Data life cycle: a perspective from the Information Science

• Autor(a) principal: Sant’Ana, Ricardo César Gonçalves
• Data de Publicação: 2016
• Tipo de documento: Artigo
• Idioma: por
• Título da fonte: Informação & Informação
• Texto Completo: https://ojs.uel.br/revistas/uel/index.php/informacao/article/view/27940
• topic: Data Life Cycle; Information Science; Big Data; Ciclo de Vida de los Datos; Ciencia de la Información; Big Data; Ciclo de Vida dos Dados; Ciência da Informação; Big Data.

Introduction: Access and use of data as a key factor has been extended to several areas of knowledge of today's society. It’s necessary to develop a new perspective that presents phases and factors involved in these processes, providing an initial analysis structure, allowing the efforts, skills and actions organization related to the data life cycle. Purpose: This article is a proposal for a new look at the data life cycle, that assumes, as a central element, the data itself, supporting itself on the concepts and contributions that Information Science can provide, without giving up the reflections on the role of other key areas such as Computer Science. Methodology: The methodological procedures consisted of bibliographic research and content analysis to describe the phases and factors related to the Data Life Cycle, developing reflections and considerations from context already consolidated in the development of systems that can corroborate the idea of centrality of data. Results: The results describe the phases of: collect, storage, recovery and discard, permeated by transverse factors: privacy, integration, quality, copyright, dissemination and preservation, composing a Data Life Cycle. Conclusions: The current context of the availability of large volumes of data, with great variety and at speeds that provide access in real time, setting the so-called Big Data that requires new concerns about access and use processes of data. The Information Science may offer a new approach, now centered in the data, and contribute to the optimization of Data Life Cycle as a whole, extending bridges between users and the data they need.