0000000000589347

AUTHOR

Ashish Karmacharya

showing 8 related works from this author

Interpreting Heterogeneous Geospatial Data Using Semantic Web Technologies

2016

International audience; The paper presents work on implementation of semantic technologies within a geospatial environment to provide a common base for further semantic interpretation. The work adds on the current works in similar areas where priorities are more on spatial data integration. We assert that having a common unified semantic view on heterogeneous datasets provides a dimension that allows us to extend beyond conventional concepts of searchability, reusability, composability and interoperability of digital geospatial data. It provides contextual understanding on geodata that will enhance effective interpretations through possible reasoning capabilities. We highlight this through …

[ INFO ] Computer Science [cs]Geospatial analysisComputer scienceInteroperabilitySemantification02 engineering and technologySDIcomputer.software_genreSocial Semantic Web020204 information systems0202 electrical engineering electronic engineering information engineeringSemantic analyticsGeospatial PDF[INFO]Computer Science [cs]Web Coverage ServiceSemantic Web StackSemantic WebData WebR2RMLInformation retrievalLand usebusiness.industryCIPcomputer.file_formatGeoSPARQLInteroperabilityGeoSPARQLSemantic technology020201 artificial intelligence & image processingHeterogeneitybusinesscomputer
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Automatic object detection in point clouds based on knowledge guided algorithms

2013

The modeling of real-world scenarios through capturing 3D digital data has been proven applicable in a variety of industrial applications, ranging from security, to robotics and to fields in the medical sciences. These different scenarios, along with variable conditions, present a challenge in discovering flexible appropriate solutions. In this paper, we present a novel approach based on a human cognition model to guide processing. Our method turns traditional data-driven processing into a new strategy based on a semantic knowledge system. Robust and adaptive methods for object extraction and identification are modeled in a knowledge domain, which has been created by purely numerical strate…

business.industryComputer sciencePoint cloudRoboticsMachine learningcomputer.software_genreObject (computer science)Data typeObject detectionDomain (software engineering)Knowledge modelingIdentification (information)Artificial intelligencebusinesscomputerAlgorithmVideometrics, Range Imaging, and Applications XII; and Automated Visual Inspection
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Use of Geospatial Analyses for Semantic Reasoning

2010

International audience; This work focuses on the integration of the spatial analyses for semantic reasoning in order to compute new axioms of an existing OWL ontology. To make it concrete, we have defined Spatial Built-ins, an extension of existing Built-ins of the SWRL rule language. It permits to run deductive rules with the help of a translation rule engine. Thus, the Spatial SWRL rules are translated to standard SWRL rules. Once the spatial functions of the Spatial SWRL rules are computed with the help of a spatial database system, the resulting translated rules are computed with a reasoning engine such as Racer, Jess or Pellet.

Geospatial analysisComputer scienceGIS system02 engineering and technologycomputer.software_genreLNCS[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]Spatial Knowledge Reasoning0202 electrical engineering electronic engineering information engineering[ INFO.INFO-AI ] Computer Science [cs]/Artificial Intelligence [cs.AI]AxiomSWRLcomputer.programming_languageOWLInformation retrieval[INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB]Spatial databaseBuilt-ins020207 software engineeringWeb Ontology LanguageSemantic reasonerExtension (predicate logic)Spatial function[ INFO.INFO-DB ] Computer Science [cs]/Databases [cs.DB]020201 artificial intelligence & image processingcomputerSpatial functions
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Spatialization of the Semantic Web

