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2018 | OriginalPaper | Chapter

Generating Executable Mappings from RDF Data Cube Data Structure Definitions

Authors: Christophe Debruyne, Dave Lewis, Declan O’Sullivan

Published in: On the Move to Meaningful Internet Systems. OTM 2018 Conferences

Publisher: Springer International Publishing

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Abstract

Data processing is increasingly the subject of various internal and external regulations, such as GDPR which has recently come into effect. Instead of assuming that such processes avail of data sources (such as files and relational databases), we approach the problem in a more abstract manner and view these processes as taking datasets as input. These datasets are then created by pulling data from various data sources. Taking a W3C Recommendation for prescribing the structure of and for describing datasets, we investigate an extension of that vocabulary for the generation of executable R2RML mappings. This results in a top-down approach where one prescribes the dataset to be used by a data process and where to find the data, and where that prescription is subsequently used to retrieve the data for the creation of the dataset “just in time”. We argue that this approach to the generation of an R2RML mapping from a dataset description is the first step towards policy-aware mappings, where the generation takes into account regulations to generate mappings that are compliant. In this paper, we describe how one can obtain an R2RML mapping from a data structure definition in a declarative manner using SPARQL CONSTRUCT queries, and demonstrate it using a running example. Some of the more technical aspects are also described.
Footnotes
1
While RDF provides us the data model, data is usually integrated using a common model captured in a so-called ontology. Ontologies – being commonly defined as “a [formal] explicit specification of a [shared] conceptualization” [10] – are also developed for a particular purpose, but the ontologies (or vocabularies) we observe on the Linked Data Web are often lightweight and meant for information exchange. Applications that consume such Linked Data are not (necessarily) known beforehand and are often published with very accessible licenses such as Creative Commons.
 
2
Even if we were not to use RDF Data Cube and R2RML, similar steps would be necessary for capturing the schema or structure of the dataset, and the creation and execution of a mapping to populate that schema.
 
3
We thank the anonymous reviewer for spotting this issue.
 
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Metadata
Title
Generating Executable Mappings from RDF Data Cube Data Structure Definitions
Authors
Christophe Debruyne
Dave Lewis
Declan O’Sullivan
Copyright Year
2018
DOI
https://doi.org/10.1007/978-3-030-02671-4_21

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