際際滷shows by User: nandana / http://www.slideshare.net/images/logo.gif 際際滷shows by User: nandana / Mon, 14 Feb 2022 19:59:29 GMT 際際滷Share feed for 際際滷shows by User: nandana A Framework for Linked Data Quality based on Data Profiling and RDF Shape Induction /nandana/a-framework-for-linked-data-quality-based-on-data-profiling-and-rdf-shape-induction thesispresentationjune2020-220214195930
Thesis PDF version: https://oa.upm.es/62935/ In the era of digital transformation, where most decision-making and artificial intelligence (AI) applications are becoming data-driven, data is becoming an essential asset. Linked Data, published in structured, machine-readable formats, with explicit semantics using Semantic Web standards, and with links to other data, is even more useful. The Linked (Open) Data cloud is growing with millions of new triples each year. Nevertheless, as we discuss in this thesis, such vast amounts of data bring several new challenges in ensuring the quality of Linked Data. The main goal of this thesis is to propose novel and scalable methods for automatic quality assessment and repair of Linked Data. The motivation for it is to significantly reduce the manual effort required by current quality assessment and repair, and to propose novel methods suitable for large-scale Linked Data sources such as DBpedia or Wikidata. The main hypothesis of this work is that data profiling metrics and automatic RDF Shape induction can be used to develop scalable and automatic quality assessment and repair methods. In this context, the following main contributions are delivered in this thesis: LDQM, a Linked Data Quality Model for representing Linked Data quality in a standard manner and LD Sniffer, a tool based on LDQM for validating accessibility of Linked Data. LDQM contains 15 quality characteristics, 89 base measures, 23 derived measures, and 124 quality indicators. Loupe, a framework for Linked Data profiling that includes the Loupe Extended Dataset Description Model and a suite of Linked Data profiling tools. The model consists of 84 Linked Data profiling metrics useful for quality assessment and repair tasks. Loupe tools have been used to evaluate 26 thousand datasets containing 34 billions of triples and Loupe contributed to the winning system of ISWC Semantic Web Challenge 2017. The Loupe Web portal has been visited more than 40,000 times by ~3000 unique visitors from 87 countries. An automatic RDF Shape induction method that follows a data-driven approach to induce integrity constraints using data profiling metrics as features. The proposed method achieved an F1 of 98.81% in deriving maximum cardinality constraints, an F1 of 97.30% in deriving minimum cardinality constraints, and an F1 of 95.94% in deriving range constraints. Four methods for automatic quality assessment and repair using RDF Shapes and data profiling metrics. They are motivated by several practical use cases that cover both Linked Data generation process and output and also cover both public and enterprise data. The four methods include (a) a method for detecting inconsistent mappings, (b) a method for detecting and eliminating noisy triples produced by open information extraction tools, (c) a method to repair links in RDF data, and (d) a method to complete type information in Linked Data ...]]>
Thesis PDF version: https://oa.upm.es/62935/ In the era of digital transformation, where most decision-making and artificial intelligence (AI) applications are becoming data-driven, data is becoming an essential asset. Linked Data, published in structured, machine-readable formats, with explicit semantics using Semantic Web standards, and with links to other data, is even more useful. The Linked (Open) Data cloud is growing with millions of new triples each year. Nevertheless, as we discuss in this thesis, such vast amounts of data bring several new challenges in ensuring the quality of Linked Data. The main goal of this thesis is to propose novel and scalable methods for automatic quality assessment and repair of Linked Data. The motivation for it is to significantly reduce the manual effort required by current quality assessment and repair, and to propose novel methods suitable for large-scale Linked Data sources such as DBpedia or Wikidata. The main hypothesis of this work is that data profiling metrics and automatic RDF Shape induction can be used to develop scalable and automatic quality assessment and repair methods. In this context, the following main contributions are delivered in this thesis: LDQM, a Linked Data Quality Model for representing Linked Data quality in a standard manner and LD Sniffer, a tool based on LDQM for validating accessibility of Linked Data. LDQM contains 15 quality characteristics, 89 base measures, 23 derived measures, and 124 quality indicators. Loupe, a framework for Linked Data profiling that includes the Loupe Extended Dataset Description Model and a suite of Linked Data profiling tools. The model consists of 84 Linked Data profiling metrics useful for quality assessment and repair tasks. Loupe tools have been used to evaluate 26 thousand datasets containing 34 billions of triples and Loupe contributed to the winning system of ISWC Semantic Web Challenge 2017. The Loupe Web portal has been visited more than 40,000 times by ~3000 unique visitors from 87 countries. An automatic RDF Shape induction method that follows a data-driven approach to induce integrity constraints using data profiling metrics as features. The proposed method achieved an F1 of 98.81% in deriving maximum cardinality constraints, an F1 of 97.30% in deriving minimum cardinality constraints, and an F1 of 95.94% in deriving range constraints. Four methods for automatic quality assessment and repair using RDF Shapes and data profiling metrics. They are motivated by several practical use cases that cover both Linked Data generation process and output and also cover both public and enterprise data. The four methods include (a) a method for detecting inconsistent mappings, (b) a method for detecting and eliminating noisy triples produced by open information extraction tools, (c) a method to repair links in RDF data, and (d) a method to complete type information in Linked Data ...]]