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A conceptual modelling-based approach to generate data value through the end-user interactions: A case study in the genomics domain

Abstract:

In the current Big data ecosystem, identifying the data with the real value to an organization, or in other words the "data value", is a key issue for the decision making process. Understanding data implies a challenging cognitive process, which involves the know-how of domain experts. We propose an approach based on conceptual modelling to discover the data value through the interactions made by users when exploring the data. Our main ideas are: 1) To create a base of domain knowledge represented by interactions; 2) To formalize the interactions of the users with the data ecosystem. Our goal is to express high-level interactions between end-users and the data scenario, which represents the cognitive process followed to enact value from data. Such interactions together a subjacent conceptual model will be the mechanisms to recommend the next data exploring steps. In this paper we provide a solution design to generate value from the huge amount of data.