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List of results

• KnoFuss: A Comprehensive Architecture for Knowledge Fusion  + (-)
• Querying the Web of Interlinked Datasets using VOID Descriptions  + (-)

• Towards a Knowledge Graph Representing Research Findings by Semantifying Survey Articles  + (5 out of the 9 researchers immediately sta …
  5 out of the 9 researchers immediately started with wellknown standardWeb search engines to explore the given topic. They tried to use several variations of keywords from the questions, e.g., “Federated Query Engines”, “SPARQL Federation”, etc. They also used digital libraries and scientific metadata services, e.g., ACM DL or Microsoft Academic Search, following the same approach and sometimes using advanced search options and filters. However, the retrieved results were either out of scope for the question but more related to the search keywords. Overall, 8 researchers found it difficult to collect information and reach a conclusive overview of the research topics or related work using current methods. Six of the participants pointed out that for some of the overview questions, search engines were as good as the proposed system particularly when the framework name is part of the search keyword. They all agreed that for complicated questions our SemSur approach outperformed any existing approach/tool. Seven participants agreed that our system would be helpful for both new and experienced researchers. Two-thirds of them strongly agreed that the time and effort they spent to find such information using our system in comparison to other traditional ways is relatively low. Finally, 100% of the participants would like to use SemSur approach in their further research for studying the literature of a research topic or writing a survey article. Since the results of queries were shown to the participants in table view, the main feedback from all participants about possible improvements was to provide a better way of data representation.
  ovide a better way of data representation.)
• SPLENDID: SPARQL Endpoint Federation Exploiting VOID Descriptions  + (AliBaba and DARQ fail to return results fo …
  AliBaba and DARQ fail to return results for six out of the 14 queries for different reasons. AliBaba generates malformed sub queries for CD3, CD5, LS6, and LS7. DARQ can not handle the unbound predicate in CD1 and LS2. For CD3 and CD5 DARQ opens too many connections to GeoNames. All other unsuccessful queries take longer than the time limit of five minutes. Overall, FedX has the best query evaluation performance. The reason is its novel and efficient query execution based on block transmission of result tuples and parallelization of joins. However, there is only a significant difference between FedX and SPLENDID for CD6, CD7, LS3, LS5-7. For the other queries SPLENDID is close to FedX and for CD3 and CD4 even slightly faster, which indicates that SPLENDID, indeed, generates better query execution plans.
  d, generates better query execution plans.)
• Avalanche: Putting the Spirit of the Web back into Semantic Web Querying  + (Avalanche is able to successfully execute …
  Avalanche is able to successfully execute query plans and retrieves many up-to-date results without having any prior knowledge of the data distribution. We, furthermore, see that different objective functions have a significant influence on the outcome and should play a critical role when deployed on the Semantic Web.
  al role when deployed on the Semantic Web.)
• A Semantic Web Middleware for Virtual Data Integration on the Web  + (Because ARQ is using a pipelining concept the response time is very good, even when data has to be retrieved from a remote data source.)
• AgreementMaker: Efficient Matching for Large Real-World Schemas and Ontologies  + (Experiments have shown that our quality measure is usually effective in defining weights for the LWC matcher.)
• LIMES - A Time-Efficient Approach for Large-Scale Link Discovery on the Web of Data  + (LIMES outperforms SILK in all experimental settings. It is important to notice that the difference in performance grows with the (product of the) size of the source and target knowledge bases.)
• Adaptive Integration of Distributed Semantic Web Data  + (No data available now.)
• Optimizing SPARQL Queries over Disparate RDF Data Sources through Distributed Semi-joins  + (No data available now.)
• Discovering and Maintaining Links on the Web of Data  + (No data available now.)
• LogMap: Logic-based and Scalable Ontology Matching  + (No data available now.)
• SERIMI – Resource Description Similarity, RDF Instance Matching and Interlinking  + (No data available now.)
• Accessing and Documenting Relational Databases through OWL Ontologies  + (No data available now.)
• Zhishi.links Results for OAEI 2011  + (No data available now.)