> Mon, 14 Feb 2022 19:59:29 GMT /nandana/a-framework-for-linked-data-quality-based-on-data-profiling-and-rdf-shape-induction nandana@slideshare.net(nandana) A Framework for Linked Data Quality based on Data Profiling and RDF Shape Induction nandana Thesis PDF version: https://oa.upm.es/62935/ In the era of digital transformation, where most decision-making and artificial intelligence (AI) applications are becoming data-driven, data is becoming an essential asset. Linked Data, published in structured, machine-readable formats, with explicit semantics using Semantic Web standards, and with links to other data, is even more useful. The Linked (Open) Data cloud is growing with millions of new triples each year. Nevertheless, as we discuss in this thesis, such vast amounts of data bring several new challenges in ensuring the quality of Linked Data. The main goal of this thesis is to propose novel and scalable methods for automatic quality assessment and repair of Linked Data. The motivation for it is to significantly reduce the manual effort required by current quality assessment and repair, and to propose novel methods suitable for large-scale Linked Data sources such as DBpedia or Wikidata. The main hypothesis of this work is that data profiling metrics and automatic RDF Shape induction can be used to develop scalable and automatic quality assessment and repair methods. In this context, the following main contributions are delivered in this thesis: LDQM, a Linked Data Quality Model for representing Linked Data quality in a standard manner and LD Sniffer, a tool based on LDQM for validating accessibility of Linked Data. LDQM contains 15 quality characteristics, 89 base measures, 23 derived measures, and 124 quality indicators. Loupe, a framework for Linked Data profiling that includes the Loupe Extended Dataset Description Model and a suite of Linked Data profiling tools. The model consists of 84 Linked Data profiling metrics useful for quality assessment and repair tasks. Loupe tools have been used to evaluate 26 thousand datasets containing 34 billions of triples and Loupe contributed to the winning system of ISWC Semantic Web Challenge 2017. The Loupe Web portal has been visited more than 40,000 times by ~3000 unique visitors from 87 countries. An automatic RDF Shape induction method that follows a data-driven approach to induce integrity constraints using data profiling metrics as features. The proposed method achieved an F1 of 98.81% in deriving maximum cardinality constraints, an F1 of 97.30% in deriving minimum cardinality constraints, and an F1 of 95.94% in deriving range constraints. Four methods for automatic quality assessment and repair using RDF Shapes and data profiling metrics. They are motivated by several practical use cases that cover both Linked Data generation process and output and also cover both public and enterprise data. The four methods include (a) a method for detecting inconsistent mappings, (b) a method for detecting and eliminating noisy triples produced by open information extraction tools, (c) a method to repair links in RDF data, and (d) a method to complete type information in Linked Data ... <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/thesispresentationjune2020-220214195930-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Thesis PDF version: https://oa.upm.es/62935/ In the era of digital transformation, where most decision-making and artificial intelligence (AI) applications are becoming data-driven, data is becoming an essential asset. Linked Data, published in structured, machine-readable formats, with explicit semantics using Semantic Web standards, and with links to other data, is even more useful. The Linked (Open) Data cloud is growing with millions of new triples each year. Nevertheless, as we discuss in this thesis, such vast amounts of data bring several new challenges in ensuring the quality of Linked Data. The main goal of this thesis is to propose novel and scalable methods for automatic quality assessment and repair of Linked Data. The motivation for it is to significantly reduce the manual effort required by current quality assessment and repair, and to propose novel methods suitable for large-scale Linked Data sources such as DBpedia or Wikidata. The main hypothesis of this work is that data profiling metrics and automatic RDF Shape induction can be used to develop scalable and automatic quality assessment and repair methods. In this context, the following main contributions are delivered in this thesis: LDQM, a Linked Data Quality Model for representing Linked Data quality in a standard manner and LD Sniffer, a tool based on LDQM for validating accessibility of Linked Data. LDQM contains 15 quality characteristics, 89 base measures, 23 derived measures, and 124 quality indicators. Loupe, a framework for Linked Data profiling that includes the Loupe Extended Dataset Description Model and a suite of Linked Data profiling tools. The model consists of 84 Linked Data profiling metrics useful for quality assessment and repair tasks. Loupe tools have been used to evaluate 26 thousand datasets containing 34 billions of triples and Loupe contributed to the winning system of ISWC Semantic Web Challenge 2017. The Loupe Web portal has been visited more than 40,000 times by ~3000 unique visitors from 87 countries. An automatic RDF Shape induction method that follows a data-driven approach to induce integrity constraints using data profiling metrics as features. The proposed method achieved an F1 of 98.81% in deriving maximum cardinality constraints, an F1 of 97.30% in deriving minimum cardinality constraints, and an F1 of 95.94% in deriving range constraints. Four methods for automatic quality assessment and repair using RDF Shapes and data profiling metrics. They are motivated by several practical use cases that cover both Linked Data generation process and output and also cover both public and enterprise data. The four methods include (a) a method for detecting inconsistent mappings, (b) a method for detecting and eliminating noisy triples produced by open information extraction tools, (c) a method to repair links in RDF data, and (d) a method to complete type information in Linked Data ...
A Framework for Linked Data Quality based on Data Profiling and RDF Shape Induction from Nandana Mihindukulasooriya
]]> 148 0 https://cdn.slidesharecdn.com/ss_thumbnails/thesispresentationjune2020-220214195930-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Leveraging Semantic Parsing for 鐃Relation Linking over Knowledge Bases /slideshow/leveraging-semantic-parsing-for-relation-linking-over-knowledge-bases/239096306 iswc2020leveragingsemanticparsingforrelationlinkingoverknowledgebases-201105083223
Presentation of the paper titled "Leveraging Semantic Parsing for Relation Linking over Knowledge Bases" at the ISWC 2020 - Research Track. @inproceedings{mihindu-sling-2020, title = "Leveraging Semantic Parsing for Relation Linking over Knowledge Bases", author = "Mihindukulasooriya, Nandana and Rossiello, Gaetano and Kapanipathi, Pavan and Abdelaziz, Ibrahim and Ravishankar, Srinivas and Yu, Mo and Gliozzo, Alfio and Roukos, Salim and Gray, Alexander", booktitle="The Semantic Web -- ISWC 2020", year="2020", publisher="Springer International Publishing", address="Cham", pages="402--419", url = "https://link.springer.com/chapter/10.1007/978-3-030-62419-4_23", doi = "10.1007/978-3-030-62419-4_23" }]]>
