The Linked Open Vocabularies (LOV) curated directory list of vocabularies has changed radically the way that engineers are assisted to explore the vocabulary space by searching for terms and vocabularies using the provided keyword based search. Running a survey regarding the decision of the vocabulary terms that can be used to annotate a specific webpage, we realised the gap between the vocabulary creators side and the vocabulary users. In this direction, the presented framework, namely the LOVR framework, aims to facilitate the vocabulary terms discovery by providing a Web service with a set of endpoints that can be invoked to get a list of recommended terms for a given webpage. Within this work, we present the framework architecture and the fundamental parts of the prototype that implements the methodology behind the LOVR framework, which leverages the LOV search. Furthermore, the various endpoints of the Web service are described by explaining their usage scenarios.
{"title":"Towards a Vocabulary Terms Discovery Assistant","authors":"Ioannis Stavrakantonakis, A. Fensel, D. Fensel","doi":"10.1145/2993318.2993347","DOIUrl":"https://doi.org/10.1145/2993318.2993347","url":null,"abstract":"The Linked Open Vocabularies (LOV) curated directory list of vocabularies has changed radically the way that engineers are assisted to explore the vocabulary space by searching for terms and vocabularies using the provided keyword based search. Running a survey regarding the decision of the vocabulary terms that can be used to annotate a specific webpage, we realised the gap between the vocabulary creators side and the vocabulary users. In this direction, the presented framework, namely the LOVR framework, aims to facilitate the vocabulary terms discovery by providing a Web service with a set of endpoints that can be invoked to get a list of recommended terms for a given webpage. Within this work, we present the framework architecture and the fundamental parts of the prototype that implements the methodology behind the LOVR framework, which leverages the LOV search. Furthermore, the various endpoints of the Web service are described by explaining their usage scenarios.","PeriodicalId":177013,"journal":{"name":"Proceedings of the 12th International Conference on Semantic Systems","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129213939","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Diego Esteves, Pablo N. Mendes, Diego Moussallem, J. C. Duarte, A. Zaveri, Jens Lehmann
Despite recent efforts to achieve a high level of interoperability of Machine Learning (ML) experiments, positively collaborating with the Reproducible Research context, we still run into problems created due to the existence of different ML platforms: each of those have a specific conceptualization or schema for representing data and metadata. This scenario leads to an extra coding-effort to achieve both the desired interoperability and a better provenance level as well as a more automatized environment for obtaining the generated results. Hence, when using ML libraries, it is a common task to re-design specific data models (schemata) and develop wrappers to manage the produced outputs. In this article, we discuss this gap focusing on the solution for the question: "What is the cleanest and lowest-impact solution, i.e., the minimal effort to achieve both higher interoperability and provenance metadata levels in the Integrated Development Environments (IDE) context and how to facilitate the inherent data querying task?". We introduce a novel and low-impact methodology specifically designed for code built in that context, combining Semantic Web concepts and reflection in order to minimize the gap for exporting ML metadata in a structured manner, allowing embedded code annotations that are, in run-time, converted in one of the state-of-the-art ML schemas for the Semantic Web: MEX Vocabulary.
