Towards Semantically-Enabled Next Generation Community Health Information Portals: The PopSciGrid Pilot

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Abstract:

We describe an approach to developing next generation health information portals. This prototype portal was developed to address two complementary goals (1) design and create a site where people can explore potential relationships between selected health-related behaviors, policies, and demographic data (2) explore semantic web technologies and linked data as enabling technologies for next generation health informatics portals. Our multidisciplinary team includes population and behavioral scientists, social network scientists, statisticians, and computer scientists focused on creating innovative proof of concept applications that integrate complex health data in understandable and usable ways. Our semantic-web based framework allowed us to design exemplar community health portal applications, with an initial focus on tobacco-related health data such as smoking prevalence and tobacco policies (taxation and smoking bans). We describe our approach, two semantically-enabled tobacco-related applications, and discuss how this approach can be used in a broad spectrum of community health applications.

History

DateCreated ByLink
September 20, 2011
19:25:03
Tim LeboDownload

Related Projects:

Health on the Web
Principal Investigator: Joanne S. Luciano and Deborah L. McGuinness
Description: The Tetherless World Constellation's Health on the Web's primary goal is to explore the next generation web technology needed to improve health.
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: Deborah L. McGuinness and Jim Hendler
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.
PopSciGrid LogoPopulation Science Grid (PopSciGrid)
Principal Investigator: Deborah L. McGuinness
Description: The National Cancer Institute’s (NCI) PopSciGrid Community Health Portal is an evolving platform demonstrating how health behavior, policy, and demographic data can be integrated, visualized, and communicated to empower communities and support new avenues of research and policy for cancer prevention and control. As a proof of concept for cyber-enabled population health research, the PopSciGrid Portal is designed to encourage trans-disciplinary collaboration, data harmonization, and development of new computational methods for disparate health related data.

Related Research Areas:

Data Frameworks
Lead Professor: Peter Fox
Description: None.
Concepts: eScience
Data Science
Lead Professor: Peter Fox
Description: Science has fully entered a new mode of operation. Data science is advancing inductive conduct of science driven by the greater volumes, complexity and heterogeneity of data being made available over the Internet. Data science combines of aspects of data management, library science, computer science, and physical science using supporting cyberinfrastructure and information technology. As such it is changing the way all of these disciplines do both their individual and collaborative work.

Data science is helping scienists face new global problems of a magnitude, complexity and interdisciplinary nature whose progress is presently limited by lack of available tools and a fully trained and agile workforce.

At present, there is a lack formal training in the key cognitive and skill areas that would enable graduates to become key participants in escience collaborations. The need is to teach key methodologies in application areas based on real research experience and build a skill-set.

At the heart of this new way of doing science, especially experimental and observational science but also increasingly computational science, is the generation of data.

Concepts: eScience
Health Informatics
Lead Professor: Deborah L. McGuinness
Description:

Health informatics is "the interdisciplinary study of the design, development, adoption and application of IT-based innovations in healthcare services delivery, management and planning." Procter, R. Dr. (Editor, Health Informatics Journal, Edinburgh, United Kingdom). (From the U.S. National Library of Medicine)


Concepts: None.
Inference And Trust
Lead Professor: Deborah L. McGuinness
Description: Inference And Trust
Concepts: Semantic Web
Semantic eScience
Lead Professor: Peter Fox
Description:
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
Social Web
Lead Professor: Jim Hendler
Description: Social Web
Concepts: Semantic Web
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: Semantic Web, eScience