Presentation of the paper titled "Leveraging Semantic Parsing for Relation Linking over Knowledge Bases" at the ISWC 2020 - Research Track. @inproceedings{mihindu-sling-2020, title = "Leveraging Semantic Parsing for Relation Linking over Knowledge Bases", author = "Mihindukulasooriya, Nandana and Rossiello, Gaetano and Kapanipathi, Pavan and Abdelaziz, Ibrahim and Ravishankar, Srinivas and Yu, Mo and Gliozzo, Alfio and Roukos, Salim and Gray, Alexander", booktitle="The Semantic Web -- ISWC 2020", year="2020", publisher="Springer International Publishing", address="Cham", pages="402--419", url = "https://link.springer.com/chapter/10.1007/978-3-030-62419-4_23", doi = "10.1007/978-3-030-62419-4_23" }]]> Thu, 05 Nov 2020 08:32:22 GMT /slideshow/leveraging-semantic-parsing-for-relation-linking-over-knowledge-bases/239096306 nandana@slideshare.net(nandana) Leveraging Semantic Parsing for 鐃Relation Linking over Knowledge Bases nandana Presentation of the paper titled "Leveraging Semantic Parsing for 鐃Relation Linking over Knowledge Bases" at the ISWC 2020 - Research Track. @inproceedings{mihindu-sling-2020, title = "Leveraging Semantic Parsing for Relation Linking over Knowledge Bases", author = "Mihindukulasooriya, Nandana and Rossiello, Gaetano and Kapanipathi, Pavan and Abdelaziz, Ibrahim and Ravishankar, Srinivas and Yu, Mo and Gliozzo, Alfio and Roukos, Salim and Gray, Alexander", booktitle="The Semantic Web -- ISWC 2020", year="2020", publisher="Springer International Publishing", address="Cham", pages="402--419", url = "https://link.springer.com/chapter/10.1007/978-3-030-62419-4_23", doi = "10.1007/978-3-030-62419-4_23" } <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/iswc2020leveragingsemanticparsingforrelationlinkingoverknowledgebases-201105083223-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Presentation of the paper titled &quot;Leveraging Semantic Parsing for 鐃Relation Linking over Knowledge Bases&quot; at the ISWC 2020 - Research Track. @inproceedings{mihindu-sling-2020, title = &quot;Leveraging Semantic Parsing for Relation Linking over Knowledge Bases&quot;, author = &quot;Mihindukulasooriya, Nandana and Rossiello, Gaetano and Kapanipathi, Pavan and Abdelaziz, Ibrahim and Ravishankar, Srinivas and Yu, Mo and Gliozzo, Alfio and Roukos, Salim and Gray, Alexander&quot;, booktitle=&quot;The Semantic Web -- ISWC 2020&quot;, year=&quot;2020&quot;, publisher=&quot;Springer International Publishing&quot;, address=&quot;Cham&quot;, pages=&quot;402--419&quot;, url = &quot;https://link.springer.com/chapter/10.1007/978-3-030-62419-4_23&quot;, doi = &quot;10.1007/978-3-030-62419-4_23&quot; }
Leveraging Semantic Parsing for Relation Linking over Knowledge Bases from Nandana Mihindukulasooriya
]]> 129 0 https://cdn.slidesharecdn.com/ss_thumbnails/iswc2020leveragingsemanticparsingforrelationlinkingoverknowledgebases-201105083223-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 ISWC 2020 - Semantic Answer Type Prediction /slideshow/iswc-2020-semantic-answer-type-prediction/237290622 semanticanswertypeprediction-200727151536
ISWC 2020 Challenge on Semantic Answer Type Prediction. Presented at the DBpedia Workshop at LDAC 2020, June 19.]]>
ISWC 2020 Challenge on Semantic Answer Type Prediction. Presented at the DBpedia Workshop at LDAC 2020, June 19.]]> Mon, 27 Jul 2020 15:15:36 GMT /slideshow/iswc-2020-semantic-answer-type-prediction/237290622 nandana@slideshare.net(nandana) ISWC 2020 - Semantic Answer Type Prediction nandana ISWC 2020 Challenge on Semantic Answer Type Prediction. Presented at the DBpedia Workshop at LDAC 2020, June 19. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/semanticanswertypeprediction-200727151536-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> ISWC 2020 Challenge on Semantic Answer Type Prediction. Presented at the DBpedia Workshop at LDAC 2020, June 19.
ISWC 2020 - Semantic Answer Type Prediction from Nandana Mihindukulasooriya
]]> 98 0 https://cdn.slidesharecdn.com/ss_thumbnails/semanticanswertypeprediction-200727151536-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Fitur - HackaTrips 2018! https://es.slideshare.net/slideshow/fitur-hackatrips-2018/86695444 grupa-equipo18-180125154220
The group presentation of HackaTrips!]]>
The group presentation of HackaTrips!]]> Thu, 25 Jan 2018 15:42:20 GMT https://es.slideshare.net/slideshow/fitur-hackatrips-2018/86695444 nandana@slideshare.net(nandana) Fitur - HackaTrips 2018! nandana The group presentation of HackaTrips! <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/grupa-equipo18-180125154220-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> The group presentation of HackaTrips!
from Nandana Mihindukulasooriya
]]> 781 3 https://cdn.slidesharecdn.com/ss_thumbnails/grupa-equipo18-180125154220-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 A Distributed Transaction Model for Read-Write Linked Data Applications /slideshow/a-distributed-transaction-model-for-readwrite-linked-data-applications/84232687 icwe2015phd-171216134357
Mihindukulasooriya, Nandana, Ra炭l Garc鱈a-Castro, and Asunci坦n G坦mez-P辿rez. "A Distributed Transaction Model for Read-Write Linked Data Applications." In International Conference on Web Engineering, pp. 631-634. Springer International Publishing, 2015.]]>
Mihindukulasooriya, Nandana, Ra炭l Garc鱈a-Castro, and Asunci坦n G坦mez-P辿rez. "A Distributed Transaction Model for Read-Write Linked Data Applications." In International Conference on Web Engineering, pp. 631-634. Springer International Publishing, 2015.]]> Sat, 16 Dec 2017 13:43:57 GMT /slideshow/a-distributed-transaction-model-for-readwrite-linked-data-applications/84232687 nandana@slideshare.net(nandana) A Distributed Transaction Model for Read-Write Linked Data Applications nandana Mihindukulasooriya, Nandana, Ra炭l Garc鱈a-Castro, and Asunci坦n G坦mez-P辿rez. "A Distributed Transaction Model for Read-Write Linked Data Applications." In International Conference on Web Engineering, pp. 631-634. Springer International Publishing, 2015. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/icwe2015phd-171216134357-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Mihindukulasooriya, Nandana, Ra炭l Garc鱈a-Castro, and Asunci坦n G坦mez-P辿rez. &quot;A Distributed Transaction Model for Read-Write Linked Data Applications.&quot; In International Conference on Web Engineering, pp. 631-634. Springer International Publishing, 2015.
