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List of results

• 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.)