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…
Scholarly publications today are still mostly disconnected from the underlying data and code used to produce the published results and findings, despite an increasing recognition of the need to share all aspects of the research process. As data become more open and transportable, a second layer of research output has emerged, linking research publications to the associated data, possibly along…
This project will study foreign influence via the lens of disinformation on news media from a computational perspective. The researchers will use Explainable Heterogeneous Adversarial Machine Learning (EXHALE) to address the limitations of current techniques in terms of comprehension, characterization, and explainability.
This NIH-funded project focuses on machine learning approaches for translating transdermal alcohol content (i.e., alcohol measured from a person’s skin) into blood alcohol content (“BAC”). Modern transdermal sensors are small, easy to use, and measure transdermal alcohol content frequently, but lag behind typical measures of BAC (especially breathalyzers) in terms of accuracy. This project…
Full title: CAREER: Towards Reliable and Optimized Data-driven Cyber-Physical Systems using Human-centric Sensing
Participatory science has opened opportunities for many to participate in data collection for science experiments about the environment, local transportation, disaster response, and public safety. The nature of the collection by non-scientists on a large scale carries…
“Understanding the Needs of Scholars in a Contemporary Publishing Environment,” better know as Publishing Without Walls (PWW), is a digital scholarly publishing initiative that is scholar-driven, openly accessible, scalable, and sustainable. PWW will directly engage with scholars throughout the research process. It aims…
For over two millennia, librarians have played a critical role in the production and transmission of knowledge. They have helped to collect, catalogue, and curate a vast range of materials that constitute much of our cultural heritage—from epic poetry on papyrus scrolls to PDFs of scholarly articles. This project interrogates these practices by building a…
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.…
Understanding the value and process of research is a crucial skill for youth, who navigate an information landscape that includes a significant amount of misinformation and disinformation. Literacy approaches highlight the ability to create and share content as key competencies of literacy, but youth have few opportunities to engage in the scholarly research process to develop these skills in…
