Presentation Title
Dark Data: making dark data FAIR
Abstract
Because the FAIR principles emphasize usability and accessibility of data, applying those principles to data that shouldn't exist or shouldn't persist increase the potential for harm. The goal of reducing how much data remains dark is a valuable one, but only if the data have appropriate safeguards against inappropriate use. We thus argue in this paper that the goals of the Making Dark Data Fair project are important goals, but only if they include explicit considerations of the necessary safeguards to ensure that the use of the data comply with all legal and moral obligations. In this paper we will discuss ethical considerations of dark data and evaluate computing and procedural solutions for a fair and ethical data stewardship pipeline.
Primary Faculty Mentor Name
Christopher M. Danforth
Faculty/Staff Collaborators
Christopher M. Danforth, Peter Sheridan Dodds, Randall Harp, Carter Ward
Status
Graduate
Student College
College of Engineering and Mathematical Sciences
Program/Major
Complex Systems
Primary Research Category
Engineering & Physical Sciences
Secondary Research Category
Arts & Humanities
Dark Data: making dark data FAIR
Because the FAIR principles emphasize usability and accessibility of data, applying those principles to data that shouldn't exist or shouldn't persist increase the potential for harm. The goal of reducing how much data remains dark is a valuable one, but only if the data have appropriate safeguards against inappropriate use. We thus argue in this paper that the goals of the Making Dark Data Fair project are important goals, but only if they include explicit considerations of the necessary safeguards to ensure that the use of the data comply with all legal and moral obligations. In this paper we will discuss ethical considerations of dark data and evaluate computing and procedural solutions for a fair and ethical data stewardship pipeline.