TAG ARCHIVES FOR data sharing

18
Feb2020

This edition of Research Ethics Roundup covers “unkind science” and the public’s waning trust, international efforts to develop data sharing standards, lack of diversity in psychological research subjects, and digital phenotyping.  Read more

10
Jan2020

On November 8, 2019, the National Institutes of Health (NIH) released its Draft NIH Policy for Data Management and Sharing and Supplement Draft Guidance as part of its continuing efforts to ensure public access to research the government conducts and pays for. Today, PRIM&R submitted comments applauding the NIH for taking steps to accelerate data sharing efforts while also offering a few constructive suggestions primarily centered around privacy and funding issues. The comment period closes today, and we encourage interested parties to consider submitting their own comments. Read more

5
Aug2019

Enthusiasm for data sharing and research transparency has grown across the social sciences. This newer scholarly imperative has begun to overlap with the long-standing mandate to minimize risks for human subjects in research. IRBs play a crucial role in this realm, as the IRB’s recommendations on a social science research protocol will often determine whether or not the data obtained through the study may be shared in the future. IRBs are tasked with assisting and educating social scientists to include the appropriate elements, language, and procedures in their protocol materials in order for researchers to approach data sharing in an ethical and responsible manner. Read more

19
Jun2019

There’s a growing trend in Social, Behavioral, and Education Research (SBER)–machine learning–in which investigators often request to obtain, through direct interaction and intervention, various sets of data on human subjects, including their physiological (i.e., data obtained from either invasive or non-invasive means) and/or biometric data (e.g., audio/visual recordings). The research as originally conceived may or may not have been considered human subjects research, but its ultimate purpose is to teach machines how to think, draw conclusions, and process information in much the same way humans do. Read more