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Property:Has conclusion
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Pages using the property "Has conclusion"
Showing 16 pages using this property.
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| Optimizing SPARQL Queries over Disparate RDF Data Sources through Distributed Semi-joins + | We briefly presented our Sesame extension Distributed SPARQL which aims at providing an integrated way of querying data sources scattered across multiple SPARQL endpoints. We shortly described its implementation and optimization used so far and outlined the direction for its future development. Distributed SPARQL is a part of Networked Graphs project and is publicly available at https://launchpad.net/networkedgraphs. + |
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| Querying Distributed RDF Data Sources with SPARQL + | DARQ offers a single interface for querying multiple, distributed SPARQL end-points and makes query federation transparent to the client. One key feature of DARQ is that it solely relies on the SPARQL standard and therefore is compatible to any SPARQL endpoint implementing this standard. Using service descriptions provides a powerful way to dynamically add and remove endpoints to the query engine in a manner that is completely transparent to the user. To reduce execution costs we introduced basic query optimization for SPARQL queries. Our experiments show that the optimization algorithm can drastically improve query performance and allow distributed answering of SPARQL queries over distributed sources in reasonable time. Because the algorithm only relies on a very small amount of statistical information we expect that further improvements are possible using techniques. An important issue when dealing with data from multiple data sources are differences in the used vocabularies and the representation of information. In further work, we plan to work on mapping and translation rules between the vocabularies used by different SPARQL endpoints. Also, we will investigate generalizing the query patterns that can be handled and blank nodes and identity relationships across graphs. + |
| Querying over Federated SPARQL Endpoints : A State of the Art Survey + | Federation query over SPARQL Endpoints made a significant progress in the recent years. Although a number of federation frameworks have already been developed, the field is still relatively far from maturity. Based on our experience with the existing federation frameworks, the frameworks mostly focus on source selection and join optimization during query execution. In this work, we have presented a list of federation frameworks over SPARQL Endpoints along with their features. According to this list, the user can have considerations to choose the suitable federation framework for their case. We have classied those framework into three categories: i) framework interprets SPARQL 1.1 query to execute federation SPARQL query covering VALUES and SERVICE operator; ii) framework handles SPARQL 1.0 query and has responsibility to find relevant source for a query and join incoming result from SPARQL Endpoints; and iii) framework accepts SPARQL 1.0 and translate the incoming query to SPARQL 1.1 format. Based on the current generation of federation frameworks surveyed in this paper, it still requires further improvements to make frameworks more effective in a broader range of applications. We suggested several features that could be included in the future developments. Finally, we point out challenges for future research directions. + |
| Querying the Web of Data with Graph Theory-based Techniques + | In this paper we present a novel graph theory-based approach for improved performance and scalability of distributed SPARQL query processing. We propose several key techniques adopted in the distributed SPARQL query engine that we developed (GDS). First, an extended MST algorithm which supports arbitrary SPARQL queries and provides better performance. Second, a simplified cost model using run-time statistics that lows requirement of service descriptions but provides good cost estimations. Third, a combination of semi-join and bind-join along with local cache that reduce network tracffic. We also compare our approach with DARQ and FedX in terms of performance and scalability. The results suggest that graph theory-based approach using lightweight service descriptions can provide better performance and scalability over other approaches Although these results are encouraging, the potential of graph theory-based approach can be developed further. First, GDS applies MST-based algorithm to BGPs rather than the whole query. BGPs are optimized separately even they are from the same query (i.e. UNION and OPTIONAL queries). In the future we aim to work on representing the whole query as a single graph and therefore provide better optimization for queries having multiple BGPs. Second, GDS does not take advantage of FILTER in optimization, which would further improve performance. Third, accurate and detailed service descriptions matters. The more accurate statistics we have, the more optimal query plan we get. Currently collecting quality service descriptions are not feasible on a large scale since most SPARQL endpoints do not provide service descriptions. However, this situation is improving as more and more approaches coming up. For example, SPARQL 1.1 aggregation features enable us to collect service descriptions more efficiently, and VoiD encourages SPARQL endpoints to publish service descriptions as well. Fourth, aggregation features in the upcoming SPARQL 1.1 (e.g. BINDINGS) can also save much efforts of our approach. In addition to these improvements, we are planning to explore the co-reference issue in the Linked Data cloud. From the perspective of distributed SPARQL queries, this issue is getting worse as more data are published , and we plan to address this issue by using our Virtual Graph approach. + |