{"title":"MEX Interfaces: Automating Machine Learning Metadata Generation","authors":"Diego Esteves, Pablo N. Mendes, Diego Moussallem, J. C. Duarte, A. Zaveri, Jens Lehmann","doi":"10.1145/2993318.2993320","DOIUrl":"https://doi.org/10.1145/2993318.2993320","url":null,"abstract":"Despite recent efforts to achieve a high level of interoperability of Machine Learning (ML) experiments, positively collaborating with the Reproducible Research context, we still run into problems created due to the existence of different ML platforms: each of those have a specific conceptualization or schema for representing data and metadata. This scenario leads to an extra coding-effort to achieve both the desired interoperability and a better provenance level as well as a more automatized environment for obtaining the generated results. Hence, when using ML libraries, it is a common task to re-design specific data models (schemata) and develop wrappers to manage the produced outputs. In this article, we discuss this gap focusing on the solution for the question: \"What is the cleanest and lowest-impact solution, i.e., the minimal effort to achieve both higher interoperability and provenance metadata levels in the Integrated Development Environments (IDE) context and how to facilitate the inherent data querying task?\". We introduce a novel and low-impact methodology specifically designed for code built in that context, combining Semantic Web concepts and reflection in order to minimize the gap for exporting ML metadata in a structured manner, allowing embedded code annotations that are, in run-time, converted in one of the state-of-the-art ML schemas for the Semantic Web: MEX Vocabulary.","PeriodicalId":177013,"journal":{"name":"Proceedings of the 12th International Conference on Semantic Systems","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128647205","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
With the increasing adoption of NoSQL data base systems like MongoDB or CouchDB more and more applications store structured data according to a non-relational, document oriented model. Exposing this structured data as Linked Data is currently inhibited by a lack of standards as well as tools and requires the implementation of custom solutions. While recent efforts aim at expressing transformations of such data models into RDF in a standardized manner, there is a lack of approaches which facilitate SPARQL execution over mapped non-relational data sources. With SparqlMap-M we show how dynamic SPARQL access to non-relational data can be achieved. SparqlMap-M is an extension to our SPARQL-to-SQL rewriter SparqlMap that performs a (partial) transformation of SPARQL queries by using a relational abstraction over a document store. Further, duplicate data in the document store is used to reduce the number of joins and custom optimizations are introduced. Our showcase scenario employs the Berlin SPARQL Benchmark (BSBM) with different adaptions to a document data model. We use this scenario to demonstrate the viability of our approach and compare it to different MongoDB setups and native SQL.
{"title":"Executing SPARQL queries over Mapped Document Store with SparqlMap-M","authors":"Jörg Unbehauen, Michael Martin","doi":"10.1145/2993318.2993326","DOIUrl":"https://doi.org/10.1145/2993318.2993326","url":null,"abstract":"With the increasing adoption of NoSQL data base systems like MongoDB or CouchDB more and more applications store structured data according to a non-relational, document oriented model. Exposing this structured data as Linked Data is currently inhibited by a lack of standards as well as tools and requires the implementation of custom solutions. While recent efforts aim at expressing transformations of such data models into RDF in a standardized manner, there is a lack of approaches which facilitate SPARQL execution over mapped non-relational data sources. With SparqlMap-M we show how dynamic SPARQL access to non-relational data can be achieved. SparqlMap-M is an extension to our SPARQL-to-SQL rewriter SparqlMap that performs a (partial) transformation of SPARQL queries by using a relational abstraction over a document store. Further, duplicate data in the document store is used to reduce the number of joins and custom optimizations are introduced. Our showcase scenario employs the Berlin SPARQL Benchmark (BSBM) with different adaptions to a document data model. We use this scenario to demonstrate the viability of our approach and compare it to different MongoDB setups and native SQL.","PeriodicalId":177013,"journal":{"name":"Proceedings of the 12th International Conference on Semantic Systems","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115875880","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
M. Hürlimann, Brian Davis, Keith Cortis, A. Freitas, S. Handschuh, Sergio Fernández
In this paper, we present a sentiment-annotated Twitter gold standard for the Brexit referendum. The data set consists of 2,000 Twitter messages ("tweets") annotated with information about the sentiment expressed, the strength of the sentiment, and context dependence. This is a valuable resource for social media-based opinion mining in the context of political events.
{"title":"A Twitter Sentiment Gold Standard for the Brexit Referendum","authors":"M. Hürlimann, Brian Davis, Keith Cortis, A. Freitas, S. Handschuh, Sergio Fernández","doi":"10.1145/2993318.2993350","DOIUrl":"https://doi.org/10.1145/2993318.2993350","url":null,"abstract":"In this paper, we present a sentiment-annotated Twitter gold standard for the Brexit referendum. The data set consists of 2,000 Twitter messages (\"tweets\") annotated with information about the sentiment expressed, the strength of the sentiment, and context dependence. This is a valuable resource for social media-based opinion mining in the context of political events.","PeriodicalId":177013,"journal":{"name":"Proceedings of the 12th International Conference on Semantic Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132789157","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Searching among the existing 500 and more vocabularies was never easier than today with the Linked Open Vocabularies (LOV) curated directory list. The LOV search provides one central point to explore the vocabulary terms space. However, it can be still cumbersome for non-experts or semantic annotation experts to discover the appropriate terms for the description of given website content. In this direction, the proposed approach is the cornerstone part of a methodology that aims to facilitate the selection of the highest ranked terms from the abundance of the registered vocabularies based on a keyword search. Moreover, it introduces for the first time the role of the contributors' background, which is retrieved from the LOV repository, in the ranking of the vocabularies. With this addition, we aim to address the issue of very low scores for the newly published vocabularies. The paper underlines the difficulty of selecting vocabulary terms through a survey and describes the approach that enables the ranking of vocabularies within the above mentioned methodology.
