening Up Climate Research: A Linked Data Approach to Publishing Data Provenance
Traditionally, the formal scientific output in most fields of natural science has been limited to peer-reviewed academic journal publications, with less attention paid to the chain of intermediate data results and their associated metadata, including provenance. In effect, this has constrained the r...
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doaj-8e98a88eb90a400dad1c63500840ae4c2020-11-24T22:34:56ZengUniversity of EdinburghInternational Journal of Digital Curation1746-82562012-03-017116317310.2218/ijdc.v7i1.223206Opening Up Climate Research: A Linked Data Approach to Publishing Data ProvenanceArif ShaonSarah CallaghanBryan LawrenceBrian MatthewsTimothy OsbornColin HarphamAndrew WoolfTraditionally, the formal scientific output in most fields of natural science has been limited to peer-reviewed academic journal publications, with less attention paid to the chain of intermediate data results and their associated metadata, including provenance. In effect, this has constrained the representation and verification of the data provenance to the confines of the related publications. Detailed knowledge of a dataset’s provenance is essential to establish the pedigree of the data for its effective re-use, and to avoid redundant re-enactment of the experiment or computation involved. It is increasingly important for open-access data to determine their authenticity and quality, especially considering the growing volumes of datasets appearing in the public domain. To address these issues, we present an approach that combines the Digital Object Identifier (DOI) – a widely adopted citation technique – with existing, widely adopted climate science data standards to formally publish detailed provenance of a climate research dataset as an associated scientific workflow. This is integrated with linked-data compliant data re-use standards (e.g. OAI-ORE) to enable a seamless link between a publication and the complete trail of lineage of the corresponding dataset, including the dataset itself.http://www.ijdc.net/index.php/ijdc/article/view/213 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Arif Shaon Sarah Callaghan Bryan Lawrence Brian Matthews Timothy Osborn Colin Harpham Andrew Woolf |
spellingShingle |
Arif Shaon Sarah Callaghan Bryan Lawrence Brian Matthews Timothy Osborn Colin Harpham Andrew Woolf Opening Up Climate Research: A Linked Data Approach to Publishing Data Provenance International Journal of Digital Curation |
author_facet |
Arif Shaon Sarah Callaghan Bryan Lawrence Brian Matthews Timothy Osborn Colin Harpham Andrew Woolf |
author_sort |
Arif Shaon |
title |
Opening Up Climate Research: A Linked Data Approach to Publishing Data Provenance |
title_short |
Opening Up Climate Research: A Linked Data Approach to Publishing Data Provenance |
title_full |
Opening Up Climate Research: A Linked Data Approach to Publishing Data Provenance |
title_fullStr |
Opening Up Climate Research: A Linked Data Approach to Publishing Data Provenance |
title_full_unstemmed |
Opening Up Climate Research: A Linked Data Approach to Publishing Data Provenance |
title_sort |
opening up climate research: a linked data approach to publishing data provenance |
publisher |
University of Edinburgh |
series |
International Journal of Digital Curation |
issn |
1746-8256 |
publishDate |
2012-03-01 |
description |
Traditionally, the formal scientific output in most fields of natural science has been limited to peer-reviewed academic journal publications, with less attention paid to the chain of intermediate data results and their associated metadata, including provenance. In effect, this has constrained the representation and verification of the data provenance to the confines of the related publications. Detailed knowledge of a dataset’s provenance is essential to establish the pedigree of the data for its effective re-use, and to avoid redundant re-enactment of the experiment or computation involved. It is increasingly important for open-access data to determine their authenticity and quality, especially considering the growing volumes of datasets appearing in the public domain. To address these issues, we present an approach that combines the Digital Object Identifier (DOI) – a widely adopted citation technique – with existing, widely adopted climate science data standards to formally publish detailed provenance of a climate research dataset as an associated scientific workflow. This is integrated with linked-data compliant data re-use standards (e.g. OAI-ORE) to enable a seamless link between a publication and the complete trail of lineage of the corresponding dataset, including the dataset itself. |
url |
http://www.ijdc.net/index.php/ijdc/article/view/213 |
work_keys_str_mv |
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