| Querying the Web of Interlinked Datasets using VOID Descriptions + | In this paper, we have introduced a query federation engine called WoDQA that discovers related datasets in a VOID store for a query and distributes the query over these datasets. The novelty of our approach is exhaustive dataset selection mechanism which includes analysis of triple pattern relations and links between datasets besides analyzing datasets for each triple pattern. WoDQA focuses on discovering relevant datasets and eliminating irrelevant ones using a rule-based approach introduced in this paper. Our approach requires query the dataset, reflect actual content of the dataset completely and accurately, and include linksets between datasets to select datasets ectively. WoDQA allows users to construct raw queries without the need to know how query will divide into sub-queries and where sub-queries are executed. Query results are complete under the assumption of available, accurate and complete VOID descriptions of datasets. The initial version of WoDQA which is introduced in this paper has some disadvantages arising from query federation approach which WoDQA builds upon. As mentioned previously, follow-your-nose has some problems such as missing results and large document retrieval. Similar problems may occur for query federation. Firstly, to find complete results to queries, it is required that metadata of all datasets must be well-defined and accurate. But, to provide such an accurate dataset metadata an automated mechanism which continuously updates the metadata is required. However, even there would be a tool which implements this requirement, providing accurate dataset metadata via such a tool is the responsibility of dataset publishers. Another problems of query federation are high latency and low selectivity of datasets which are similar to retrieval of large documents in follow-your-nose. Query optimization can be a solution for these problems of query federation. Grouping triple patterns to lter more triples on an endpoint can prevent high latency (required processing time) and changing query evaluation order according to dataset selectivity statistics can prevent retrieving large result sets. To make WoDQA functioning in the wild, optimization step of query federation is required to be implemented. We plan to incorporate triple pattern selectivity into query reorganization using VOID properties about statistics. On the other hand, we could not make an evaluation of our approach in this paper, since VOID documents in current VOID stores are not well-dened. Since SPARQL endpoint denitions, linkset descriptions or vocabularies are missing in most of VOID documents, we could not nd a chance to execute comprehensive scenarios. Developing a tool which extracts well-dened VOID descriptions of datasets, and by this means evaluating our approach is a required future work to confirm applicability of WoDQA on linked open data. Also, evaluating the analysis cost of WoDQA for a large VOID store will be possible when well-dened VOIDs are constructed. + |
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| RDB2ONT: A Tool for Generating OWL Ontologies From Relational Database Systems + | In this paper, an algorithm and tool for generating OWL ontologies from relational database systems is presented. The tool, RDB2ONT, helps the domain experts to quickly generate and publish OWL ontologies describing the underlying relational database systems while preserving their structural constraints. The generated ontologies are constructed using a set of vocabularies and structures defined in schema that describes relational database systems on the web so they guarantees that user applications can work with data instances that conformed to a set of known vocabularies and structures. The generated ontologies provide a standardized and meaningful way for describing the underlying relational database systems so they “bridge” the semantic gaps between the ontologies describing relational database systems and/or the ontologies describing other data sources on the web such as flat-files, semi-structures, etc. Concepts in OWL ontologies can be defined at multiple levels of granularities thus the generated OWL ontologies can be used to address the semantic heterogeneity problem at multiple levels. Evolutions of database systems in large-scale environments are inevitable so by using the RDB2ONT tool, OWL ontologies can be re-generated with little effort from the domain experts thus speed up the process of facilitating data in the underlying relational database systems with other data sources on the web. Although the generated OWL ontologies provide the explicit meaning of concepts and their semantic relationships between related concepts, there are still many open research questions that need to be addressed. One of the questions is how to merge the generated OWL ontologies into an integrated OWL ontology so that common views of concepts can be achieved? This would allow users to pose queries on the common views of concepts rather than the concepts defined in the individual ontologies. + |
