Data curation is a critical step in scientific data digitization, sharing, integration and use. The considerable resources allocated to digitization of natural science collections in the U.S. and globally require a focus on both digitization efficiencies and the utility of the generated data. One way to address both issues is to employ workflow software to automate and streamline data curation…

This project will create both a master’s and doctoral-level specialization in Socio-technical Data Analytics (SODA). Partnerships with local researchers and businesses who already work with large data-sets will enable master's graduates to receive first-hand experience with both the social and technical implications of large digital data collections, and thus be well-prepared for leadership…

This project arises from longstanding recognition of the challenges associated with the documentation of, and access to, collections of performance ephemera, for which the British Library is a key repository in the UK. Live musical events play a vital role in community life across the globe, yet they often leave only faint traces on the historical record, even in modern times. Sources can be…

This project is a collaboration with Harvard University and the Astrophysics Data System (ADS), a digital library portal operated by the Smithsonian Astrophysical Observatory (SAO) under a NASA grant. With over 15 million records, ADS is one of the most important archives in the scientific field of astronomy.

"Newer documents are ‘born digital,’ making them machine-readable and…

Graph Neural Networks have proven to be a powerful tool for harnessing graph data, which is widely used for representing rich relational information in multiple areas. However, the performance of graph neural networks largely depends on the amount of labeled data, which is subject to an expensive and time-consuming annotation process. This creates data without labels, or a label scarcity.…