A Distributed Transaction Model for Read-Write Linked Data Applications from Nandana Mihindukulasooriya
]]> 145 4 https://cdn.slidesharecdn.com/ss_thumbnails/icwe2015phd-171216134357-thumbnail.jpg?width=120&height=120&fit=bounds document Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Repairing Hidden Links in Linked Data /slideshow/repairing-hidden-links-in-linked-data/83424885 kcap2017-version1-171205192825
Knowledge Graphs (KG) are becoming core components of most artificial intelligence applications. Linked Data, as a method of publishing KGs, allows applications to traverse within, and even out of, the graph thanks to global dereferenceable identifiers denoting entities, in the form of IRIs. However, as we show in this work, after analyzing several popular datasets (namely DBpedia, LOD Cache, and Web Data Commons JSON-LD data) many entities are being represented using literal strings where IRIs should be used, diminishing the advantages of using Linked Data. To remedy this, we propose an approach for identifying such strings and replacing them with their corresponding entity IRIs. The proposed approach is based on identifying relations between entities based on both ontological axioms as well as data profiling information and converting strings to entity IRIs based on the types of entities linked by each relation. Our approach showed 98\% recall and 76\% precision in identifying such strings and 97\% precision in converting them to their corresponding IRI in the considered KG. Further, we analyzed how the connectivity of the KG is increased when new relevant links are added to the entities as a result of our method. Our experiments on a subset of the Spanish DBpedia data show that it could add 25% more links to the KG and improve the overall connectivity by 17%.]]>
Knowledge Graphs (KG) are becoming core components of most artificial intelligence applications. Linked Data, as a method of publishing KGs, allows applications to traverse within, and even out of, the graph thanks to global dereferenceable identifiers denoting entities, in the form of IRIs. However, as we show in this work, after analyzing several popular datasets (namely DBpedia, LOD Cache, and Web Data Commons JSON-LD data) many entities are being represented using literal strings where IRIs should be used, diminishing the advantages of using Linked Data. To remedy this, we propose an approach for identifying such strings and replacing them with their corresponding entity IRIs. The proposed approach is based on identifying relations between entities based on both ontological axioms as well as data profiling information and converting strings to entity IRIs based on the types of entities linked by each relation. Our approach showed 98\% recall and 76\% precision in identifying such strings and 97\% precision in converting them to their corresponding IRI in the considered KG. Further, we analyzed how the connectivity of the KG is increased when new relevant links are added to the entities as a result of our method. Our experiments on a subset of the Spanish DBpedia data show that it could add 25% more links to the KG and improve the overall connectivity by 17%.]]> Tue, 05 Dec 2017 19:28:25 GMT /slideshow/repairing-hidden-links-in-linked-data/83424885 nandana@slideshare.net(nandana) Repairing Hidden Links in Linked Data nandana Knowledge Graphs (KG) are becoming core components of most artificial intelligence applications. Linked Data, as a method of publishing KGs, allows applications to traverse within, and even out of, the graph thanks to global dereferenceable identifiers denoting entities, in the form of IRIs. However, as we show in this work, after analyzing several popular datasets (namely DBpedia, LOD Cache, and Web Data Commons JSON-LD data) many entities are being represented using literal strings where IRIs should be used, diminishing the advantages of using Linked Data. To remedy this, we propose an approach for identifying such strings and replacing them with their corresponding entity IRIs. The proposed approach is based on identifying relations between entities based on both ontological axioms as well as data profiling information and converting strings to entity IRIs based on the types of entities linked by each relation. Our approach showed 98\% recall and 76\% precision in identifying such strings and 97\% precision in converting them to their corresponding IRI in the considered KG. Further, we analyzed how the connectivity of the KG is increased when new relevant links are added to the entities as a result of our method. Our experiments on a subset of the Spanish DBpedia data show that it could add 25% more links to the KG and improve the overall connectivity by 17%. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/kcap2017-version1-171205192825-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Knowledge Graphs (KG) are becoming core components of most artificial intelligence applications. Linked Data, as a method of publishing KGs, allows applications to traverse within, and even out of, the graph thanks to global dereferenceable identifiers denoting entities, in the form of IRIs. However, as we show in this work, after analyzing several popular datasets (namely DBpedia, LOD Cache, and Web Data Commons JSON-LD data) many entities are being represented using literal strings where IRIs should be used, diminishing the advantages of using Linked Data. To remedy this, we propose an approach for identifying such strings and replacing them with their corresponding entity IRIs. The proposed approach is based on identifying relations between entities based on both ontological axioms as well as data profiling information and converting strings to entity IRIs based on the types of entities linked by each relation. Our approach showed 98\% recall and 76\% precision in identifying such strings and 97\% precision in converting them to their corresponding IRI in the considered KG. Further, we analyzed how the connectivity of the KG is increased when new relevant links are added to the entities as a result of our method. Our experiments on a subset of the Spanish DBpedia data show that it could add 25% more links to the KG and improve the overall connectivity by 17%.
Repairing Hidden Links in Linked Data from Nandana Mihindukulasooriya
]]> 396 7 https://cdn.slidesharecdn.com/ss_thumbnails/kcap2017-version1-171205192825-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Loupe API - A Linked Data Profiling Service for Quality Assessment /slideshow/loupe-api-ldq-2017/76599363 loup-api-ldq-2017-170602175820
Loupe API - A Linked Data Profiling Service for Quality Assessment Nandana Mihindukulasooriya, Ra炭l Garc鱈a-Castro, Freddy Priyatna, Edna Ruckhaus and Nelson Saturno. "Loupe API - A Linked Data Profiling Service for Quality Assessment". In the proceedings of the 4th Workshop on Linked Data Quality (LDQ2017). Monday, 29th of May 2017. Portoro転, Slovenia. co-located with the the 14th Extended Semantic Web Conference (ESWC 2017). ]]>
Loupe API - A Linked Data Profiling Service for Quality Assessment Nandana Mihindukulasooriya, Ra炭l Garc鱈a-Castro, Freddy Priyatna, Edna Ruckhaus and Nelson Saturno. "Loupe API - A Linked Data Profiling Service for Quality Assessment". In the proceedings of the 4th Workshop on Linked Data Quality (LDQ2017). Monday, 29th of May 2017. Portoro転, Slovenia. co-located with the the 14th Extended Semantic Web Conference (ESWC 2017). ]]> Fri, 02 Jun 2017 17:58:19 GMT /slideshow/loupe-api-ldq-2017/76599363 nandana@slideshare.net(nandana) Loupe API - A Linked Data Profiling Service for Quality Assessment nandana Loupe API - A Linked Data Profiling Service for Quality Assessment Nandana Mihindukulasooriya, Ra炭l Garc鱈a-Castro, Freddy Priyatna, Edna Ruckhaus and Nelson Saturno. "Loupe API - A Linked Data Profiling Service for Quality Assessment". In the proceedings of the 4th Workshop on Linked Data Quality (LDQ2017). Monday, 29th of May 2017. Portoro転, Slovenia. co-located with the the 14th Extended Semantic Web Conference (ESWC 2017). <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/loup-api-ldq-2017-170602175820-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Loupe API - A Linked Data Profiling Service for Quality Assessment Nandana Mihindukulasooriya, Ra炭l Garc鱈a-Castro, Freddy Priyatna, Edna Ruckhaus and Nelson Saturno. &quot;Loupe API - A Linked Data Profiling Service for Quality Assessment&quot;. In the proceedings of the 4th Workshop on Linked Data Quality (LDQ2017). Monday, 29th of May 2017. Portoro転, Slovenia. co-located with the the 14th Extended Semantic Web Conference (ESWC 2017).
