Model Theory and Entailment Rules for RDF Containers, Collections and Reification

An RDF graph is, at its core, just a set of statements consisting of subjects, predicates and objects. Nevertheless, since its inception practitioners have asked for richer data structures such as containers (for open lists, sets and bags), collections (for closed lists) and reification (for quoting and provenance). Though this desire has been addressed in the RDF primer and RDF Schema specification, they are explicitely ignored in its model theory. In this paper we formalize the intuitive semantics (as suggested by the RDF primer, the RDF Schema and RDF semantics specifications) of these compound data structures by two orthogonal extensions of the RDFS model theory (RDFCC for RDF containers and collections, and RDFR for RDF reification). Second, we give a set of entailment rules that is sound and complete for the RDFCC and RDFR model theories. We show that complexity of RDFCC and RDFR entailment remains the same as that of simple RDF entailment

Interoperability between Multimedia Collections for Content and Metadata-Based Searching

Artiste is a European project developing a cross-collection search system for art galleries and museums. It combines image content retrieval with text based retrieval and uses RDF mappings in order to integrate diverse databases. The test sites of the Louvre, Victoria and Albert Museum, Uffizi Gallery and National Gallery London provide their own database schema for existing metadata, avoiding the need for migration to a common schema. The system will accept a query based on one museum’s fields and convert them, through an RDF mapping into a form suitable for querying the other collections. The nature of some of the image processing algorithms means that the system can be slow for some computations, so the system is session-based to allow the user to return to the results later. The system has been built within a J2EE/EJB framework, using the Jboss Enterprise Application Server

Exploring manuscripts: sharing ancient wisdoms across the semantic web

Recent work in digital humanities has seen researchers in-creasingly producing online editions of texts and manuscripts, particularly in adoption of the TEI XML format for online publishing. The benefits of semantic web techniques are un-derexplored in such research, however, with a lack of sharing and communication of research information. The Sharing Ancient Wisdoms (SAWS) project applies linked data prac-tices to enhance and expand on what is possible with these digital text editions. Focussing on Greek and Arabic col-lections of ancient wise sayings, which are often related to each other, we use RDF to annotate and extract seman-tic information from the TEI documents as RDF triples. This allows researchers to explore the conceptual networks that arise from these interconnected sayings. The SAWS project advocates a semantic-web-based methodology, en-hancing rather than replacing current workflow processes, for digital humanities researchers to share their findings and collectively benefit from each other’s work

LODE: Linking Digital Humanities Content to the Web of Data

Numerous digital humanities projects maintain their data collections in the form of text, images, and metadata. While data may be stored in many formats, from plain text to XML to relational databases, the use of the resource description framework (RDF) as a standardized representation has gained considerable traction during the last five years. Almost every digital humanities meeting has at least one session concerned with the topic of digital humanities, RDF, and linked data. While most existing work in linked data has focused on improving algorithms for entity matching, the aim of the LinkedHumanities project is to build digital humanities tools that work "out of the box," enabling their use by humanities scholars, computer scientists, librarians, and information scientists alike. With this paper, we report on the Linked Open Data Enhancer (LODE) framework developed as part of the LinkedHumanities project. With LODE we support non-technical users to enrich a local RDF repository with high-quality data from the Linked Open Data cloud. LODE links and enhances the local RDF repository without compromising the quality of the data. In particular, LODE supports the user in the enhancement and linking process by providing intuitive user-interfaces and by suggesting high-quality linking candidates using tailored matching algorithms. We hope that the LODE framework will be useful to digital humanities scholars complementing other digital humanities tools

SWI-Prolog and the Web

Where Prolog is commonly seen as a component in a Web application that is either embedded or communicates using a proprietary protocol, we propose an architecture where Prolog communicates to other components in a Web application using the standard HTTP protocol. By avoiding embedding in external Web servers development and deployment become much easier. To support this architecture, in addition to the transfer protocol, we must also support parsing, representing and generating the key Web document types such as HTML, XML and RDF. This paper motivates the design decisions in the libraries and extensions to Prolog for handling Web documents and protocols. The design has been guided by the requirement to handle large documents efficiently. The described libraries support a wide range of Web applications ranging from HTML and XML documents to Semantic Web RDF processing. To appear in Theory and Practice of Logic Programming (TPLP)Comment: 31 pages, 24 figures and 2 tables. To appear in Theory and Practice of Logic Programming (TPLP

Crossing the Curatorial Chasm - Lessons from the FACADE project

4th International Conference on Open RepositoriesThis presentation was part of the session : Conference PresentationsDate: 2009-05-19 01:00 PM – 02:30 PMThe FACADE project was tasked with developing a preservation strategy and program for proprietary, complex 3D CAD models used in architecture and design. In achieving this goal, the project created an expressive object model as an RDF ontology, wrote numerous curatorial applications to assist project comprehension and metadata creation, devised techniques for processing collections at large scale, and designed compelling visualization and discovery user interfaces. Actual instance collections were ingested into DSpace, and UIs manifested from them.Institute of Museum and Library Service

Image annotation with Photocopain

Photo annotation is a resource-intensive task, yet is increasingly essential as image archives and personal photo collections grow in size. There is an inherent conflict in the process of describing and archiving personal experiences, because casual users are generally unwilling to expend large amounts of effort on creating the annotations which are required to organise their collections so that they can make best use of them. This paper describes the Photocopain system, a semi-automatic image annotation system which combines information about the context in which a photograph was captured with information from other readily available sources in order to generate outline annotations for that photograph that the user may further extend or amend

GraphX: Unifying Data-Parallel and Graph-Parallel Analytics

From social networks to language modeling, the growing scale and importance of graph data has driven the development of numerous new graph-parallel systems (e.g., Pregel, GraphLab). By restricting the computation that can be expressed and introducing new techniques to partition and distribute the graph, these systems can efficiently execute iterative graph algorithms orders of magnitude faster than more general data-parallel systems. However, the same restrictions that enable the performance gains also make it difficult to express many of the important stages in a typical graph-analytics pipeline: constructing the graph, modifying its structure, or expressing computation that spans multiple graphs. As a consequence, existing graph analytics pipelines compose graph-parallel and data-parallel systems using external storage systems, leading to extensive data movement and complicated programming model. To address these challenges we introduce GraphX, a distributed graph computation framework that unifies graph-parallel and data-parallel computation. GraphX provides a small, core set of graph-parallel operators expressive enough to implement the Pregel and PowerGraph abstractions, yet simple enough to be cast in relational algebra. GraphX uses a collection of query optimization techniques such as automatic join rewrites to efficiently implement these graph-parallel operators. We evaluate GraphX on real-world graphs and workloads and demonstrate that GraphX achieves comparable performance as specialized graph computation systems, while outperforming them in end-to-end graph pipelines. Moreover, GraphX achieves a balance between expressiveness, performance, and ease of use