A Methodological Approach to Incorporating Data-On-The-Web: Sociological and Psychological Considerations

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Presented at the

Authors:Tim Lebo



Abstract:

For those wishing to construct an effective visualization, an understanding of human cognition is essential. This understanding must be even more comprehensive -- and detailed -- when striving to develop an automated system to produce visualizations of a disparate body of data, for a diverse set of audiences viewing the resulting visual messages with a variety of goals within a variety of contexts. After a brief review of the ongoing objectives for such a system and why it should be based on the Resource Description Framework and Linked Data principles, I will present the data aggregation and incorporation methodology developed over the past year to address practical concerns for a wealth of real-life data. The remainder of the talk will reflect upon the sociological and psychological cognitive factors of the challenges we faced, the solutions we established, and the remaining concerns we have yet to address. http://bitly.com/lebo-cogsci-issues-2011 will be used to share additional resources for this talk.


Related Projects:

Inference Web Project LogoInference Web
Principal Investigator: Deborah L. McGuinness
Description: The Inference Web is a Semantic Web based knowledge provenance infrastructure that supports interoperable explanations of sources, assumptions, learned information, and answers as an enabler for trust. Provenance - if users (humans and agents) are to use and integrate data from unknown, uncertain, or multiple sources, they need provenance metadata for evaluation Interoperability - more systems are using varied sources and multiple information manipulation engines, thus increasing interoperability requirements Explanation/Justification - if information has been manipulated (i.e., by sound deduction or by heuristic processes), information manipulation trace information should be available Trust - if some sources are more trustworthy than others, trust ratings are desired The Inference Web consists of two important components: Proof Markup Language (PML) Ontology - Semantic Web based representation for exchanging explanations including provenance information - annotating the sources of knowledge justification information - annotating the steps for deriving the conclusions or executing workflows trust information - annotating trustworthiness assertions about knowledge and sources IW Toolkit - Web-based and standalone tools that facilitate human users to browse, debug, explain, and abstract the knowledge encoded in PML.
DCO-DS LogoLinking Open Government Data (LOGD)
Principal Investigator: Jim Hendler and Deborah L. McGuinness
Description: The LOGD project investigates the role of Semantic Web technologies, especially Linked Data, in producing, enhancing and utilizing government data published on Data.gov and other websites.

Related Research Areas:

Inference And Trust
Lead Professor: Deborah L. McGuinness
Description: Inference And Trust
Concepts:
Knowledge Provenance
Lead Professor: Deborah L. McGuinness
Description: Knowledge Provenance
Concepts: Provenance,
X-informatics
Lead Professor: Peter Fox
Description: In the last 2-3 years, Informatics has attained greater visibility across a broad range of disciplines, especially in light of great successes in bio- and biomedical-informatics and significant challenges in the explosion of data and information resources. Xinformatics is intended to provide both the common informatics knowledge as well as how it is implemented in specific disciplines, e.g. X=astro, geo, chem, etc. Informatics' theoretical basis arises from information science, cognitive science, social science, library science as well as computer science. As such, it aggregates these studies and adds both the practice of information processing, and the engineering of information systems.
Concepts: ,