Loupe API - A Linked Data Profiling Service for Quality Assessment from Nandana Mihindukulasooriya
]]> 248 3 https://cdn.slidesharecdn.com/ss_thumbnails/loup-api-ldq-2017-170602175820-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Research Poster Design /slideshow/research-poster-design-73629108/73629108 researchposterdesign-170325094802
A presentation on how to prepare and present an effective research paper based on a summary of the paper by the paper Preparing and Presenting Effective Research Poster by Jane E. Miller in Health Services Research journal.]]>
A presentation on how to prepare and present an effective research paper based on a summary of the paper by the paper Preparing and Presenting Effective Research Poster by Jane E. Miller in Health Services Research journal.]]> Sat, 25 Mar 2017 09:48:02 GMT /slideshow/research-poster-design-73629108/73629108 nandana@slideshare.net(nandana) Research Poster Design nandana A presentation on how to prepare and present an effective research paper based on a summary of the paper by the paper Preparing and Presenting Effective Research Poster by Jane E. Miller in Health Services Research journal. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/researchposterdesign-170325094802-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> A presentation on how to prepare and present an effective research paper based on a summary of the paper by the paper Preparing and Presenting Effective Research Poster by Jane E. Miller in Health Services Research journal.
Research Poster Design from Nandana Mihindukulasooriya
]]> 488 6 https://cdn.slidesharecdn.com/ss_thumbnails/researchposterdesign-170325094802-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Hidden Gems https://es.slideshare.net/slideshow/hidden-gems-71267468/71267468 hiddengems-170122200738
A small application bring tourism into charming hidden villages to increase the income of small local communities and empower responsible tourism. ]]>
A small application bring tourism into charming hidden villages to increase the income of small local communities and empower responsible tourism. ]]> Sun, 22 Jan 2017 20:07:38 GMT https://es.slideshare.net/slideshow/hidden-gems-71267468/71267468 nandana@slideshare.net(nandana) Hidden Gems nandana A small application bring tourism into charming hidden villages to increase the income of small local communities and empower responsible tourism. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/hiddengems-170122200738-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> A small application bring tourism into charming hidden villages to increase the income of small local communities and empower responsible tourism.
from Nandana Mihindukulasooriya
]]> 416 4 https://cdn.slidesharecdn.com/ss_thumbnails/hiddengems-170122200738-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Collaborative Ontology Evolution and Data Quality - An Empirical Analysis /nandana/ontology-changes-and-data-quality-69457509 ontologychangesanddataquality-161123141620
Since more than a decade, theoretical research on ontology evolution has been published in literature and frameworks for managing ontology changes have been developed. However, there are less studies that analyze widely used ontologies developed in a collaborative manner to understand community-driven ontology evolution in practice. We performed an empirical analysis on how four well-known ontologies (DBpedia, Schema.org, PROV-O, and FOAF) have evolved through their lifetime and an analysis of the data quality issues caused by some of the ontology changes. ]]>
Since more than a decade, theoretical research on ontology evolution has been published in literature and frameworks for managing ontology changes have been developed. However, there are less studies that analyze widely used ontologies developed in a collaborative manner to understand community-driven ontology evolution in practice. We performed an empirical analysis on how four well-known ontologies (DBpedia, Schema.org, PROV-O, and FOAF) have evolved through their lifetime and an analysis of the data quality issues caused by some of the ontology changes. ]]> Wed, 23 Nov 2016 14:16:20 GMT /nandana/ontology-changes-and-data-quality-69457509 nandana@slideshare.net(nandana) Collaborative Ontology Evolution and Data Quality - An Empirical Analysis nandana Since more than a decade, theoretical research on ontology evolution has been published in literature and frameworks for managing ontology changes have been developed. However, there are less studies that analyze widely used ontologies developed in a collaborative manner to understand community-driven ontology evolution in practice. We performed an empirical analysis on how four well-known ontologies (DBpedia, Schema.org, PROV-O, and FOAF) have evolved through their lifetime and an analysis of the data quality issues caused by some of the ontology changes. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/ontologychangesanddataquality-161123141620-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Since more than a decade, theoretical research on ontology evolution has been published in literature and frameworks for managing ontology changes have been developed. However, there are less studies that analyze widely used ontologies developed in a collaborative manner to understand community-driven ontology evolution in practice. We performed an empirical analysis on how four well-known ontologies (DBpedia, Schema.org, PROV-O, and FOAF) have evolved through their lifetime and an analysis of the data quality issues caused by some of the ontology changes.
