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An integration-oriented ontology to govern evolution in big data ecosystems

Author
Nadal, S.; Romero, O.; Abello, A.; Vassiliadis , P.; Vansummeren, S.
Type of activity
Journal article
Journal
Information systems
Date of publication
2019-01
Volume
79
First page
3
Last page
19
DOI
https://doi.org/10.1016/j.is.2018.01.006 Open in new window
Project funding
(GENESIS) Generation and Evolution of Smart APIs
SUpporting evolution and adaptation of PERsonalized Software by Exploiting contextual Data and End-user feedback
Repository
http://arxiv.org/abs/1801.05161 Open in new window
http://hdl.handle.net/2117/117075 Open in new window
URL
https://www.sciencedirect.com/science/article/pii/S0306437917304660 Open in new window
Abstract
Big Data architectures allow to flexibly store and process heterogeneous data, from multiple sources, in their original format. The structure of those data, commonly supplied by means of REST APIs, is continuously evolving. Thus data analysts need to adapt their analytical processes after each API release. This gets more challenging when performing an integrated or historical analysis. To cope with such complexity, in this paper, we present the Big Data Integration ontology, the core construct t...
Citation
Nadal, S., Romero, O., Abelló, A., Vassiliadis , P., Vansummeren, S. An integration-oriented ontology to govern evolution in big data ecosystems. "Information systems", vol. 79, Gener 2019, p. 3-19.
Keywords
Data integration, Evolution
Group of research
IMP - Information Modelling and Processing
inLab FIB
inSSIDE - integrated Software, Service, Information and Data Engineering

Participants