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Authors: Theodora Galani 1 ; Yannis Stavrakas 2 ; George Papastefanatos 2 and Yannis Vassiliou 1

Affiliations: 1 School of Electrical and Computer Engineering, NTUA, Iroon Polytechniou 9, Athens, Greece ; 2 RC ATHENA, Artemidos 6 & Epidavrou, Marousi, Greece

Keyword(s): Querying Data Evolution, Change Modelling, XPath.

Abstract: Evo-graph is a model for data evolution that captures data versions and treats changes as first-class citizens. A change in evo-graph can be compound, comprising disparate changes, and is associated with the data items it affects. In previous work, we specified how an evo-graph can be reduced to a snapshot holding under a specific time instance, we presented an XML representation of evo-graph called evoXML, we defined how evo-graph is constructed as the current snapshot evolves, as well as presented and evaluated the C2D framework that implements these concepts using XML technologies. In this paper, we formally define evo-path, an XPath extension for querying the data history and change structure in a uniform way over evo-graph. We specify the evo-path syntax, semantics and implementation, and present several query categories.

CC BY-NC-ND 4.0

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Paper citation in several formats:
Galani, T.; Stavrakas, Y.; Papastefanatos, G. and Vassiliou, Y. (2021). Evo-Path: Querying Data Evolution through Complex Changes. In Proceedings of the 10th International Conference on Data Science, Technology and Applications - DATA; ISBN 978-989-758-521-0; ISSN 2184-285X, SciTePress, pages 353-361. DOI: 10.5220/0010615703530361

@conference{data21,
author={Theodora Galani. and Yannis Stavrakas. and George Papastefanatos. and Yannis Vassiliou.},
title={Evo-Path: Querying Data Evolution through Complex Changes},
booktitle={Proceedings of the 10th International Conference on Data Science, Technology and Applications - DATA},
year={2021},
pages={353-361},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010615703530361},
isbn={978-989-758-521-0},
issn={2184-285X},
}

TY - CONF

JO - Proceedings of the 10th International Conference on Data Science, Technology and Applications - DATA
TI - Evo-Path: Querying Data Evolution through Complex Changes
SN - 978-989-758-521-0
IS - 2184-285X
AU - Galani, T.
AU - Stavrakas, Y.
AU - Papastefanatos, G.
AU - Vassiliou, Y.
PY - 2021
SP - 353
EP - 361
DO - 10.5220/0010615703530361
PB - SciTePress