DaVe: A Semantic Data Value Vocabulary to Enable Data Value Characterisation

Abstract

While data value and value creation are highly relevant in today’s society, there is as yet no consensus data value models, dynamics, measurement techniques or even methods of categorising and comparing them. In this paper we analyse and categorise existing aspects of data that are used in literature to characterise and/or quantify data value. Based on these data value dimensions, as well as a number of value assessment use cases, we also define the Data Value Vocabulary (DaVe) that allows for the comprehensive representation of data value. This vocabulary can be extended to allow for the representation of data value dimensions as required in the context at hand. This vocabulary will allow users to monitor and asses data value throughout any value creating or data exploitation efforts, therefore laying the basis for effective management of value and efficient value exploitation. It also allows for the integration of diverse metrics that span many data value dimensions and which most likely pertain to a range of different tools in different formats. DaVe is evaluated using Gruber’s ontology design criteria, and by instantiating it in a deployment case study. This paper is an extension of Attard and Brennan (2018) [3].