Now showing items 1-20 of 51

    • Whyis 2: An Open Source Framework for Knowledge Graph Development and Research 

      McCusker, Jamie; McGuinness, Deborah L. (Springer, 2023-03-23)
      Whyis is the first open source framework for creating custom provenance-driven knowledge graph applications, or KGApps, support- ing three principal tasks: knowledge curation, inference, and interaction. It has been used ...
    • Guiding principles for technical infrastructure to support computable biomedical knowledge 

      McCusker, Jamie; McIntosh, Leslie D.; Shaffer, Chris; Boisvert, Peter; Ryan, James; Navale, Vivek; Topaloglu, Umit; Richesson, Rachel L. (Wiley Periodicals LLC, 2022-11-01)
      Over the past 4 years, the authors have participated as members of the Mobilizing Computable Biomedical Knowledge Technical Infrastructure working group and focused on conceptualizing the infrastructure required to use ...
    • An Ontology for Fairness Metrics 

      Franklin, Jade S; Bhanot, Karan; Ghalwash, Mohamed; Bennett, Kristin P.; McCusker, Jamie; McGuinness, Deborah L. (ACM, 2022-07)
      Recent research has revealed that many machine-learning models and the datasets they are trained on suffer from various forms of bias, and a large number of different fairness metrics have been created to measure this bias. ...
    • FAIR and Interactive Data Graphics from a Scientific Knowledge Graph 

      Deagen, Michael E.; McCusker, Jamie; Fateye, Tolulomo; Stouffer, Samuel; Brinson, L. Cate; McGuinness, Deborah L.; Schadler, Linda S. (Nature Scientific Data, 2022-05)
      Graph databases capture richly linked domain knowledge by integrating heterogeneous data and metadata into a unified representation. Here, we present the use of bespoke, interactive data graphics (bar charts, scatter plots, ...
    • Geospatial Reasoning with shapefiles for Supporting Policy Decisions 

      Santos, Henrique; McCusker, Jamie; McGuinness, Deborah L. (2021-10-12)
      Policies are authoritative assets that are present in multiple domains to support decision-making. They describe what actions are allowed or recommended when domain entities and their attributes satisfy certain criteria. ...
    • Nanomine: A Knowledge Graph for Nanocomposite Materials Science 

      McCusker, Jamie; Keshan, Neha; Rashid, Sabbir; Deagen, Michael; Brinson, Cate; McGuinness, Deborah L. (2020-11-01)
      Knowledge graphs can be used to help scientists integrate and explore their data in novel ways. NanoMine, built with the Whyis knowledge graph framework, integrates diverse data from over 1,700 polymer nanocomposite ...
    • Polymer Nanocomposite Data: Curation, Frameworks, Access and Potential for Discovery and Design 

      Brinson, Cate; Deagen, Michael; Chen, Wei; McCusker, Jamie; McGuinness, Deborah L.; Schadler, Linda; Palmeri, Marc; Ghumman, Umar; Lin, Anqi; Hu, Bingyin (American Chemical Society, Macro Letters, 2020-07-01)
      With the advent of the materials genome initiative (MGI) in the United States and a similar focus on materials data around the world, a number of materials data resources and associated vocabularies, tools, and repositories ...
    • The Semantic Data Dictionary- An Approach for Describing and Annotating Data 

      Rashid, Sabbir; McCusker, Jamie; Pinheiro, Paulo; Bax, Marcello; Santos, Henrique; Stingone, Jeanette; Das, Amar K.; McGuinness, Deborah L. (2020-04-01)
      It is common practice for data providers to include text descriptions for each column when publishing datasets in the form of data dictionaries. While these documents are useful in helping an end-user properly interpret ...
    • Knowledge Extraction of Cohort Characteristics in Research Publications 

      Franklin, Jade; Chari, Shruthi; Foreman, Morgan A.; Seneviratne, Oshani; Gruen, Daniel M.; McCusker, Jamie; Das, Amar K.; McGuinness, Deborah L. (AMIA, 2020)
      When healthcare providers review the results of a clinical trial study to understand its applicability to their practice, they typically analyze how well the characteristics of the study cohort correspond to those of the ...
    • A Semantic Framework for Enabling Radio Spectrum Policy Management and Evaluation 

      Santos, Henrique; Mulvehill, Alice; Erickson, John S.; McCusker, Jamie; Gordon, Minor; Xie, Owen; Stouffer, Samuel; Capraro, Gerard; Pidwerbetsky, Alex; Burgess, John; Berlinsky, Allan; Turck, Kurt; Ashdown, Jonathan; McGuinness, Deborah L. (2020)
      Because radio spectrum is a finite resource, its usage and sharing is regulated by government agencies. These agencies define policies to manage spectrum allocation and assignment across multiple organizations, systems, ...
    • Making Study Populations Visible through Knowledge Graphs 

      Chari, Shruthi; Qim, Miao; Agu, Nkechinyere; Seneviratne, Oshani; McCusker, Jamie; Bennett, Kristin P.; Das, Amar; McGuinness, Deborah L. (2019-10-12)
    • The CHEAR Data Repository: Facilitating children’s environmental health and exposome research through data harmonization, pooling and accessibility. 