{"title":"Linked Open Vocabulary Ranking and Terms Discovery","authors":"Ioannis Stavrakantonakis, A. Fensel, D. Fensel","doi":"10.1145/2993318.2993338","DOIUrl":"https://doi.org/10.1145/2993318.2993338","url":null,"abstract":"Searching among the existing 500 and more vocabularies was never easier than today with the Linked Open Vocabularies (LOV) curated directory list. The LOV search provides one central point to explore the vocabulary terms space. However, it can be still cumbersome for non-experts or semantic annotation experts to discover the appropriate terms for the description of given website content. In this direction, the proposed approach is the cornerstone part of a methodology that aims to facilitate the selection of the highest ranked terms from the abundance of the registered vocabularies based on a keyword search. Moreover, it introduces for the first time the role of the contributors' background, which is retrieved from the LOV repository, in the ranking of the vocabularies. With this addition, we aim to address the issue of very low scores for the newly published vocabularies. The paper underlines the difficulty of selecting vocabulary terms through a survey and describes the approach that enables the ranking of vocabularies within the above mentioned methodology.","PeriodicalId":177013,"journal":{"name":"Proceedings of the 12th International Conference on Semantic Systems","volume":"216 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134062415","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this paper we study whether state-of-the-art techniques for multi-domain and multilingual entity linking can be ported to the clinical domain. To do so, we compare two known entity linking systems, BabelFly and TagMe, that leverage on Wikipedia and DBpedia, with the standard clinical semantic annotation and disambiguation system, MetaMap, over the SemRep clinical word sense disambiguation gold standard. We show that BabelFly and especially TagMe, while achieving decent precision on clinical annotation, outmatch MetaMap's F1-score.
{"title":"Cross-Evaluation of Entity Linking and Disambiguation Systems for Clinical Text Annotation","authors":"Camilo Thorne, Stefano Faralli, H. Stuckenschmidt","doi":"10.1145/2993318.2993345","DOIUrl":"https://doi.org/10.1145/2993318.2993345","url":null,"abstract":"In this paper we study whether state-of-the-art techniques for multi-domain and multilingual entity linking can be ported to the clinical domain. To do so, we compare two known entity linking systems, BabelFly and TagMe, that leverage on Wikipedia and DBpedia, with the standard clinical semantic annotation and disambiguation system, MetaMap, over the SemRep clinical word sense disambiguation gold standard. We show that BabelFly and especially TagMe, while achieving decent precision on clinical annotation, outmatch MetaMap's F1-score.","PeriodicalId":177013,"journal":{"name":"Proceedings of the 12th International Conference on Semantic Systems","volume":"143 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115809891","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This article introduces KRLO, an ontology of knowledge representation languages (KRLs), the first to represent KRL abstract models in a uniform way and the first to represent KRL notations, i.e., concrete models. Thus, KRLO can help design tools handling many KRLs and letting their end-users design or adapt KRLs. KRLO also represent KRL import, translation and export methods in a declarative way, both via Datalog like rules and pure functions.
{"title":"Top-level Ideas about Importing, Translating and Exporting Knowledge via an Ontology of Representation Languages","authors":"Philippe A. Martin, Jérémy Bénard","doi":"10.1145/2993318.2993344","DOIUrl":"https://doi.org/10.1145/2993318.2993344","url":null,"abstract":"This article introduces KRLO, an ontology of knowledge representation languages (KRLs), the first to represent KRL abstract models in a uniform way and the first to represent KRL notations, i.e., concrete models. Thus, KRLO can help design tools handling many KRLs and letting their end-users design or adapt KRLs. KRLO also represent KRL import, translation and export methods in a declarative way, both via Datalog like rules and pure functions.","PeriodicalId":177013,"journal":{"name":"Proceedings of the 12th International Conference on Semantic Systems","volume":"33 9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115029431","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Images account for an important part of Multimedia Linked Open Data, but currently most of the semantic relations between images and other entities are based on manual semantic annotation. With the popularity of image hosting websites, such as Flickr, plentiful tagging information of images makes it possible to automatically generate semantic relations between images and other semantic entities. In this paper, we propose a model for linking images to semantic knowledge base (KB) with user-generated tags of those images, while taking into account topical semantic similarity between tags. The experimental results show that our approach can effectively realize the mentioned aim.
