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15.6 - Transforming Data Adaptation Science and Services: An Innovative Visual Ontology Application

Project - Summary


The objectives of our CVDI project were to develop:

  • A prototype visual ontology application for capturing software reuse and adaptation in a target test domain.
  • A platform for modeling adaptation science and service.
  • An approach for CVDI partners to determine and strategically plan for greater impact of data, application, and algorithm outputs.

Project - Team

Team Member Role Email Phone Number Academic Site/IAB
Jane Greenberg PI Not available Not available Drexel University
Xia Lin PI Not available Not available Drexel University
Kai Li PhD Student Not available Not available Drexel University
Xuemei Gong PhD Student Not available Not available Drexel University

Project - Impact and Uses/Benefits

The impact and benefits of our work include the following:

  • A more accurate view of data and algorithm reuse.
  • Platform to enable radical, new adaptation combinations, documenting reuse of data and algorithms.

Specific to industry, our work can help industry provide services that support better science and informed decision making. The actual impact on better science is hard to measure, although the growth in digital data and data intensive research provides opportunities to address society's grand challenges in ways that have been previously unimaginable. The cost of data gathering and software development is not trivial, and the reuse of these resources is being mandated and encouraged by federal agencies. Industry also recognizes the value of these approaches in efforts such as the recent launch of the NSF Big Data Regional Hubs. The work pursued and achieved in our CVDI project leads to a better return on investment (ROI) of resources allocated to data and software creation, use, archiving, by enabling reuse that is accurate and resourceful. The work may also procure deeper understanding sustainable knowledge of ontological connections among knowledge assets. Finally, we believe the work can lead to better effort to explore predictive capabilities in the future, although more research is needed in this area.

Project - Deep Dive

Project - Documents

FilenameFilesizeLast modified
15.6_year_4_ip_letter_combined.pdf371.0 KiB2019/08/22 11:50
15.6_year_4_presentation.pptx2.4 MiB2019/08/22 11:50
15.6_year_4_quad.pptx1.5 MiB2019/08/22 11:50
15.6_year_4_executive_summary.pdf159.6 KiB2019/08/22 11:50
15.6_year_4_final_report.pdf627.9 KiB2019/08/22 10:33
projects/year4/15.6.txt · Last modified: 2019/08/22 10:35 by sally.johnson