Re-engineering data with 4D ontologies and graph databases

9Citations
Citations of this article
35Readers
Mendeley users who have this article in their library.

Abstract

The amount of data that is being made available on the Web is increasing. This provides business organisations with the opportunity to acquire large datasets in order to offer novel information services or to better market existing products and services. Much of this data is now publicly available (e.g., thanks to initiatives such as Open Government Data). The challenge from a corporate perspective is to make sense of the third party data and transform it so that it can more easily integrate with their existing corporate data or with datasets with a different provenance. This paper presents research-in-progress aimed at semantically transforming raw data on U.K. registered companies. The approach adopted is based on BORO (a 4D foundational ontology and re-engineering method) and the target technological platform is Neo4J (a graph database). The primary challenges encountered are (1) re-engineering the raw data into a 4D ontology and (2) representing the 4D ontology into a graph database. The paper will discuss such challenges and explain the transformation process that is currently being adopted. © 2013 Springer-Verlag.

Cite

CITATION STYLE

APA

De Cesare, S., Foy, G., & Partridge, C. (2013). Re-engineering data with 4D ontologies and graph databases. In Lecture Notes in Business Information Processing (Vol. 148 LNBIP, pp. 304–316). Springer Verlag. https://doi.org/10.1007/978-3-642-38490-5_29

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free