Configurable User Interface Framework for Cross-Disciplinary and Citizen Science

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Use cases for data discovery and analysis vary widely when looking across disciplines and levels of expertise. Domain experts across disciplines may have a thorough understanding of self-describing data formats, such as netCDF, and the software packages that are compatible. However, they may be unfamiliar with specific vocabulary terms used to describe the data parameters or instrument packages used in someone else’s collection, which are often useful in data discovery. Citizen scientists may struggle with both expert vocabularies and knowledge of existing tools for analyzing and visualizing data. There are some solutions to these problems. For expert vocabularies, semantic technologies like the Resource Description Framework (RDF) have been used to map terms from an expert vocabulary to layperson terminology. For data analysis and visualization, tools can be mapped to data products using semantic technologies as well. This presentation discusses a solution to these problems based on the S2S Framework, a configurable user interface framework for Web services. S2S unifies the two solutions previously described using a data service abstraction (“search services”) and a user interface (UI) abstraction (“widgets”). Using OWL (Ontology Web Language), S2S has defined a vocabulary for describing search services and their outputs, and the compatibility of those outputs with UI widgets. By linking search service outputs to widgets, S2S can automatically compose UIs for search and analysis of data, making it easier for citizen scientists to manipulate data. Addressing the problem of expert vocabularies, we have created Linked Data widgets for S2S, which can leverage distributed RDF resources to present alternative views of expert vocabularies. This presentation covers some examples where we have applied Linked Data widgets to improve data discovery for both cross-disciplinary and non-expert users.


DateCreated ByLink
April 25, 2012
Peter FoxDownload

Related Projects:

SeSF Project LogoSemantic eScience Framework (SeSF)
Principal Investigator: Peter Fox
Co Investigator: Jim Hendler and Deborah L. McGuinness
Description: Over the past few years, semantic technologies have evolved and new tools are appearing. Part of the effort in this project will be to accommodate these advances in the new framework and lay out a sustainable software path for the (certain) technical advances. In addition to a generalization of the current data science interface, we will include an upper-level interface suitable for use by clearinghouses, and/or educational portals, digital libraries, and other disciplines.

Related Research Areas:

Data Frameworks
Lead Professor: Peter Fox
Description: None.
Concepts: eScience
Semantic eScience
Lead Professor: Peter Fox
Science has fully entered a new mode of operation. E-science, defined as a combination of science, informatics, computer science, cyberinfrastructure and information technology is changing the way all of these disciplines do both their individual and collaborative work.
As semantic technologies have been gaining momentum in various e-Science areas (for example, W3C's new interest group for semantic web health care and life science), it is important to offer semantic-based methodologies, tools, middleware to facilitate scientific knowledge modeling, logical-based hypothesis checking, semantic data integration and application composition, integrated knowledge discovery and data analyzing for different e-Science applications.
Partially influenced by the Artificial Intelligence community, the Semantic Web researchers have largely focused on formal aspects of semantic representation languages or general-purpose semantic application development, with inadequate consideration of requirements from specific science areas. On the other hand, general science researchers are growing ever more dependent on the web, but they have no coherent agenda for exploring the emerging trends on the semantic web technologies. It urgently requires the development of a multi-disciplinary field to foster the growth and development of e-Science applications based on the semantic technologies and related knowledge-based approaches.

Concepts: eScience