Search by property

This page provides a simple browsing interface for finding entities described by a property and a named value. Other available search interfaces include the page property search, and the ask query builder.

List of results

• Querying the Web of Interlinked Datasets using VOID Descriptions  + (In this paper, we have introduced a query …
  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.
  ble when well-dened VOIDs are constructed.)
• LogMap: Logic-based and Scalable Ontology Matching  + (In this paper, we have presented LogMap, a …
  In this paper, we have presented LogMap, a highly scalable ontology matching tool with built-in reasoning and diagnosis capabilities. LogMap's features and scalability behaviour make it well-suited for matching large-scale ontologies. LogMap, however, is still an early-stage prototype and there is plenty of room for improvement.
  d there is plenty of room for improvement.)
• DataMaster – a Plug-in for Importing Schemas and Data from Relational Databases into Protégé  + (In this paper, we have presented the DataM …
  In this paper, we have presented the DataMaster Protégé plug-in, which allows a user to import schema structures and data from relational databases accessible through JDBC. We have presented the four ontologies that can be used to represent the database structure and the table data and finally we have given a short overview of the different import options available in the DataMaster plug-in.
  tions available in the DataMaster plug-in.)
• Cross: an OWL wrapper for teasoning on relational databases  + (In this paper, we have proposed the ODBC m …
  In this paper, we have proposed the ODBC model, a formalization of relational databases focusing on their logic model. We have then presented a transformation of that model into OWL, a DL-based language designed for the Semantic Web. This transformation is implemented by the Cross open-source prototype, which effectively introduces the interesting notion of semantic values. We proved that the knowledge-based produced by this transformation is consistent if and only if the source database state is weakly legal (i.e. legal but regarding foreign key constraints). Taking advantage of that result, we have shown how that transformation can prove useful for the purpose of analysing legacy RDBs, enhancing existing RDBs with additional constraints, and integrating them in the SW.
  nstraints, and integrating them in the SW.)
• SLINT: A Schema-Independent Linked Data Interlinking System  + (In this paper, we present SLINT, an effici …
  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.
  to detect more than 13,000 identity pairs.)
• Accessing and Documenting Relational Databases through OWL Ontologies  + (In this paper, we presented a completely a …
  In this paper, we presented a completely automated approach to map relational databases and ontologies. The system proposed is capable of extracting an ontological view of the relational schema, and to enable SPARQL access to the relational data source by means of a query rewriting mechanism. The same approach can be used to efficiently store relational ontologies on a RDBMS; moreover, the mapping we devised is completely based on OWL with no need to resort to a new formalism. The impact of this system has been discussed considering three main applications: (i) publishing of relational data in an ontological format, (ii) documentation of relational schemas by means of ontological annotations, and (iii) efficient relational storage for data-intensive ontologies.
  nal storage for data-intensive ontologies.)
• Updating Relational Data via SPARQL/Update  + (In this paper, we presented our approach O …
  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.
  can be reported in an appropriate format.)
• Integration of Scholarly Communication Metadata using Knowledge Graphs  + (In this paper, we presented the concept of …
  In this paper, we presented the concept of Scholarly Communication Metadata Knowledge Graph (SCM-KG), which integrates heterogeneous, distributed schemas, data and metadata from a variety of scholarly communication data sources. As a proof-of-concept, we developed an SCM-KG pipeline to create a knowledge graph by integrating data collected from heterogeneous data sources. We showed the capability of parallelization in rule-based data mappings, and we also presented how semantic similarity measures are applied to determine the relatedness of concepts in two resources in terms of the relatedness of their RDF interlinking structure. Results of the empirical evaluation suggest that the integration approach pursued by the SCM-KG pipeline is able to effectively integrate pieces of information spread across different data sources. The experiments suggest that the rule based mapping together with semantic structure based instance matching technique implemented in the SCM-KG pipeline integrates data in a knowledge graph with high accuracy. Although our initial use case addresses the scientific metadata domain, we generated billions of triples with high accuracy in mapping and linking, and we regard it capable at an industrial scale and in use cases demanding high precision.
  and in use cases demanding high precision.)
• FedX: Optimization Techniques for Federated Query Processing on Linked Data  + (In this paper, we proposed novel optimizat …
  In this paper, we proposed novel optimization techniques for efficient SPARQL query processing in the federated setting. As revealed by our benchmarks, bound joins combined with our grouping and source selection approaches are effective in terms of performance. By minimizing the number of intermediate requests, we are able to improve query performance significantly compared to state-of-the-art systems. We presented FedX, a practical solution that allows for querying multiple distributed Linked Data sources as if the data resides in a virtually integrated RDF graph. Compatible with the SPARQL 1.0 query language, our framework allows clients to integrate available SPARQL endpoints on-demand into a federation without any local preprocessing. While we focused on optimization techniques for conjunctive queries, namely basic graph patterns (BGPs), there is additional potential in developing novel, operator-specific optimization techniques for distributed settings (in particular for OPTIONAL queries), which we are planning to address in future work. As our experiments confirm, the optimization of BGPs alone (combined with common equivalent rewritings) already yields significant performance gains. Important features for federated query processing are the federation extensions proposed for the upcoming SPARQL 1.1 language definition. These allow to specify data sources directly within the query using the SERVICE operator, and moreover to attach mappings to the query as data using the BINDINGS operator. When implementing the SPARQL 1.1 federation extensions for our next release,FedX can exploit these language features to further improve performance. In fact, the SPARQL 1.1 SERVICE keyword is a trivial extension, which enhances our source selection approach with possibilities for manual specification of new sources and gives the query designer more control. Statistics can in uence performance tremendously in a distributed setting. Currently, FedX does not use any local statistics since we follow the design goal of on-demand federation setup. We aim at providing a federation framework, in which data sources can be integrated ad-hoc, and used immediately for query processing. In a future release, (remote) statistics (e.g., using VoID ) can be incorporated for source selection and to further improve our join order algorithm.
  further improve our join order algorithm.)
• Bringing Relational Databases into the Semantic Web: A Survey  + (In this paper, we tried to present the wea …
  In this paper, we tried to present the wealth of research work marrying the worlds of relational databases and Semantic Web. We illustrated the variety of different approaches and identified the main challenges that researchers of this field face as well as proposed solutions.
  field face as well as proposed solutions.)
• Zhishi.links Results for OAEI 2011  + (In this report, we have presented a brief …
  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.
  uides for improvements have been proposed.)

