Multi-Paradigm Reasoning for Access to Heterogeneous GIS

Accessing and querying geographical data in a uniform way has become easier in recent years. Emerging standards like WFS turn the web into a geospatial web services enabled place. Mediation architectures like VirGIS overcome syntactical and semantical heterogeneity between several distributed sources. On mobile devices, however, this kind of solution is not suitable, due to limitations, mostly regarding bandwidth, computation power, and available storage space. The aim of this paper is to present a solution for providing powerful reasoning mechanisms accessible from mobile applications and involving data from several heterogeneous sources. By adapting contents to time and location, mobile web information systems can not only increase the value and suitability of the service itself, but can substantially reduce the amount of data delivered to users. Because many problems pertain to infrastructures and transportation in general and to way finding in particular, one cornerstone of the architecture is higher level reasoning on graph networks with the Multi-Paradigm Location Language MPLL. A mediation architecture is used as a “graph provider” in order to transfer the load of computation to the best suited component – graph construction and transformation for example being heavy on resources. Reasoning in general can be conducted either near the “source” or near the end user, depending on the specific use case. The concepts underlying the proposal described in this paper are illustrated by a typical and concrete scenario for web applications

Heterogeneous biomedical database integration using a hybrid strategy: a p53 cancer research database.

Complex problems in life science research give rise to multidisciplinary collaboration, and hence, to the need for heterogeneous database integration. The tumor suppressor p53 is mutated in close to 50% of human cancers, and a small drug-like molecule with the ability to restore native function to cancerous p53 mutants is a long-held medical goal of cancer treatment. The Cancer Research DataBase (CRDB) was designed in support of a project to find such small molecules. As a cancer informatics project, the CRDB involved small molecule data, computational docking results, functional assays, and protein structure data. As an example of the hybrid strategy for data integration, it combined the mediation and data warehousing approaches. This paper uses the CRDB to illustrate the hybrid strategy as a viable approach to heterogeneous data integration in biomedicine, and provides a design method for those considering similar systems. More efficient data sharing implies increased productivity, and, hopefully, improved chances of success in cancer research. (Code and database schemas are freely downloadable, http://www.igb.uci.edu/research/research.html.)

Geospatial data integration with Semantic Web services: the eMerges approach

Geographic space still lacks the semantics allowing a unified view of spatial data. Indeed, as a unique but all encompassing domain, it presents specificities that geospatial applications are still unable to handle. Moreover, to be useful, new spatial applications need to match human cognitive abilities of spatial representation and reasoning. In this context, eMerges, an approach to geospatial data integration based on Semantic Web Services (SWS), allows the unified representation and manipulation of heterogeneous spatial data sources. eMerges provides this integration by mediating legacy spatial data sources to high-level spatial ontologies through SWS and by presenting for each object context dependent affordances. This generic approach is applied here in the context of an emergency management use case developed in collaboration with emergency planners of public agencies

Semantic Technologies for Manuscript Descriptions — Concepts and Visions

The contribution at hand relates recent developments in the area of the World Wide Web to codicological research. In the last number of years, an informational extension of the internet has been discussed and extensively researched: the Semantic Web. It has already been applied in many areas, including digital information processing of cultural heritage data. The Semantic Web facilitates the organisation and linking of data across websites, according to a given semantic structure. Software can then process this structural and semantic information to extract further knowledge. In the area of codicological research, many institutions are making efforts to improve the online availability of handwritten codices. If these resources could also employ Semantic Web techniques, considerable research potential could be unleashed. However, data acquisition from less structured data sources will be problematic. In particular, data stemming from unstructured sources needs to be made accessible to SemanticWeb tools through information extraction techniques. In the area of museum research, the CIDOC Conceptual Reference Model (CRM) has been widely examined and is being adopted successfully. The CRM translates well to Semantic Web research, and its concentration on contextualization of objects could support approaches in codicological research. Further concepts for the creation and management of bibliographic coherences and structured vocabularies related to the CRM will be considered in this chapter. Finally, a user scenario showing all processing steps in their context will be elaborated on

Towards structured sharing of raw and derived neuroimaging data across existing resources