2012

syntax for Horn-like rules. The SWRL as the form, antecedentconsequent, where both antecedent and consequent are conjunctions of atoms written a1^ ... ^ an. Atoms in rules can be of the form C(x), P(x,y), Q(x,z), sameAs(x,y), differentFrom(x,y), or builtIn(pred, z1, ..., zn), where C is an OWL description, P is an OWL individual-valued property, Q is an OWL data-valued property, pred is a datatype predicate URIref, x and y are either individual-valued variables or OWL individuals, and z, z1, ... zn are either data-valued variables or OWL data literals. An OWL data literal is either a typed literal or a plain literal. Variables are indicated by using the standard convention of prefixing the…

computer.internet_protocolProgramming languagebusiness.industryComputer science02 engineering and technologyOntology (information science)computer.software_genreSocial Semantic WebWorld Wide WebXQueryXML Schema (W3C)020204 information systems0202 electrical engineering electronic engineering information engineeringLiteral (computer programming)020201 artificial intelligence & image processingSemantic Web StackbusinesscomputerSemantic WebXPathcomputer.programming_language
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Integration of Spatial processing and knowledge Processing through the Semantic Web Stack

2011

International audience; This paper presents the integration process of spatial technologies and Semantic Web technologies and its associated tool. The result of this work is a spatial query and rule engine of spatial. To do so, existing ontology with spatial elements is adjusted in order to process the spatial knowledge through spatial technologies. This paper outlines the methods and the processes of these adjustments and how results are returned by our tool. The SWRL and the SPARQL language are extended for spatial purpose and the existing OWL ontology wine is used as an application example.

Spatial processing010504 meteorology & atmospheric sciencescomputer.internet_protocolComputer science02 engineering and technologyOntology (information science)computer.software_genre01 natural sciencesSPARQLOWL-SSocial Semantic WebRule languageOWL Ontology0202 electrical engineering electronic engineering information engineeringSPARQL[INFO.INFO-DB] Computer Science [cs]/Databases [cs.DB]Semantic Web StackSemantic WebSWRL0105 earth and related environmental sciencesKnowledge processingInformation retrieval[INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB]Databasebusiness.industrySemantic Web Rule Languagecomputer.file_formatSpatial query[ INFO.INFO-DB ] Computer Science [cs]/Databases [cs.DB]020201 artificial intelligence & image processingbusinessQuery languagecomputer
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An SDI for archaeological data with a RESTful interface to semantically modeled information

2013

International audience; The poster focuses on current activities carried out within a bi-national research project "HIGEOMES - Die historische Geographie Obermesopotamiens im 2. Jahrtausend v. Chr.". Motivated by the increase of archaeological and epigraphic sources in recent decades the project aims at an integrated analysis and transparent access of these heterogeneous data. A designed application needs to consider that archaeological data contain absolute geography - the association with a specific geographic location, while epigraphic data imply relative geography - the topological relation of places. The solution is provided by a Web GIS interface supporting scientists to better unders…

[ INFO.INFO-DB ] Computer Science [cs]/Databases [cs.DB][INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB][INFO.INFO-WB] Computer Science [cs]/WebArchaeology[INFO.INFO-WB]Computer Science [cs]/Web[ INFO.INFO-WB ] Computer Science [cs]/Web[INFO.INFO-DB] Computer Science [cs]/Databases [cs.DB]Information SystemSDISemantics
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ArchaeoKM: Managing Data through Knowledge in Industrial Archaeological Sites

2011

pas de résumé

[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI][ INFO.INFO-AI ] Computer Science [cs]/Artificial Intelligence [cs.AI][INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]
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ArchaeoKM: Realizing Knowledge of the Archaeologists

2010

The potentiality of ontology within the faculty of archaeology has recently been felt. However, the use of ontology is limited either within the data interoperability for data sharing within various heterogeneous platforms or data integration of heterogeneous dataset. Thus the full potentiality of ontology is still to be realized within the community of archaeology. We are developing a system "ArchaeoKM" which uses ontology beyond data integration. It uses the strength of ontology to reason the knowledge presented within. Additionally, ArchaeoKM involves archaeologists to define their knowledge of an excavation site through domain rules which they define through the descriptions and observa…

[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI][INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB]information system[ INFO.INFO-DB ] Computer Science [cs]/Databases [cs.DB]spatial data[INFO.INFO-DB] Computer Science [cs]/Databases [cs.DB]ontologyknowledge management[ INFO.INFO-AI ] Computer Science [cs]/Artificial Intelligence [cs.AI][INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]Industrial archaeology
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