Giovanni Tummarello

Invited paper: Sig.ma: Live views on the Web of Data

We present Sig.ma, both a service and an end user application to access the Web of Data as an integrated information space. Sig.ma uses an holistic approach in which large scale semantic Web indexing, logic reasoning, data aggregation heuristics, ad-hoc ontology consolidation, external services and responsive user interaction all play together to create rich entity descriptions. These consolidated entity descriptions then form the base for embeddable data mashups, machine oriented services as well as data browsing services. Finally, we discuss Sig.mas peculiar characteristics and report on lessons learned and ideas it inspires.

Rapid prototyping of semantic mash-ups through semantic web pipes

The use of RDF data published on the Web for applications is still a cumbersome and resource-intensive task due to the limited software support and the lack of standard programming paradigms to deal with everyday problems such as combination of RDF data from dierent sources, object identifier consolidation, ontology alignment and mediation, or plain querying and filtering tasks. In this paper we present a framework, Semantic Web Pipes, that supports fast implementation of Semantic data mash-ups while preserving desirable properties such as abstraction, encapsulation, component-orientation, code re-usability and maintainability which are common and well supported in other application areas.

Web Semantics in the Clouds

Cloud computing refers to the use of large-scale computer clusters often built from low-cost hardware and network equipment, where resources are allocated dynamically among users of the cluster. While the paradigm is not entirely novel, recent developments in software frameworks for cloud computing are making it increasingly easy for programmers to parallelize and thereby scale-up complex data-processing tasks. This article investigates how this trend is impacting the semantic Web field and shows how cloud computing can be used to analyze, query, and reason with the massive amounts of metadata handled by semantic search engines.

Interlinking the Social Web with Semantics

This paper deals with applying semantic Web technologies to the social Web can lead to a social semantic Web, creating a network of interlinked and semantically rich knowledge. One of the most visible trends on the Web is the emergence of social Web sites, which help people create and gather knowledge by simplifying user contributions via blogs, tagging and folksonomies, wikis, podcasts, and online social networks. The social Web has enabled community-based knowledge acquisition.

Searching web data: An entity retrieval and high-performance indexing model

More and more (semi) structured information is becoming available on the web in the form of documents embedding metadata (e.g., RDF, RDFa, Microformats and others). There are already hundreds of millions of such documents accessible and their number is growing rapidly. This calls for large scale systems providing effective means of searching and retrieving this semi-structured information with the ultimate goal of making it exploitable by humans and machines alike. This article examines the shift from the traditional web document model to a web data object (entity) model and studies the challenges faced in implementing a scalable and high performance system for searching semi-structured data objects over a large heterogeneous and decentralised infrastructure. Towards this goal, we define an entity retrieval model, develop novel methodologies for supporting this model and show how to achieve a high-performance entity retrieval system. We introduce an indexing methodology for semi-structured data which offers a good compromise between query expressiveness, query processing and index maintenance compared to other approaches. We address high-performance by optimisation of the index data structure using appropriate compression techniques. Finally, we demonstrate that the resulting system can index billions of data objects and provides keyword-based as well as more advanced search interfaces for retrieving relevant data objects in sub-second time. This work has been part of the Sindice search engine project at the Digital Enterprise Research Institute (DERI), NUI Galway. The Sindice system currently maintains more than 200 million pages downloaded from the web and is being used actively by many researchers within and outside of DERI.

RDFSync: efficient remote synchronization of RDF models

In this paper we describe RDFSync, a methodology for efficient synchronization and merging of RDF models. RDFSync is based on decomposing a model into Minimum Self-Contained graphs (MSGs). After illustrating theory and deriving properties of MSGs, we show how a RDF model can be represented by a list of hashes of such information fragments. The synchronization procedure here described is based on the evaluation and remote comparison of these ordered lists. Experimental results show that the algorithm provides very significant savings on network traffic compared to the file-oriented synchronization of serialized RDF graphs. Finally, we provide the design and report the implementation of a protocol for executing the RDFSync algorithm over HTTP.

Sig.ma: live views on the web of data

We demonstrate Sig.ma, both a service and an end user application to access the Web of Data as an integrated information space. Sig.ma uses an holistic approach in which large scale semantic web indexing, logic reasoning, data aggregation heuristics, ad hoc ontology consolidation, external services and responsive user interaction all play together to create rich entity descriptions. These consolidated entity descriptions then form the base for embeddable data mashups, machine oriented services as well as data browsing services. Finally, we discuss Sig.mas peculiar characteristics and report on lessions learned and ideas it inspires.

Signing individual fragments of an RDF graph

Being able to determine the provenience of statements is a fundamental step in any SW trust modeling. We propose a methodology that allows signing of small groups of RDF statements. Groups of statements signed with this methodology can be safely inserted into any existing triple store without the loss of provenance information since only standard RDF semantics and constructs are used. This methodology has been implemented and is both available as open source library and deployed in a SW P2P project.

Semantic sitemaps: efficient and flexible access to datasets on the semantic web

Increasing amounts of RDF data are available on the Web for consumption by Semantic Web browsers and indexing by Semantic Web search engines. Current Semantic Web publishing practices, however, do not directly support efficient discovery and high-performance retrieval by clients and search engines. We propose an extension to the Sitemaps protocol which provides a simple and effective solution: Data publishers create Semantic Sitemaps to announce and describe their data so that clients can choose the most appropriate access method. We show how this protocol enables an extended notion of authoritative information across different access methods.

Introducing RDF Graph Summary with Application to Assisted SPARQL Formulation

One of the reasons for the slow adoption of SPARQL is the complexity in query formulation due to data diversity. The principal barrier a user faces when trying to formulate a query is that he generally has no information about the underlying structure and vocabulary of the data. In this paper, we address this problem at the maximum scale we can think of: providing assistance in formulating SPARQL queries over the entire Sindice data collection - 15 billion triples and counting coming from more than 300K datasets. We present a method to help users in formulating complex SPARQL queries across multiple heterogeneous data sources. Even if the structure and vocabulary of the data sources are unknown to the user, the user is able to quickly and easily formulate his queries. Our method is based on a summary of the data graph and assists the user during an interactive query formulation by recommending possible structural query elements.