Data sharing efforts increasingly contribute to the acceleration of scientific discovery. Neuroimaging data is accumulating in distributed domain-specific databases and there is currently no integrated access mechanism nor an accepted format for the critically important meta-data that is necessary for making use of the combined, available neuroimaging data. In this manuscript, we present work from the Derived Data Working Group, an open-access group sponsored by the Biomedical Informatics Research Network (BIRN) and the International Neuroimaging Coordinating Facility (INCF) focused on practical tools for distributed access to neuroimaging data. The working group develops models and tools facilitating the structured interchange of neuroimaging meta-data and is making progress towards a unified set of tools for such data and meta-data exchange. We report on the key components required for integrated access to raw and derived neuroimaging data as well as associated meta-data and provenance across neuroimaging resources. The components include (1) a structured terminology that provides semantic context to data, (2) a formal data model for neuroimaging with robust tracking of data provenance, (3) a web service-based application programming interface (API) that provides a consistent mechanism to access and query the data model, and (4) a provenance library that can be used for the extraction of provenance data by image analysts and imaging software developers. We believe that the framework and set of tools outlined in this manuscript have great potential for solving many of the issues the neuroimaging community faces when sharing raw and derived neuroimaging data across the various existing database systems for the purpose of accelerating scientific discovery

Future internet enablers for VGI applications

This paper presents the authors experiences with the development of mobile Volunteered Geographic Information (VGI) applications in the context of the ENVIROFI project and Future Internet Public Private Partnership (FI-PPP) FP7 research programme.FI-PPP has an ambitious goal of developing a set of Generic FI Enablers (GEs) - software and hardware tools that will simplify development of thematic future internet applications. Our role in the programme was to provide requirements and assess the usability of the GEs from the point of view of the environmental usage area, In addition, we specified and developed three proof of concept implementations of environmental FI applications, and a set of specific environmental enablers (SEs) complementing the functionality offered by GEs. Rather than trying to rebuild the whole infrastructure of the Environmental Information Space (EIS), we concentrated on two aspects: (1) how to assure the existing and future EIS services and applications can be integrated and reused in FI context; and (2) how to profit from the GEs in future environmental applications.This paper concentrates on the GEs and SEs which were used in two of the ENVIROFI pilots which are representative for the emerging class of Volunteered Geographic Information (VGI) use-cases: one of them is pertinent to biodiversity and another to influence of weather and airborne pollution on users’ wellbeing. In VGI applications, the EIS and SensorWeb overlap with the Social web and potentially huge amounts of information from mobile citizens needs to be assessed and fused with the observations from official sources. On the whole, the authors are confident that the FI-PPP programme will greatly influence the EIS, but the paper also warns of the shortcomings in the current GE implementations and provides recommendations for further developments

A spatial mediator model for integrating heterogeneous spatial data

The complexity and richness of geospatial data create specific problems in heterogeneous data integration. To deal with this type of data integration, we propose a spatial mediator embedded in a large distributed mobile environment (GeoGrid). The spatial mediator takes a user request from a field application and uses the request to select the appropriate data sources, constructs subqueries for the selected data sources, defines the process of combining the results from the subqueries, and develop an integration script that controls the integration process in order to respond to the request. The spatial mediator uses ontologies to support search for both geographic location based on symbolic terms as well as providing a term-based index to spatial data sources based on the relational model. In our approach, application designers only need to be aware of a minimum amount about the queries needed to supply users with the required data. The key part of this research has been the development of the spatial mediator that can dynamically respond to requests within the GeoGrid environment for geographic maps and related relational spatial data

Benefits and challenges of applying Semantic Web Services in the e-Government domain

Joining up services in e-Government usually implies governmental agencies acting in concert without a central control regime. This requires the sharing of scattered and heterogeneous data. Semantic Web Service (SWS) technology can help to integrate, mediate and reason between these datasets. However, since few real-world applications have been developed, it is still unclear which are the actual benefits and issues of adopting such a technology in the e-Government domain. In this paper, we contribute to raising awareness of the potential benefits in the e-Government community by analyzing motivations, requirements, and expected results, before proposing a reusable SWS-based framework. We demonstrate the application of this framework by a compelling use case: a GIS-based emergency planning system. We illustrate the obtained benefits and the key challenges which remain to be addressed

Context Mediation Demonstration of Counter-Terrorism Intelligence (CTI) Integration

Examination of intelligence failures prior to the 9/11/01 attacks made clear it that lack of effective information exchange among government agencies hindered the capability of identifying potential threats and preventing terrorist actions. A 2002 National Research Council study noted that “Although there are many private and public databases that contain information potentially relevant to counterterrorism programs, they lack the necessary context definitions (i.e., metadata) and access tools to enable interoperation with other databases and the extraction of meaningful and timely information.”[14] This report clearly recognized the importance of problems that the semantic data integration research community has been studying