Editorial: AI for Data Discovery and Reuse Huajin Wang Keith Webster 10.1184/R1/10093568.v1 https://kilthub.cmu.edu/articles/conference_contribution/Editorial_AI_for_Data_Discovery_and_Reuse/10093568 <div> <div> <div> <p>There is great value embedded in reusing scientifc data for secondary discoveries. However, it is challenging to find and reuse the large amount of existing scientific data distributed across the web and data repositories. Some of the challenges reside in the volume and complexity of scientific data, others pertain to the current practices and workflow of research data management. AIDR 2019 (Artificial Intelligence for Data Discovery and Reuse) is a new conference that brings together researchers across a broad range of disciplines, computer scientists, tool developers, data providers, and data curators, to share innovative solutions that apply artificial intelligence to scientific data discovery and reuse, and discuss how various stakeholders work together to create a healthy data ecosys- tem. This editorial summarizes the main themes and takeaways from the inaugural AIDR conference. </p> </div> </div> </div> 2019-10-31 13:21:12 Artificial Intelligence Data Reuse Data Discovery open science research data management metadata