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Articles 1 - 6 of 6
Full-Text Articles in Science and Technology Studies
Linked Open Social Signals, Pablo N. Mendes, Alexandre Passant, Pavan Kapanipathi, Amit P. Sheth
Linked Open Social Signals, Pablo N. Mendes, Alexandre Passant, Pavan Kapanipathi, Amit P. Sheth
Kno.e.sis Publications
In this paper we discuss the collection, semantic annotation and analysis of real-time social signals from micro-blogging data. We focus on users interested in analyzing social signals collectively for sensemaking. Our proposal enables flexibility in selecting subsets for analysis, alleviating information overload. We define an architecture that is based on state-of-the-art Semantic Web technologies and a distributed publish subscribe protocol for real time communication. In addition, we discuss our method and application in a scenario related to the health care reform in the United States.
Sparql Query Re-Writing For Spatial Datasets Using Partonomy Based Transformation Rules, Prateek Jain, Cory Andrew Henson, Amit P. Sheth, Peter Z. Yeh, Kunal Verma
Sparql Query Re-Writing For Spatial Datasets Using Partonomy Based Transformation Rules, Prateek Jain, Cory Andrew Henson, Amit P. Sheth, Peter Z. Yeh, Kunal Verma
Kno.e.sis Publications
Often the information present in a spatial knowledge base is represented at a different level of granularity and abstraction than the query constraints. For querying ontology’s containing spatial information, the precise relationships between spatial entities has to be specified in the basic graph pattern of SPARQL query which can result in long and complex queries. We present a novel approach to help users intuitively write SPARQL queries to query spatial data, rather than relying on knowledge of the ontology structure. Our framework re-writes queries, using transformation rules to exploit part-whole relations between geographical entities to address the mismatches between query …
Tcruzikb: Enabling Complex Queries For Genomic Data Exploration, Pablo N. Mendes, Bobby Mcknight, Amit P. Sheth, Jessica C. Kissinger
Tcruzikb: Enabling Complex Queries For Genomic Data Exploration, Pablo N. Mendes, Bobby Mcknight, Amit P. Sheth, Jessica C. Kissinger
Kno.e.sis Publications
We developed a novel analytical environment to aid in the examination of the extensive amount of interconnected data available for genome projects. Our focus is to enable flexibility and abstraction from implementation details, while retaining the expressivity required for post-genomic research. To achieve this goal, we associated genomics data to ontologies and implemented a query formulation and execution environment with added visualization capabilities. We use ontology schemas to guide the user through the process of building complex queries in a flexible Web interface. Queries are serialized in SPARQL and sent to servers via Ajax. A component for visualization of the …
A Framework To Support Spatial, Temporal And Thematic Analytics Over Semantic Web Data, Matthew Perry, Amit P. Sheth
A Framework To Support Spatial, Temporal And Thematic Analytics Over Semantic Web Data, Matthew Perry, Amit P. Sheth
Kno.e.sis Publications
Spatial and temporal data are critical components in many applications. This is especially true in analytical applications ranging from scientific discovery to national security and criminal investigation. The analytical process often requires uncovering and analyzing complex thematic relationships between disparate people, places and events. Fundamentally new query operators based on the graph structure of Semantic Web data models, such as semantic associations, are proving useful for this purpose. However, these analysis mechanisms are primarily intended for thematic relationships. In this paper, we describe a framework built around the RDF data model for analysis of thematic, spatial and temporal relationships between …
An Experiment In Integrating Large Biomedical Knowledge Resources With Rdf: Application To Associating Genotype And Phenotype Information, Satya S. Sahoo, Olivier Bodenreider, Kelly Zeng, Amit P. Sheth
An Experiment In Integrating Large Biomedical Knowledge Resources With Rdf: Application To Associating Genotype And Phenotype Information, Satya S. Sahoo, Olivier Bodenreider, Kelly Zeng, Amit P. Sheth
Kno.e.sis Publications
Bridging between genotype and phenotype is generally achieved through the integration of knowledge sources such as Entrez Gene (EG), Online Mendelian Inheritance in Man (OMIM) and the Gene Ontology (GO). Traditionally, such integration implies manual effort or the development of customized software. In this paper, we demonstrate how the Resource Description Framework (RDF) can be used to represent and integrate these resources and support complex queries over the unified resource. We illustrate the effectiveness of our approach by answering a real-world biomedical query linking a specific molecular function, glycosyltransferase, to the disorder congenital muscular dystrophy, which potentially forms a new …
What, Where And When: Supporting Semantic, Spatial And Temporal Queries In A Dbms, Matthew Perry, Amit P. Sheth, Farshad Hakimpour, Prateek Jain
What, Where And When: Supporting Semantic, Spatial And Temporal Queries In A Dbms, Matthew Perry, Amit P. Sheth, Farshad Hakimpour, Prateek Jain
Kno.e.sis Publications
Spatial and temporal data are critical components in many applications. This is especially true in analytical domains such as national security and criminal investigation. The outcome of the analytical process in these applications often hinges on uncovering and analyzing complex relationships between disparate people, places and events. Fundamentally new query operators based on the graph structure of Semantic Web data models, such as semantic associations, are proving useful in these applications. However, these analysis mechanisms are primarily intended for thematic relationships. We describe a framework built around the RDF metadata model for analysis of thematic, spatial and temporal relationships between …