• AgreementMaker: Efficient Matching for Large Real-World Schemas and Ontologies  + (No data available now.)

• SERIMI – Resource Description Similarity, RDF Instance Matching and Interlinking  + (RDF instance matching in the context of in …
  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.
  reference alignment, in 70% of the cases.)
• SPLENDID: SPARQL Endpoint Federation Exploiting VOID Descriptions  + (SPLENDID allows for transparent query fede …
  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.
  allow for more efficient query execution.)
• Towards a Knowledge Graph for Science  + (The transition from purely document-centri …
  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.
  llaboratively and in a coordinated manner.)
• 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).)
• Optimizing SPARQL Queries over Disparate RDF Data Sources through Distributed Semi-joins  + (We briefly presented our Sesame extension …
  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.
  at https://launchpad.net/networkedgraphs.)
• ANAPSID: An Adaptive Query Processing Engine for SPARQL Endpoints  + (We have defined ANAPSID, an adaptive query …
  We have defined ANAPSID, an adaptive query processing engine for RDF Linked Data accessible through SPARQL endpoints. ANAPSID provides a set of physical operators and an execution engine able to adapt the query execution to the availability of the endpoints and to hide delays from users. Reported experimental results suggest that our proposed techniques reduce execution times and are able to produce answers when other engines fail. Also, depending on the selectivity of the join operator and the data transfer delays, ANAPSID operators may overcome state-of-the-art Symmetric Hash Join operators. In the future, we plan to extend ANAPSID with more powerful and lightweight operators like Eddy and MJoin, which are able to route received responses through different operators and adapt the execution to unpredictable delays by changing the order in which each data item is routed.
  e order in which each data item is routed.)
• A Survey of Current Link Discovery Frameworks  + (We investigated ten LD frameworks and comp …
  We investigated ten LD frameworks and compared their functionality based on a common set of criteria. The criteria cover the main steps such as the configuration of linking specifications and methods for matching and runtime optimization. We also covered general aspects such as the supported input formats and link types, support for a GUI and software availability as open source. We observed that the considered tools already provide a rich functionality with support for semi-automatic configuration including advanced learning-based approaches such as unsupervised genetic programming or active learning. On the other side, we found that most tools still focus on simple property-based match techniques rather than using the ontological context within structural matchers. Furthermore, existing links and background knowledge are not yet exploited in the considered frameworks. More comprehensive support of efficiency techniques is also necessary such as the combined use of blocking, filtering and parallel processing. We also analyzed comparative evaluations of the LD frameworks to assess their relative effectiveness and efficiency. In this respect, the OAEI instance matching track is the most relevant effort and we thus analyzed its match tasks and the tool participation and results for the last years. Unfortunately, the participation has been rather low thereby preventing the comparative evaluation between most of the tools. Moreover, the focus of the contest has been on effectiveness so far while runtime efficiency has not yet been evaluated. To better assess the relative effectiveness and efficiency of LD tools it would be valuable to test them on a common set of benchmark tasks on the same hardware. Given the general availability of the tools and the existence of a considerable set of match task definitions and datasets this should be feasible with reasonable effort.
  should be feasible with reasonable effort.)
• A Probabilistic-Logical Framework for Ontology Matching  + (We presented a Markov logic based framewor …
  We presented a Markov logic based framework for ontology matching capturing a wide range of matching strategies. Since these strategies are expressed with a unified syntax and semantics we can isolate variations and empirically evaluate their effects. Even though we focused only on a small subset of possible alignment strategies the results are already quite promising. We have also successfully learned weights for soft formulae within the framework. In cases where training data is not available, weights set manually by experts still result in improved alignment quality. Research related to determining appropriate weights based on structural properties of ontologies is a topic of future work.
  s of ontologies is a topic of future work.)
• LIMES - A Time-Efficient Approach for Large-Scale Link Discovery on the Web of Data  + (We presented the LIMES framework, which im …
  We presented the LIMES framework, which implements a very time-efficient approach for the discovery of links between knowledge bases on the Linked Data Web. We evaluated our approach both with synthetic and real data and showed that it outperforms state-of-the-art approaches with respect to the number of comparisons and runtime. In particular, we showed that the speedup of our approach grows with the a-priori time complexity of the mapping task, making our framework especially suitable for handling large-scale matching tasks (cf. results of the SimCities experiment).
  (cf. results of the SimCities experiment).)
• Discovering and Maintaining Links on the Web of Data  + (We presented the Silk framework, a flexibl …
  We presented the Silk framework, a flexible tool for discovering links between entities within different web data sources. The Silk-LSL link specification language was introduced and its applicability was demonstrated within a life science use case. We then proposed the WOD-LMP protocol for synchronizing and maintaining links between continuously changing Linked Data sources.
  continuously changing Linked Data sources.)