| Relational.OWL - A Data and Schema Representation Format Based on OWL + | In this paper we have shown how to represent schema and data items originally stored in relational database systems using our own OWL ontology. Relational.OWL enables us to semantically represent the schema of any relational database. This representation itself can be interpreted, due to the properties of OWL Full, as a novel ontology. Based on the latter ontology, we can now semantically represent the data stored in this specific database. The advantage of this representation technique is obvious: Both, schema and data changes can automatically be transferred to and processed by any remote database system, which is able to understand knowledge representation techniques used within OWL. Misunderstandings are impossible.Besides the refinement and completion of the concrete schema representation, we consider on how to adopt our technique to other types of database systems. Similar solutions can easily be found for Object-Oriented Databases, Hierarchical Databases like IMS, or its hybrid the modern and more common X.500 or LDAP Directory Systems + |
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| SERIMI – Resource Description Similarity, RDF Instance Matching and Interlinking + | RDF instance matching in the context of interlinking RDF datasets published in the Linked Data Cloud is the task of determining if two resources are referred to the same entity in the real world. This is a challenging task in high demand by data publishers that wish to interlink their datasets in the cloud. In this work, we propose a novel approach, called SERIMI, for solving the RDF instance-matching problem automatically. SERIMI matches instances between a source and target datasets, without prior knowledge of the data, domain or schema of these datasets. It does so by approximating the notion of similarity by pairing instances based on entity labels as well as structural (ontological) context. As part of the SERIMI approach, we proposed the CRDS function to approximate that judgment of similarity. We used two collections proposed by the OAEI 2010 initiative to evaluate SERIMI. On average, SERIMI outperforms two representative systems, RiMOM and ObjectCoref, which tried to solve the same problem using the same collections and reference alignment, in 70% of the cases. + |
| SLINT: A Schema-Independent Linked Data Interlinking System + | In this paper, we present SLINT, an efficient schema-independent linked data interlinking system. We select important predicates by predicate’s coverage and discriminability. The predicate alignments are constructed and filtered for obtaining key alignments.We implement an adaptive filtering technique to produce candidates and identities. Compare with the most recent systems, SLINT highly outperforms the precision and recall in interlinking. The performance of SLINT is also very high when it takes around 1 minute to detect more than 13,000 identity pairs. + |
| SPLENDID: SPARQL Endpoint Federation Exploiting VOID Descriptions + | SPLENDID allows for transparent query federation over distributed SPARQL endpoints. In order to achieve a good query execution performance, data source selection and query optimization is based on basic statistical information which is obtained from VOID descriptions. The utilization of open semantic web standards, like VOID and SPARQL endpoints, allows for flexible integration of various distributed and linked RDF data sources. We have described in detail the implementation of the data source selection and the join order optimization. The evaluation shows that our approach can achieve good query performance and is competitive compared to other state-of-the-art federation implementations. In our analysis of the source selection we came to the conclusion that at least predicate and type statistics should be included in VOID description for RDF datasets. The use of 3rd party sameAs links, however, can significantly increase the number of requests and thus, hamper the efficiency of query execution plans. The comparison of the two employed physical join implementations has shown that the network overhead plays an important role. Both hash join and bind join can significantly reduce the query processing time for certain types of queries. With SPLENDID we also like to advocate the adoption of VOID statistics for Linked Data. As next steps, we plan to investigate whether VOID descriptions can easily be extended with more detailed statistics in order to allow for more accurate cardinality estimates and, thus, better query execution plans. On the other hand, the actual query execution has not yet been optimized in SPLENDID. Therefore, we plan to integrate optimization techniques as used in FedX. Moreover, the adoption of the SPARQL 1.1 federation extension will also allow for more efficient query execution. + |
