Abstract
A pervasive problem in Data Science is that the knowledge generated by possibly expensive analytics processes is subject to decay over time as the data and algorithms used to compute it change, and the external knowledge embodied by reference datasets evolves. Deciding when such knowledge outcomes should be refreshed, following a sequence of data change events, requires problem-specific functions to quantify their value and its decay over time, as well as models for estimating the cost of their re-computation. Challenging is the ambition to develop a decision support system for informing re-computation decisions over time that is both generic and customisable.With the help of a case study from genomics, in this paper we offer an initial formalisation of this problem, highlight research challenges, and outline a possible approach based on the analysis of metadata from a history of past computations.
Original language | English |
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Title of host publication | Data Analytics - 31st British International Conference on Databases, BICOD 2017, Proceedings |
Editors | Andrea Calì, Peter Wood, Nigel Martin, Alexandra Poulovassilis |
Publisher | Springer Verlag |
Pages | 65-77 |
Number of pages | 13 |
ISBN (Print) | 9783319607948 |
DOIs | |
Publication status | Published - 2017 |
Event | 31st British International Conference on Databases, BICOD 2017 - London, United Kingdom Duration: 10 Jul 2017 → 12 Jul 2017 |
Publication series
Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
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Volume | 10365 LNCS |
ISSN (Print) | 0302-9743 |
ISSN (Electronic) | 1611-3349 |
Conference
Conference | 31st British International Conference on Databases, BICOD 2017 |
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Country/Territory | United Kingdom |
City | London |
Period | 10/07/17 → 12/07/17 |
Bibliographical note
Publisher Copyright:© Springer International Publishing AG 2017.
Keywords
- Incremental computation
- Metadata management
- Partial re-computation
- Provenance
- Selective re-computation
ASJC Scopus subject areas
- Theoretical Computer Science
- General Computer Science