2010

• Cosmin Basca, Abraham Bernstein, Avalanche - Putting the Spirit of the Web back into Semantic Web Querying. (conference/Demo)
  
  Traditionally Semantic Web applications either included a web crawler or relied on external services to gain access to the Web of Data. Recent efforts, have enabled applications to query the entire Se- mantic Web for up-to-date results. Such approaches are based on either centralized indexing of semantically annotated metadata or link traversal and URI dereferencing as in the case of Linked Open Data. They pose a number of limiting assumptions, thus breaking the openness principle of the Web. In this demo we present a novel technique called Avalanche, designed to allow a data surfer to query the Semantic Web transpar- ently. The technique makes no prior assumptions about data distribu- tion. Specifically, Avalanche can perform ?live? queries over the Web of Data. First, it gets on-line statistical information about the data dis- tribution, as well as bandwidth availability. Then, it plans and executes the query in a distributed manner trying to quickly provide first answers.
  
• Cosmin Basca, Abraham Bernstein, Avalanche: Putting the Spirit of the Web back into Semantic Web Querying, Proceedings Of The 6th International Workshop On Scalable Semantic Web Knowledge Base Systems (SSWS2010), Editor(s): Achille Fokoue, Thorsten Liebig, Yuanbo Guo, November ; 2010. (inproceedings/full paper)
  
  Traditionally Semantic Web applications either included a web crawler or relied on external services to gain access to the Web of Data. Recent efforts have enabled applications to query the entire Se- mantic Web for up-to-date results. Such approaches are based on either centralized indexing of semantically annotated metadata or link traver- sal and URI dereferencing as in the case of Linked Open Data. By mak- ing limiting assumptions about the information space, they violate the openness principle of the Web ? a key factor for its ongoing success. In this article we propose a technique called Avalanche, designed to allow a data surfer to query the Semantic Web transparently without making any prior assumptions about the distribution of the data ? thus adhering to the openness criteria. Specifically, Avalanche can perform ?live? (SPARQL) queries over the Web of Data. First, it gets on-line statistical information about the data distribution, as well as bandwidth availability. Then, it plans and executes the query in a distributed man- ner trying to quickly provide first answers. The main contribution of this paper is the presentation of this open and distributed SPARQL querying approach. Furthermore, we propose to extend the query planning algo- rithm with qualitative statistical information. We empirically evaluate Avalanche using a realistic dataset, show its strengths but also point out the challenges that still exist.
  
• Minh Khoa Nguyen, Cosmin Basca, Abraham Bernstein, B+Hash Tree: Optimizing query execution times for on-Disk Semantic Web data structures, Proceedings Of The 6th International Workshop On Scalable Semantic Web Knowledge Base Systems (SSWS2010), Editor(s): Achille Fokoue, Thorsten Liebig, Yuanbo Guo, November ; 2010. (inproceedings/full paper)
  
  The increasing growth of the Semantic Web has substantially enlarged the amount of data available in RDF format. One proposed so- lution is to map RDF data to relational databases (RDBs). The lack of a common schema, however, makes this mapping inefficient. Some RDF-native solutions use B+Trees, which are potentially becoming a bottleneck, as the single key-space approach of the Semantic Web may even make their O(log(n)) worst case performance too costly. Alterna- tives, such as hash-based approaches, suffer from insufficient update and scan performance. In this paper we propose a novel type of index struc- ture called a B+Hash Tree, which combines the strengths of traditional B-Trees with the speedy constant-time lookup of a hash-based structure. Our main research idea is to enhance the B+Tree with a Hash Map to enable constant retrieval time instead of the common logarithmic one of the B+Tree. The result is a scalable, updatable, and lookup-optimized, on-disk index-structure that is especially suitable for the large key-spaces of RDF datasets. We evaluate the approach against existing RDF index- ing schemes using two commonly used datasets and show that a B+Hash Tree is at least twice as fast as its competitors ? an advantage that we show should grow as dataset sizes increase.
  
• Cosmin Basca, Robert H. Warren, Abraham Bernstein, Canopener: Recycling Old and New Data, 3rd Workshop on Mashups, Enterprise Mashups and Lightweight Composition on the Web (MEM 2010), April 2010. (inproceedings/full paper)
  
  The advent of social markup languages and lightweight pub- lic data access methods has created an opportunity to share the social, documentary and system information locked in most servers as a mashup. Whereas solutions already exists for creating and managing mashups from network sources, we propose here a mashup framework whose primary infor- mation sources are the applications and user files of a server. This enables us to use server legacy data sources that are already maintained as part of basic administration to se- mantically link user documents and accounts using social web constructs.
  

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