Collaborative Ontology Evolution and Data Quality - An Empirical Analysis from Nandana Mihindukulasooriya
]]> 853 5 https://cdn.slidesharecdn.com/ss_thumbnails/ontologychangesanddataquality-161123141620-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Erasmus+ promotional event - Kandy, Sri Lanka /slideshow/erasmus-plus-promotion-kandy/65406363 erasmuspluspromotionkandy-160826204429
Erasmus plus promotion kandy]]>
Erasmus plus promotion kandy]]> Fri, 26 Aug 2016 20:44:29 GMT /slideshow/erasmus-plus-promotion-kandy/65406363 nandana@slideshare.net(nandana) Erasmus+ promotional event - Kandy, Sri Lanka nandana Erasmus plus promotion kandy <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/erasmuspluspromotionkandy-160826204429-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Erasmus plus promotion kandy
Erasmus+ promotional event - Kandy, Sri Lanka from Nandana Mihindukulasooriya
]]> 333 5 https://cdn.slidesharecdn.com/ss_thumbnails/erasmuspluspromotionkandy-160826204429-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Loupe model - Use Cases and Requirements /slideshow/loupe-model-use-cases-and-requirements/64110771 loupemodel-160718054548
Loupe model - Use Cases and Requirements ]]>
Loupe model - Use Cases and Requirements ]]> Mon, 18 Jul 2016 05:45:48 GMT /slideshow/loupe-model-use-cases-and-requirements/64110771 nandana@slideshare.net(nandana) Loupe model - Use Cases and Requirements nandana Loupe model - Use Cases and Requirements <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/loupemodel-160718054548-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Loupe model - Use Cases and Requirements
Loupe model - Use Cases and Requirements from Nandana Mihindukulasooriya
]]> 351 4 https://cdn.slidesharecdn.com/ss_thumbnails/loupemodel-160718054548-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 4V - WP3 Progress Report (TIN2013-46238) /slideshow/4v-zaragoza/63982536 4v-zaragozq-160713103630
The slides presented in the F2F meeting of the 4V project on 15th of June, 2015 at Zaragoza.]]>
The slides presented in the F2F meeting of the 4V project on 15th of June, 2015 at Zaragoza.]]> Wed, 13 Jul 2016 10:36:30 GMT /slideshow/4v-zaragoza/63982536 nandana@slideshare.net(nandana) 4V - WP3 Progress Report (TIN2013-46238) nandana The slides presented in the F2F meeting of the 4V project on 15th of June, 2015 at Zaragoza. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/4v-zaragozq-160713103630-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> The slides presented in the F2F meeting of the 4V project on 15th of June, 2015 at Zaragoza.
4V - WP3 Progress Report (TIN2013-46238) from Nandana Mihindukulasooriya
]]> 310 1 https://cdn.slidesharecdn.com/ss_thumbnails/4v-zaragozq-160713103630-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Introduction to W3C Linked Data Platform /slideshow/ldac2016/63326408 ldac2016-160622084931
A set of slides that provides a high-level overview of the W3C Linked Data Platform specification presented at the 4th Linked Data in Architecture and Construction Workshop. For more detailed and technical version of the presentation, please refer to http://www.slideshare.net/nandana/learning-w3c-linked-data-platform-with-examples LDAC 2016 programme http://smartcity.linkeddata.es/LDAC2016/#programme]]>
A set of slides that provides a high-level overview of the W3C Linked Data Platform specification presented at the 4th Linked Data in Architecture and Construction Workshop. For more detailed and technical version of the presentation, please refer to http://www.slideshare.net/nandana/learning-w3c-linked-data-platform-with-examples LDAC 2016 programme http://smartcity.linkeddata.es/LDAC2016/#programme]]> Wed, 22 Jun 2016 08:49:31 GMT /slideshow/ldac2016/63326408 nandana@slideshare.net(nandana) Introduction to W3C Linked Data Platform nandana A set of slides that provides a high-level overview of the W3C Linked Data Platform specification presented at the 4th Linked Data in Architecture and Construction Workshop. For more detailed and technical version of the presentation, please refer to http://www.slideshare.net/nandana/learning-w3c-linked-data-platform-with-examples LDAC 2016 programme http://smartcity.linkeddata.es/LDAC2016/#programme <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/ldac2016-160622084931-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> A set of slides that provides a high-level overview of the W3C Linked Data Platform specification presented at the 4th Linked Data in Architecture and Construction Workshop. For more detailed and technical version of the presentation, please refer to http://www.slideshare.net/nandana/learning-w3c-linked-data-platform-with-examples LDAC 2016 programme http://smartcity.linkeddata.es/LDAC2016/#programme
Introduction to W3C Linked Data Platform from Nandana Mihindukulasooriya
]]> 1609 6 https://cdn.slidesharecdn.com/ss_thumbnails/ldac2016-160622084931-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 A Two-Fold Quality Assurance Approach for Dynamic Knowledge Bases : The 3cixty Use Case /slideshow/a-twofold-quality-assurance-approach-for-dynamic-knowledge-bases-the-3cixty-use-case/62524443 3cixty-a-two-fold-quality-assurance-approach-for-dynamic-knowledge-bases-160530051813
The presentation for the paper "A Two-Fold Quality Assurance Approach for Dynamic Knowledge Bases : The 3cixty Use Case" presented at the 1st International Workshop on Completing and Debugging the Semantic Web at the 13th Extended Semantic Web Conference.]]>
The presentation for the paper "A Two-Fold Quality Assurance Approach for Dynamic Knowledge Bases : The 3cixty Use Case" presented at the 1st International Workshop on Completing and Debugging the Semantic Web at the 13th Extended Semantic Web Conference.]]> Mon, 30 May 2016 05:18:13 GMT /slideshow/a-twofold-quality-assurance-approach-for-dynamic-knowledge-bases-the-3cixty-use-case/62524443 nandana@slideshare.net(nandana) A Two-Fold Quality Assurance Approach for Dynamic Knowledge Bases : The 3cixty Use Case nandana The presentation for the paper "A Two-Fold Quality Assurance Approach for Dynamic Knowledge Bases : The 3cixty Use Case" presented at the 1st International Workshop on Completing and Debugging the Semantic Web at the 13th Extended Semantic Web Conference. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/3cixty-a-two-fold-quality-assurance-approach-for-dynamic-knowledge-bases-160530051813-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> The presentation for the paper &quot;A Two-Fold Quality Assurance Approach for Dynamic Knowledge Bases : The 3cixty Use Case&quot; presented at the 1st International Workshop on Completing and Debugging the Semantic Web at the 13th Extended Semantic Web Conference.
