Research and Data Reusability

Read this article. Be sure you can explain the methods (approach) for extracting data based on usability.

Abstract

High-throughput scientific instruments are generating massive amounts of data. Today, one of the main challenges faced by researchers is to make the best use of the world's growing wealth of data. Data (re)usability is becoming a distinct characteristic of modern scientific practice. By data (re)usability, we mean the ease of using data for legitimate scientific research by one or more communities of research (consumer communities) that is produced by other communities of research (producer communities). Data (re)usability allows the reanalysis of evidence, reproduction, and verification of results, minimizing duplication of effort, and building on the work of others. It has four main dimensions: policy, legal, economic, and technological. The paper addresses the technological dimension of data reusability. The conceptual foundations of data reuse as well as the barriers that hamper data reuse are presented and discussed. The data publication process is proposed as a bridge between the data author and user and the relevant technologies enabling this process are presented.


Source: Constantino Thanos, https://www.mdpi.com/2304-6775/5/1/2/htm
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