A Templating System to Generate Provenance
- Submitting institution
-
King's College London
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 84888598
- Type
- D - Journal article
- DOI
-
10.1109/TSE.2017.2659745
- Title of journal
- IEEE TRANSACTIONS ON SOFTWARE ENGINEERING
- Article number
- -
- First page
- 103
- Volume
- 44
- Issue
- 2
- ISSN
- 0098-5589
- Open access status
- Compliant
- Month of publication
- April
- Year of publication
- 2017
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
4
- Research group(s)
-
-
- Citation count
- 9
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- The standard PROV for provenance is seen as “providing the foundations to generate explanations for an AI decision” (see ICO guidance). To lower the PROV adoption threshold, the PROV-template approach enables developers to specify the structure of provenance declaratively, and to instantiate it by runtime logging. The paper formalises an algorithm, quantitatively evaluates its space and time performance in real-life applications, and qualitatively explains the benefits for developers. PROV-template is released in open source (ProvToolbox: 3000+ downloads), hosted as a service (openprovenance.org/services), used by projects UML2PROV (Rioja), DARE (Edinburgh), Impact (Spawar), and implemented independently by the Environment Agency Austria.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