      Stingone, Jeanette; Pinheiro, Paulo; Meola, Jay; McCusker, Jamie; Bengoa, Sofia; Kovatch, Patricia; McGuinness, Deborah L.; Teitelbaum, Susan (Environmental Epidemiology, 2019-10-01)
      Funded by the U.S. National Institute of Environmental Health Sciences, the Children’s Health Exposure Analysis Resource (CHEAR) provides scientific investigators access to laboratory and statistical analyses aimed at ...
    • Ontology-enabled Analysis of Study Populations 

      Chari, Shruthi; Qim, Miao; Agu, Nkechinyere; Seneviratne, Oshani; McCusker, Jamie; Bennett, Kristin P.; Das, Amar; McGuinness, Deborah L. (2019-10-01)
      We address the problem of modeling study populations in research studies in a declarative manner. Research studies often have a great degree of variability in the reporting of population descriptions. To make study populations ...
    • Automating Population Health Studies through Semantics and Statistics Semantic Statistics (SemStats) 

      New, Alexander; Qi, Miao; Chari, Shruthi; Rashid, Sabbir; Seneviratne, Oshani; McCusker, Jamie; Erickson, John S.; McGuinness, Deborah L.; Bennett, Kristin P. (Springer, 2019-10)
      With the rapid development of the Semantic Web, machines are able to understand the contextual meaning of data, including in the field of automated semantics-driven statistical reasoning. This paper introduces a ...
    • G-PROV: Provenance Management for Clinical Practice Guidelines 

      Agu, Nkechinyere; Keshan, Neha; Chari, Shruthi; Seneveratne, Oshani; Rashid, Sabbir; Das, Amar K.; McCusker, Jamie; McGuinness, Deborah L. (CEUR-WS, 2019-10)
      Providing provenance of treatment suggestions made by clinical decision support systems can enhance transparency and trust in these systems by healthcare practitioners. Provenance can aid in resolving ambiguity and conflicts ...
    • The CHEAR Data Repository: Facilitating children’s environmental health and exposome research through data harmonization, pooling and accessibility 

      Stingone, Jeanette; Pinheiro, Paulo; Meola, Jay; McCusker, Jamie; Bengoa, Sofia; Kovatch, Patricia; McGuinness, Deborah L.; Teitelbaum, Susan (2019-08-28)
      Funded by the U.S. National Institute of Environmental Health Sciences, the Children’s Health Exposure Analysis Resource (CHEAR) provides scientific investigators access to laboratory and statistical analyses aimed at ...
    • Enabling Trust in Clinical Decision Support Recommendations through Semantics 

      Seneviratne, Oshani; Das, Amar K.; Chari, Shruthi; Agu, Nkechinyere; Rashid, Sabbir; Chen, Ching-Hua; McCusker, Jamie; Hendler, James A.; McGuinness, Deborah L. (CEUR Workshop Proceedings (CEUR-WS.org), 2019)
      In an ideal world, the evidence presented in a clinical guideline would cover all aspects of patient care and would apply to all types of patients; however, in practice, this rarely is the case. Existing medical decision ...
    • A Linked Data Representation for Summary Statistics and Grouping Criteria 

      McCusker, Jamie; Dumontier, Michel; Chari, Shruthi; McGuinness, Deborah L. (CEUR-WS, 2019)
      . Summary statistics are fundamental to data science, and are the buidling blocks of statistical reasoning. Most of the data and statistics made available on government web sites are aggregate, however, until now, we ...
    • NanoMine Schema: A Data Representation for Polymer Nanocomposites 

      Zhoa, He; Wang, Yixian; Lin, Anqi; Hu, Bingyin; Yan, Rui; McCusker, Jamie; Chen, Wei; McGuinness, Deborah L.; Schadler, Linda; Brinson, Cate (APL Materials, 2018-11-30)
      Polymer nanocomposites consist of a polymer matrix and fillers with at least one dimension below 100 nanometers (nm) [L. Schadler et al., Jom 59(3), 53–60 (2007)]. A key challenge in constructing an effective data resource ...
    • Developing Probabilistic Scientific Knowledge Graphs with Whyis 

      McCusker, Jamie; McGuinness, Deborah L. (2018-11-03)