A Two-Fold Quality Assurance Approach for Dynamic Knowledge Bases : The 3cixty Use Case from Nandana Mihindukulasooriya
]]> 802 7 https://cdn.slidesharecdn.com/ss_thumbnails/3cixty-a-two-fold-quality-assurance-approach-for-dynamic-knowledge-bases-160530051813-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 An analysis of the quality issues of the properties available in the Spanish DBpedia /slideshow/an-analysis-of-the-quality-issues-of-the-properties-available-in-the-spanish-dbpedia/55040212 spanishdbpediaqualityanalysis-151112141321-lva1-app6891
DBpedia exposes data from Wikipedia as machine-readable Linked Data. The DBpedia data extraction process generates RDF data in two ways; (a) using the mappings that map the data from Wikipedia infoboxes to the DBpedia ontology and other vocabularies, and (b) using infobox-properties, i.e., properties that are not defined in the DBpedia ontology but are auto-generated using the infobox attribute-value pairs. The work presented in this paper inspects the quality issues of the properties used in the Spanish DBpedia dataset according to conciseness, consistency, syntactic validity, and semantic accuracy quality dimensions.]]>
DBpedia exposes data from Wikipedia as machine-readable Linked Data. The DBpedia data extraction process generates RDF data in two ways; (a) using the mappings that map the data from Wikipedia infoboxes to the DBpedia ontology and other vocabularies, and (b) using infobox-properties, i.e., properties that are not defined in the DBpedia ontology but are auto-generated using the infobox attribute-value pairs. The work presented in this paper inspects the quality issues of the properties used in the Spanish DBpedia dataset according to conciseness, consistency, syntactic validity, and semantic accuracy quality dimensions.]]> Thu, 12 Nov 2015 14:13:21 GMT /slideshow/an-analysis-of-the-quality-issues-of-the-properties-available-in-the-spanish-dbpedia/55040212 nandana@slideshare.net(nandana) An analysis of the quality issues of the properties available in the Spanish DBpedia nandana DBpedia exposes data from Wikipedia as machine-readable Linked Data. The DBpedia data extraction process generates RDF data in two ways; (a) using the mappings that map the data from Wikipedia infoboxes to the DBpedia ontology and other vocabularies, and (b) using infobox-properties, i.e., properties that are not defined in the DBpedia ontology but are auto-generated using the infobox attribute-value pairs. The work presented in this paper inspects the quality issues of the properties used in the Spanish DBpedia dataset according to conciseness, consistency, syntactic validity, and semantic accuracy quality dimensions. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/spanishdbpediaqualityanalysis-151112141321-lva1-app6891-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> DBpedia exposes data from Wikipedia as machine-readable Linked Data. The DBpedia data extraction process generates RDF data in two ways; (a) using the mappings that map the data from Wikipedia infoboxes to the DBpedia ontology and other vocabularies, and (b) using infobox-properties, i.e., properties that are not defined in the DBpedia ontology but are auto-generated using the infobox attribute-value pairs. The work presented in this paper inspects the quality issues of the properties used in the Spanish DBpedia dataset according to conciseness, consistency, syntactic validity, and semantic accuracy quality dimensions.
An analysis of the quality issues of the properties available in the Spanish DBpedia from Nandana Mihindukulasooriya
]]> 426 7 https://cdn.slidesharecdn.com/ss_thumbnails/spanishdbpediaqualityanalysis-151112141321-lva1-app6891-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Describing LDP Applications 鐃with the Hydra Core Vocabulary /slideshow/describing-ldp-applications-with-the-hydra-core-vocabulary/48844975 ldp-hydra-api-salad2015-150601143936-lva1-app6892
Describing LDP Applications with the Hydra Core Vocabulary]]>
Describing LDP Applications with the Hydra Core Vocabulary]]> Mon, 01 Jun 2015 14:39:36 GMT /slideshow/describing-ldp-applications-with-the-hydra-core-vocabulary/48844975 nandana@slideshare.net(nandana) Describing LDP Applications 鐃with the Hydra Core Vocabulary nandana Describing LDP Applications 鐃with the Hydra Core Vocabulary <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/ldp-hydra-api-salad2015-150601143936-lva1-app6892-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Describing LDP Applications 鐃with the Hydra Core Vocabulary
Describing LDP Applications with the Hydra Core Vocabulary from Nandana Mihindukulasooriya
]]> 3229 7 https://cdn.slidesharecdn.com/ss_thumbnails/ldp-hydra-api-salad2015-150601143936-lva1-app6892-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Learning W3C Linked Data Platform with examples /slideshow/learning-w3c-linked-data-platform-with-examples/41131600 learningw3clinkeddataplatformwithexamples-141104191116-conversion-gate02
The W3C Linked Data Platform (LDP) specification describes a set of best practices and simple approach for a read-write Linked Data architecture, based on HTTP access to web resources that describe their state using the RDF data model. This presentation provides a set of simple examples that illustrates how an LDP client can interact with an LDP server in the context of a read-write Linked Data application i.e. how to use the LDP protocol for retrieving, updating, creating and deleting Linked Data resources.]]>
The W3C Linked Data Platform (LDP) specification describes a set of best practices and simple approach for a read-write Linked Data architecture, based on HTTP access to web resources that describe their state using the RDF data model. This presentation provides a set of simple examples that illustrates how an LDP client can interact with an LDP server in the context of a read-write Linked Data application i.e. how to use the LDP protocol for retrieving, updating, creating and deleting Linked Data resources.]]> Tue, 04 Nov 2014 19:11:16 GMT /slideshow/learning-w3c-linked-data-platform-with-examples/41131600 nandana@slideshare.net(nandana) Learning W3C Linked Data Platform with examples nandana The W3C Linked Data Platform (LDP) specification describes a set of best practices and simple approach for a read-write Linked Data architecture, based on HTTP access to web resources that describe their state using the RDF data model. This presentation provides a set of simple examples that illustrates how an LDP client can interact with an LDP server in the context of a read-write Linked Data application i.e. how to use the LDP protocol for retrieving, updating, creating and deleting Linked Data resources. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/learningw3clinkeddataplatformwithexamples-141104191116-conversion-gate02-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> The W3C Linked Data Platform (LDP) specification describes a set of best practices and simple approach for a read-write Linked Data architecture, based on HTTP access to web resources that describe their state using the RDF data model. This presentation provides a set of simple examples that illustrates how an LDP client can interact with an LDP server in the context of a read-write Linked Data application i.e. how to use the LDP protocol for retrieving, updating, creating and deleting Linked Data resources.