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| Towards a Knowledge Graph Representing Research Findings by Semantifying Survey Articles + | In this article, we presented SemSur, a Semantic Survey Ontology, and an approach for creating a comprehensive knowledge graph representing research findings. We see this work as an initial step of a long-term research agenda to create a paradigm shift from document-based to knowledge-based scholarly communication. Our vision is to have this work deployed in an extended version of the existing OpenResearch.org platform. We have created instances of three selected surveys on different fields of research using the SemSur ontology. We evaluated our approach involving nine researchers. As we see in the evaluation results, SemSur enables successful retrieval of relevant and accurate results without users having to spend much time and effort compared to traditional ways. This ontology can have a significant influence on the scientific community especially for researchers who want to create a survey article or write literature on a certain topic. The results of our evaluation show that researchers agree that the traditional way of gathering an overview on a particular research topic is cumbersome and time-consuming. Much effort is needed and important information might be easily overlooked. Collaborative integration of research metadata provided by the community supports researchers in this regard. Interviewed domain experts mentioned that it might be necessary to read and understand 30 to 100 scientific articles to get a proper level of understanding or an overview of a topic or sub-topics. A collaboration of researchers as owners of each particular research work to provide a structured and semantic representation of their research achievements can have a huge impact in making their research more accessible. A similar effort is spent on preparing survey and overview articles. + |
| Towards a Knowledge Graph for Science + | The transition from purely document-centric to a more knowledge-based view on scholarly communication is in line with the current digital transformation of information flows in general and is thus inevitable. However, this also creates a need for the implementation of corresponding tools and workflows supporting the switch. As of now, there are still very few of those tools, and their design and concrete features remain a challenge that is yet to be tackled – collaboratively and in a coordinated manner. + |
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| Unveiling the hidden bride: deep annotation for mapping and migrating legacy data to the Semantic Web + | In this paper, we have described deep annotation, an original framework to provide semantic annotation for large sets of data. Deep annotation leaves semantic data where it can be handled best, viz. in database systems. Thus, deep annotation provides a means for mapping and reusing dynamic data in the Semantic Web with tools that are comparatively simple and intuitive to use. To attain this objective we have defined a deep annotation process and the appropriate architecture. We have incorporated the means for server-side markup that allows the user to define semantic mappings by using OntoMat-Annotizer to create Web presentation-based annotations 12 and OntoMat-Reverse to create schema-based annotations. An ontology and mapping editor and an inference engine are then used to investigate and exploit the resulting descriptions either for querying the database content or to materialize the content into RDF files. In total, we have provided a complete framework and its prototype implementation for deep annotation. + |
| Updating Relational Data via SPARQL/Update + | In this paper, we presented our approach OntoAccess that enables the manipulation of relational data via SPARQL/Update. We introduced the update-aware RDB to RDF mapping language R3M that captures additional information about the database schema, in particular about integrity constraints. This information enables the detection of update requests that are invalid from the RDB perspective. Such requests cannot be executed by the database engine as they would violate integrity constraints of the database schema. The information can also be exploited to provide semantically rich feedback to the client. Therefore, the causes for the rejection of a request and possible directions for improvement can be reported in an appropriate format. + |
| Use of OWL and SWRL for Semantic Relational Database Translation + | We are currently applying Automapper's approach to other Semantic Bridges. Specifically, we are exploring its use for both SOAP and RESTful services in our Semantic Bridge for Web Services (SBWS). + |
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| Zhishi.links Results for OAEI 2011 + | In this report, we have presented a brief description of Zhishi.links, an instance matching system. We have introduced the architecture of our system and specific techniques we used. Also, the results have been analyzed in detail and several guides for improvements have been proposed. + |
Facts about "Has conclusion"
| Has type "Has type" is a predefined property that describes the datatype of a property and is provided by Semantic MediaWiki. | Text + |
