Harvard University
To make empirical research more reliable and replicable by helping academic journals process, publish, and preserve datasets accompanying article submissions
When researchers share data, their empirical results become more reproducible and more reusable. This, in turn, can accelerate progress while enhancing accountability and transparency. This grant supports efforts by Gary King and Mercи Crosas of the Institute for Quantitative Social Science (IQSS) at Harvard University to facilitate data sharing through continued development of the Dataverse Network (DVN), a leading Harvard-based data repository. Working with scientists, technologists, and academic publishers, King and Crosas have launched an ambitious project to help academic journals make data submission a fully integrated part of the paper submission process, using the Dataverse infrastructure to store and manipulate data submitted by authors. Grant funds will support several activities aimed at expanding and improving Dataverse, including convening workshops and conferences with stakeholders to develop uniform standards and protocols, crafting an application programming interface, and developing several “data widgets” that allow real-time manipulation of data uploaded to the system.