Learning W3C Linked Data Platform with examples from Nandana Mihindukulasooriya
]]> 7117 4 https://cdn.slidesharecdn.com/ss_thumbnails/learningw3clinkeddataplatformwithexamples-141104191116-conversion-gate02-thumbnail.jpg?width=120&height=120&fit=bounds presentation White http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Linked data platform adapter for bugzilla poster /slideshow/linked-data-platform-adapter-for-bugzill-poster/40964712 linkeddataplatformadapterforbugzillposter-141031090516-conversion-gate02
The W3C Linked Data Platform (LDP) specification defines a standard HTTP-based protocol for read/write Linked Data and provides the basis for application integration using Linked Data. This poster presents an LDP adapter for the Bugzilla issue tracker and demonstrates how to use the LDP protocol to expose a traditional application as a read/write Linked Data application. This approach provides a flexible LDP adoption strategy with minimal changes to existing applications.]]>
The W3C Linked Data Platform (LDP) specification defines a standard HTTP-based protocol for read/write Linked Data and provides the basis for application integration using Linked Data. This poster presents an LDP adapter for the Bugzilla issue tracker and demonstrates how to use the LDP protocol to expose a traditional application as a read/write Linked Data application. This approach provides a flexible LDP adoption strategy with minimal changes to existing applications.]]> Fri, 31 Oct 2014 09:05:16 GMT /slideshow/linked-data-platform-adapter-for-bugzill-poster/40964712 nandana@slideshare.net(nandana) Linked data platform adapter for bugzilla poster nandana The W3C Linked Data Platform (LDP) specification defines a standard HTTP-based protocol for read/write Linked Data and provides the basis for application integration using Linked Data. This poster presents an LDP adapter for the Bugzilla issue tracker and demonstrates how to use the LDP protocol to expose a traditional application as a read/write Linked Data application. This approach provides a flexible LDP adoption strategy with minimal changes to existing applications. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/linkeddataplatformadapterforbugzillposter-141031090516-conversion-gate02-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> The W3C Linked Data Platform (LDP) specification defines a standard HTTP-based protocol for read/write Linked Data and provides the basis for application integration using Linked Data. This poster presents an LDP adapter for the Bugzilla issue tracker and demonstrates how to use the LDP protocol to expose a traditional application as a read/write Linked Data application. This approach provides a flexible LDP adoption strategy with minimal changes to existing applications.
Linked data platform adapter for bugzilla poster from Nandana Mihindukulasooriya
]]> 606 2 https://cdn.slidesharecdn.com/ss_thumbnails/linkeddataplatformadapterforbugzillposter-141031090516-conversion-gate02-thumbnail.jpg?width=120&height=120&fit=bounds document White http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 LDP4j: A framework for the development of interoperable 鐃read-write Linked Data applications /slideshow/ldp4j-a-framework-for-the-development-of-interoperable-readwrite-linked-data-applications/40533758 ldp4j-iswc-141021051002-conversion-gate01
This presentation introduces LDP4j, an open source Java-based framework for the development of read-write Linked Data applications based on the W3C Linked Data Platform 1.0 (LDP) specification and available under the Apache 2.0 license. This was presented in the ISWC 2014 Developer Woskshop. http://www.ldp4j.org/]]>
This presentation introduces LDP4j, an open source Java-based framework for the development of read-write Linked Data applications based on the W3C Linked Data Platform 1.0 (LDP) specification and available under the Apache 2.0 license. This was presented in the ISWC 2014 Developer Woskshop. http://www.ldp4j.org/]]> Tue, 21 Oct 2014 05:10:02 GMT /slideshow/ldp4j-a-framework-for-the-development-of-interoperable-readwrite-linked-data-applications/40533758 nandana@slideshare.net(nandana) LDP4j: A framework for the development of interoperable 鐃read-write Linked Data applications nandana This presentation introduces LDP4j, an open source Java-based framework for the development of read-write Linked Data applications based on the W3C Linked Data Platform 1.0 (LDP) specification and available under the Apache 2.0 license. This was presented in the ISWC 2014 Developer Woskshop. http://www.ldp4j.org/ <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/ldp4j-iswc-141021051002-conversion-gate01-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> This presentation introduces LDP4j, an open source Java-based framework for the development of read-write Linked Data applications based on the W3C Linked Data Platform 1.0 (LDP) specification and available under the Apache 2.0 license. This was presented in the ISWC 2014 Developer Woskshop. http://www.ldp4j.org/
LDP4j: A framework for the development of interoperable read-write Linked Data applications from Nandana Mihindukulasooriya
]]> 1705 1 https://cdn.slidesharecdn.com/ss_thumbnails/ldp4j-iswc-141021051002-conversion-gate01-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 https://cdn.slidesharecdn.com/profile-photo-nandana-48x48.jpg?cb=1703767062 Specialties: Semantic Web, Linked Data, Java, Web Services, Service Oriented Architectures, Security Research Interests: Quality assessment and repair of Linked Data Read-write Linked Data applications Enterprise Application Integration with Linked Data Machine Learning Technologies : Java, J2EE, C RDF(S), OWL, SPARQL UML, SQL, XML, XSD, XSLT, SOAP, REST, WSDL, BPEL, WS-*, WS-Sec* OSGi, JAX-WS, JAX-RS, JAXB, JAXP Frameworks : Spring, Hibernate, Struts 2 JUnit, EasyMock, Selenium Apache Tomcat, JBoss, IBM WebSphere Application Server Apache Axis2, Synapse, ODE WSO2 AS, ESB, IdentityServer, Apache CXF, ServiceMix, Camel, Fuse ESB Apache Jena, Sesame Tools : Eclipse, IntelliJ IDE... nandana.org https://cdn.slidesharecdn.com/ss_thumbnails/thesispresentationjune2020-220214195930-thumbnail.jpg?width=320&height=320&fit=bounds nandana/a-framework-for-linked-data-quality-based-on-data-profiling-and-rdf-shape-induction A Framework for Linked... https://cdn.slidesharecdn.com/ss_thumbnails/iswc2020leveragingsemanticparsingforrelationlinkingoverknowledgebases-201105083223-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/leveraging-semantic-parsing-for-relation-linking-over-knowledge-bases/239096306 Leveraging Semantic Pa... https://cdn.slidesharecdn.com/ss_thumbnails/semanticanswertypeprediction-200727151536-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/iswc-2020-semantic-answer-type-prediction/237290622 ISWC 2020 - Semantic A...