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Full-Text Articles in OS and Networks
Alignment And Dataset Identification Of Linked Data In Semantic Web, Kalpa Gunaratna, Sarasi Lalithsena, Amit P. Sheth
Alignment And Dataset Identification Of Linked Data In Semantic Web, Kalpa Gunaratna, Sarasi Lalithsena, Amit P. Sheth
Kno.e.sis Publications
The Linked Open Data (LOD) cloud has gained significant attention in the Semantic Web community over the past few years. With rapid expansion in size and diversity, it consists of over 800 interlinked datasets with over 60 billion triples. These datasets encapsulate structured data and knowledge spanning over varied domains such as entertainment, life sciences, publications, geography, and government. Applications can take advantage of this by using the knowledge distributed over the interconnected datasets, which is not realistic to find in a single place elsewhere. However, two of the key obstacles in using the LOD cloud are the limited support …
Types Of Property Pairs And Alignment On Linked Datasets - A Preliminary Analysis, Kalpa Gunaratna, Krishnaprasad Thirunarayan, Amit P. Sheth
Types Of Property Pairs And Alignment On Linked Datasets - A Preliminary Analysis, Kalpa Gunaratna, Krishnaprasad Thirunarayan, Amit P. Sheth
Kno.e.sis Publications
Dataset publication on the Web has been greatly influenced by the Linked Open Data (LOD) project. Many interlinked datasets have become freely available on the Web creating a structured and distributed knowledge representation. Analysis and aligning of concepts and instances in these interconnected datasets have received a lot of attention in the recent past compared to properties. We identify three different categories of property pairs found in the alignment process and study their relative distribution among well known LOD datasets. We also provide comparative analysis of state-of-the-art techniques with regard to different categories, highlighting their capabilities. This could lead to …
Key Ingredients For Your Next Semantics Elevator Talk, Krzysztof Janowicz, Pascal Hitzler
Key Ingredients For Your Next Semantics Elevator Talk, Krzysztof Janowicz, Pascal Hitzler
Computer Science and Engineering Faculty Publications
2012 brought a major change to the semantics research community. Discussions on the use and benefits of semantic technologies are shifting away from the why to the how. Surprisingly this more in stakeholder interest is not accompanied by a more detailed understanding of what semantics research is about. Instead of blaming others for their (wrong) expectations, we need to learn how to emphasize the paradigm shift proposed by semantics research while abstracting from technical details and advocate the added value in a way that relates to the immediate needs of individual stakeholders without overselling. This paper highlights some of …
Linked Sensor Data, Harshal Kamlesh Patni, Cory Andrew Henson, Amit P. Sheth
Linked Sensor Data, Harshal Kamlesh Patni, Cory Andrew Henson, Amit P. Sheth
Kno.e.sis Publications
A number of government, corporate, and academic organizations are collecting enormous amounts of data provided by environmental sensors. However, this data is too often locked within organizations and underutilized by the greater community. In this paper, we present a framework to make this sensor data openly accessible by publishing it on the Linked Open Data (LOD) Cloud. This is accomplished by converting raw sensor observations to RDF and linking with other datasets on LOD. With such a framework, organizations can make large amounts of sensor data openly accessible, thus allowing greater opportunity for utilization and analysis.
Dynamic Associative Relationships On The Linked Open Data Web, Pablo N. Mendes, Pavan Kapanipathi, Delroy H. Cameron, Amit P. Sheth
Dynamic Associative Relationships On The Linked Open Data Web, Pablo N. Mendes, Pavan Kapanipathi, Delroy H. Cameron, Amit P. Sheth
Kno.e.sis Publications
We provide a definition of context based on theme, time and location, and propose a mixed retrieval/extraction model for the dynamic suggestion of trending relationships to LOD resources.
Sensor Discovery On Linked Data, Josh Pschorr, Cory Andrew Henson, Harshal Kamlesh Patni, Amit P. Sheth
Sensor Discovery On Linked Data, Josh Pschorr, Cory Andrew Henson, Harshal Kamlesh Patni, Amit P. Sheth
Kno.e.sis Publications
There has been a drive recently to make sensor data accessible on the Web. However, because of the vast number of sensors collecting data about our environment, finding relevant sensors on the Web is a non-trivial challenge. In this paper, we present an approach to discovering sensors through a standard service interface over Linked Data. This is accomplished with a semantic sensor network middleware that includes a sensor registry on Linked Data and a sensor discovery service that extends the OGC Sensor Web Enablement. With this approach, we are able to access and discover sensors that are positioned near named-locations …
Provenance Aware Linked Sensor Data, Harshal Kamlesh Patni, Satya S. Sahoo, Cory Andrew Henson, Amit P. Sheth
Provenance Aware Linked Sensor Data, Harshal Kamlesh Patni, Satya S. Sahoo, Cory Andrew Henson, Amit P. Sheth
Kno.e.sis Publications
Provenance, from the French word “provenir”, describes the lineage or history of a data entity. Provenance is critical information in the sensors domain to identify a sensor and analyze the observation data over time and geographical space. In this paper, we present a framework to model and query the provenance information associated with the sensor data exposed as part of the Web of Data using the Linked Open Data conventions. This is accomplished by developing an ontology-driven provenance management infrastructure that includes a representation model and query infrastructure. This provenance infrastructure, called Sensor Provenance Management System (PMS), is …