Data articles as a means to Implemet to Implement to FAIR.   Pros and Cons

403 Forbidden

Using Technology to break cultural silos towards open data and open science

Product & Innovation. aadivar has 17 repositories available. Follow their code on GitHub.

aadivar - Overview

Research assessment is the process or a metric which aims to assess the impact of the research study. The assessment may include the process that aims in evaluating the quality or intellect of a researcher given the notion that qualified scientists are more productive and may drive quality research in the process of Scholarly Communications. Over time, we have become used to equating the quality of the research with the quality or performance of the researcher. The emphasis over publications may encourage unethical practices, Which may be extrapolated to the evolution of problems like, Irreproducibility, Scientific fraud. Over the past century, a myriad of activities has been undertaken or are still being taken to improve the ways by which research can be assessed. Beginning with the first evolution of the Impact Factor and more recently other, Citation metrics, Altmetrics, etc. have resulted from this work. In this article, we discuss around the myriad of strategies that may play a significant role in the cultural transition of Science and Scientists that is still ongoing. And also highlight the reasons why we should not only look at research assessment but should also be keen on researcher evaluations and differentiate them from one another. Reflecting this, the title of the article signals how the strategies that researchers may need to consider might impact the way they interact with the Open Data movement.