{"title":"Linking Images to Semantic Knowledge Base with User-generated Tags","authors":"Shuangyong Song, Qingliang Miao, Yao Meng","doi":"10.1145/2993318.2993340","DOIUrl":"https://doi.org/10.1145/2993318.2993340","url":null,"abstract":"Images account for an important part of Multimedia Linked Open Data, but currently most of the semantic relations between images and other entities are based on manual semantic annotation. With the popularity of image hosting websites, such as Flickr, plentiful tagging information of images makes it possible to automatically generate semantic relations between images and other semantic entities. In this paper, we propose a model for linking images to semantic knowledge base (KB) with user-generated tags of those images, while taking into account topical semantic similarity between tags. The experimental results show that our approach can effectively realize the mentioned aim.","PeriodicalId":177013,"journal":{"name":"Proceedings of the 12th International Conference on Semantic Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116299563","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Different access control models are presented in literature for semantic data, allowing the expression and enforcement of access policies that are based on roles and other attributes of the requesting user usually. We investigate a different access control perspective in the present work, allowing a Policy Administrator to define system obligations that are focused on the enhanced semantics, with a particular reference to the information that can be inferred from the starting knowledge representation, using DL reasoning. That is done by applying a paradigm for the specification and enforcement of access control obligations to the SPARQL-DL query model for OWL ontologies. The presented approach allows more than a simple permit/deny control on inferred data (e.g., data can be returned, but after an anonymization process), together with the possibility of specifying very expressive policies.
{"title":"Modeling and Enforcing Access Control Obligations for SPARQL-DL Queries","authors":"Nicoletta Fornara, Fabio Marfia","doi":"10.1145/2993318.2993337","DOIUrl":"https://doi.org/10.1145/2993318.2993337","url":null,"abstract":"Different access control models are presented in literature for semantic data, allowing the expression and enforcement of access policies that are based on roles and other attributes of the requesting user usually. We investigate a different access control perspective in the present work, allowing a Policy Administrator to define system obligations that are focused on the enhanced semantics, with a particular reference to the information that can be inferred from the starting knowledge representation, using DL reasoning. That is done by applying a paradigm for the specification and enforcement of access control obligations to the SPARQL-DL query model for OWL ontologies. The presented approach allows more than a simple permit/deny control on inferred data (e.g., data can be returned, but after an anonymization process), together with the possibility of specifying very expressive policies.","PeriodicalId":177013,"journal":{"name":"Proceedings of the 12th International Conference on Semantic Systems","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126419812","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
F. Kleedorfer, Yana Panchenko, C. Busch, C. Huemer
When linked data applications communicate, they commonly use messaging technologies in which the message exchange itself is not represented as linked data, since it takes place on a different architectural level. When a message cannot be verified and traced on the linked data level, trust in data is moved from message originators to service providers. However, there are use cases in which the actual message exchange and its verifiability are of importance. In such situations, the separation between application data and communication data is not desirable. To address this, we propose messaging based on linked data, where communicating entities and their messages are represented as interconnected Web resources, and we show how conversations can be made verifiable using digital signatures.
{"title":"Verifiability and Traceability in a Linked Data Based Messaging System","authors":"F. Kleedorfer, Yana Panchenko, C. Busch, C. Huemer","doi":"10.1145/2993318.2993342","DOIUrl":"https://doi.org/10.1145/2993318.2993342","url":null,"abstract":"When linked data applications communicate, they commonly use messaging technologies in which the message exchange itself is not represented as linked data, since it takes place on a different architectural level. When a message cannot be verified and traced on the linked data level, trust in data is moved from message originators to service providers. However, there are use cases in which the actual message exchange and its verifiability are of importance. In such situations, the separation between application data and communication data is not desirable. To address this, we propose messaging based on linked data, where communicating entities and their messages are represented as interconnected Web resources, and we show how conversations can be made verifiable using digital signatures.","PeriodicalId":177013,"journal":{"name":"Proceedings of the 12th International Conference on Semantic Systems","volume":"72 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127379883","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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