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Projects

TWC Faculty: Tomek Strzalkowski
Research Staff: Ning Sa, Henrique Santos
Funding Agency/Sponsor: Office of Naval Research

Rubric-Based Intelligent Curation (RUBICON) is a modular framework for building sailor-centric, domain-specific systems that curate and guide text-based reporting at the time of entry. It uses large language models (LLMs), report quality rubrics (RQRs), and an automated initialization curriculum that can be adapted to a wide range of report domains with minimal human input. Using an interactive in-line suggestion interface, RUBICON simultaneously reduces the warfighter’s burden for detailed report writing while improving report data quality.

TWC Faculty: Deborah L. McGuinness
Research Staff: Henrique Santos
Funding Agency/Sponsor: William T. Grant Foundation

How do clinical supervisory decisions improve the use of research evidence in mental health treatment activities and youth mental health outcomes?

TWC Faculty: Deborah L. McGuinness, Jim Hendler
Research Staff: John S. Erickson, Henrique Santos

ChatBS: A Context-aware LLM Exploratory Sandbox uses the OpenAI Completion API service (GPT-4-0613 model) to answer questions. Each sentence in a ChatBS result is automatically linked to a Google query to facilate fact-checking. If requested, ChatBS can then use the OpenAI API to construct an entity/relation graph of these results in the form ['entity1', 'relationship', 'entity2'].

TWC Faculty: Deborah L. McGuinness
Research Staff: Jamie McCusker, Henrique Santos, John S. Erickson, Sabbir M. Rashid

Whyis is a provenance-aware nano-scale knowledge graph publishing, management, and analysis framework. Whyis aims to support domain-aware management and curation of knowledge from many different sources. Its primary goal is to enable creation of useful domain- and data-driven knowledge graphs. Knowledge can be contributed and managed through direct user interaction, statistical analysis, or data ingestion from many different kinds of data sources.

TWC Faculty: Deborah L. McGuinness
Research Staff: Henrique Santos, Sabbir M. Rashid, Jamie McCusker
The aim of the Semantic Data Dictionary (SDD) approach is to annotate datasets such that it is machine readable, uses best practice ontologies, and follows FAIR Guiding Principles. It is a project that was developed to address machines’ difficulty in understanding data dictionaries, a standard method used to describe datasets through the use of tables that identify information about data variables’ content, description, and format. With SDD, there is an extension and integration of data from multiple domains using a common metadata standard.
Research Staff: Jamie McCusker, Sabbir M. Rashid

Semantic Extract, Transform, and Load-er (SETLr) is a flexible, scalable tool for providing semantic interpretations to tabular, XML, and JSON-based data from local or web files. It has been used by diverse projects and has shown to be scalable and flexible, allowing for the simplified creation of arbitrary RDF, including ontologies and nanopublications, from many different data formats. Semantic ETL scripts use best practice standards for provenance (PROV-O) and support streaming conversion for RDF transformation using the JSON-LD based templating language, JSLDT.

TWC Faculty: Deborah L. McGuinness
Research Staff: Henrique Santos
Funding Agency/Sponsor: National Institutes of Health
HADatAc (Human-Aware Data Acquisition framework) is an open-source infrastructure that enables combined acquisitions of data and metadata in a way that metadata is properly and logically connected to data.
TWC Faculty: Tomek Strzalkowski, Deborah L. McGuinness
Research Staff: Sabbir M. Rashid, Henrique Santos
Funding Agency/Sponsor: Defense Advanced Research Projects Agency

Automated clusteRing Curriculum LearnIng Guided by Human Training (ARCLIGHT), is a classification engine capable of (1) automated discovery and characterization of objects and activities in multimedia data and (2) solicitation of input from human analysts to refine, correct, or update its internal knowledgebase.