• D2RQ – Treating Non-RDF Databases as Virtual RDF Graphs  + (No data available now.)
• Use of OWL and SWRL for Semantic Relational Database Translation  + (No data available now.)
• DataMaster – a Plug-in for Importing Schemas and Data from Relational Databases into Protégé  + (No data available now.)
• RDB2ONT: A Tool for Generating OWL Ontologies From Relational Database Systems  + (No data available now.)
• From Relational Data to RDFS Models  + (No data available now.)
• Relational.OWL - A Data and Schema Representation Format Based on OWL  + (No data available now.)
• Unveiling the hidden bride: deep annotation for mapping and migrating legacy data to the Semantic Web  + (No data available now.)
• Updating Relational Data via SPARQL/Update  + (No data available now.)
• Bringing Relational Databases into the Semantic Web: A Survey  + (No data available now.)
• Analysing Scholarly Communication Metadata of Computer Science Events  + (No data available now.)
• A Survey of Current Link Discovery Frameworks  + (No data available now.)
• Integration of Scholarly Communication Metadata using Knowledge Graphs  + (No data available now.)
• Cross: an OWL wrapper for teasoning on relational databases  + (No data available now.)
• Towards a Knowledge Graph for Science  + (No data available now.)
• SLINT: A Schema-Independent Linked Data Interlinking System  + (SLINT system totally outperforms the other …
  SLINT system totally outperforms the others on both precision and recall. AgreementMaker has a competitive precision with SLINT on dataset D3 but this system is much lower in recall. Zhishi.Links results on dataset D3 are very high, but the F1 score of SLINT is still 0.05 higher in overall.
  of SLINT is still 0.05 higher in overall.)
• Querying Distributed RDF Data Sources with SPARQL  + (The experiments show that our optimization …
  The experiments show that our optimizations significantly improve query evaluation performance. For query Q1 the execution times of optimized and unoptimized execution are almost the same. This is due to the fact that the query plans for both cases are the same and bind joins of all sub-queries in order of appearance is exact the right strategy. For queries Q2 and Q4 the unoptimized queries took longer than 10 min to answer and timed out, whereas the execution time of the optimized queries is quiet reasonable. The optimized execution of Q1 and Q2 takes almost the same time because Q2 is rewritten into Q1.
  same time because Q2 is rewritten into Q1.)
• A Probabilistic-Logical Framework for Ontology Matching  + (Using stability constraints improves alignment quality with both learned and manually set weights.)
• Querying the Web of Data with Graph Theory-based Techniques  + (We divide evaluation results of GDS, FedX …
  We divide evaluation results of GDS, FedX and DARQ into three categories. First is query performance related metrics. Limited by space, we only provide QPS in this paper7. Second is system loads including CPU usage and memory usage. Third is network overhead including uploading data and downloading data. Here we especially compare GDS with FedX, because DARQ fails providing correct results or is time out on many queries.
  ct results or is time out on many queries.)
• ANAPSID: An Adaptive Query Processing Engine for SPARQL Endpoints  + (We observe that SHJ and ANAPSID operators …
  We observe that SHJ and ANAPSID operators are able to produce the first tuple faster than ARQ or Hash join, even in an ideal scenario with no delays; further, ARQ performance is clearly aff_ected by data transfer distribution and its execution time can be almost two orders of magnitude greater than the time of SHJ or ANAPSID. We notice that SHJ and ANAPSID are competitive, this is because the number of intermediate results is very small, and the benefits of the RJTs cannot be exploited. This suggests that the performance of ANAPSID operators depends on the selectivity of the join operator and the data transfer delays.
  oin operator and the data transfer delays.)
• FedX: Optimization Techniques for Federated Query Processing on Linked Data  + (With our optimization techniques, we are able to reduce the number of requests significantly, e.g., from 170,579 (DARQ) and 93,248 (AliBaba) to just 23 (FedX) for query CD3.)
• Querying over Federated SPARQL Endpoints : A State of the Art Survey  + ({{{Results}}})