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Property:Has conclusion

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Pages using the property "Has conclusion"

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A
A Probabilistic-Logical Framework for Ontology Matching +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.  +
A Semantic Web Middleware for Virtual Data Integration on the Web +In this contribution a mediator-based system for virtual data integration based on SemanticWeb technology has been presented. The system is primarily developed for sharing scientific data, but because of its generic architecture, it is supposed to be used for many other Semantic Web applications. In this paper query federation based on SPARQL and Jena/ARQ has been demonstrated in detail and several concepts for query optimization which is currently on the agenda have been discussed. Additional contributions can be expected after the implementation of additional features mentioned before.  +
A Survey of Current Link Discovery Frameworks +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.  +
ANAPSID: An Adaptive Query Processing Engine for SPARQL Endpoints +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.  +
Accessing and Documenting Relational Databases through OWL Ontologies +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.  +
Adaptive Integration of Distributed Semantic Web Data +An adaptive framework has been presented for executing queries over multiple SPARQL endpoints that differs from existing approaches which use static query optimisation techniques. Many SPARQL web services are currently available and the number of them is growing. The work presented in this paper is a framework for executing queries over federations of such services. The framework proposed in this paper, which allows adaptive query processing over dynamically constructed predicate tables to be performed in conjunction with the construction of the predicate tables, was shown to perform relatively well in unpredictable environments where source query failures may occur. The prototype implemented was evaluated using real data, showing some advantage in terms of response times of adaptive over non-adaptive methods using a subset of DBPedia..  +
AgreementMaker: Efficient Matching for Large Real-World Schemas and Ontologies +No data available now.  +
Analysing Scholarly Communication Metadata of Computer Science Events +In summary, we made the following observations: With the number of submissions to the top conferences having tripled on average in the last three decades, acceptance rates are going down slightly. Most of those conferences that are A- or A*-rated today have a long continuity. In summary, we made the following observations: With the number of submissions to the top conferences having tripled on average in the last three decades, acceptance rates are going down slightly. Most of those conferences that are A- or A*-rated today have a long continuity. Geographical distribution is not generally relevant; some good conferences take place in the same location; others cycle between continents. Good conferences always take place around the same time of the year. This might mean that the community got used to them being important events. Some topics have attracted increasing interest recently e.g., database topics thanks to the `big data' trend. This might be confirmed by further investigations into more recent, emerging events in such fields.  +
Avalanche: Putting the Spirit of the Web back into Semantic Web Querying +In this paper we presented Avalanche , a novel approach for querying the Web of Data that (1) makes no assumptions about data distribution, availability, or partitioning, (2) provides up-to-date results, and (3) is flexible since it assumes nothing about the structure of participating triple stores. Specifically, we showed that Avalanche is able to execute non-trivial queries over distributed data-sources with an ex-ante unknown data-distribution. We showed two possible utility functions to guide the planning and execution over the distributed data-sources—the basic simple model and an extended model exploiting join estimation. We found that whilst the simple model found some results faster it did find less results than the extended model using the same stopping criteria. We believe that if we were to query huge information spaces the overhead of badly selected plans will be subdued by the better but slower plans of the extended utility function. To our knowledge, Avalanche is the first Semantic Web query system that makes no assumptions about the data distribution whatsoever. Whilst it is only a first implementation with a number of drawbacks it represents a first important towards bringing the spirit of the web back to triple-stores—a major condition to fulfill the vision of a truly global and open Semantic Web.  +
B
Bringing Relational Databases into the Semantic Web: A Survey +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.  +
C
Cross: an OWL wrapper for teasoning on relational databases +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.  +
D
D2RQ – Treating Non-RDF Databases as Virtual RDF Graphs +D2RQ offers a flexible, easy-to-use access mechanism to non-RDF databases. It allows the integration of legacy databases into the data access architecture currently standardized by the W3C Data Access Working Group  +
DataMaster – a Plug-in for Importing Schemas and Data from Relational Databases into Protégé +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.  +
Discovering and Maintaining Links on the Web of Data +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.  +
F
FedX: Optimization Techniques for Federated Query Processing on Linked Data +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.  +
From Relational Data to RDFS Models +In this paper we have introduced FDR2 – a technique that enables us to link relational and RDF/S data models. According to FDR2 a relational schema is automatically created to explicate the structure and internal relationships between elements of a relational collection of data. Explication of virtual relations allows the user to construct a relational schema specific RDMap by defining relationships between concepts from the relational schema and a domain ontology. The actual relational data are automatically expressed in RDF according to the generated relational schema. Run-time integration is achieved by applying an RDFS reasoner to merge the above-mentioned components into a single RDFS model and to deduct necessary entailments. A resulting run-time model allows to access the relational data with queries termed according to the domain ontology. FDR2 is purely RDF/S-based and does not require any additional software components except an RDFS reasoner.  +
I
Integration of Scholarly Communication Metadata using Knowledge Graphs +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.  +
K
KnoFuss: A Comprehensive Architecture for Knowledge Fusion +-  +
L
LIMES - A Time-Efficient Approach for Large-Scale Link Discovery on the Web of Data +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).  +
LogMap: Logic-based and Scalable Ontology Matching +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.  +
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