Hypermedia-based discovery for source selection using low-cost linked data interfaces

Evaluating federated Linked Data queries requires consulting multiple sources on the Web. Before a client can execute queries, it must discover data sources, and determine which ones are relevant. Federated query execution research focuses on the actual execution, while data source discovery is often marginally discussed-even though it has a strong impact on selecting sources that contribute to the query results. Therefore, the authors introduce a discovery approach for Linked Data interfaces based on hypermedia links and controls, and apply it to federated query execution with Triple Pattern Fragments. In addition, the authors identify quantitative metrics to evaluate this discovery approach. This article describes generic evaluation measures and results for their concrete approach. With low-cost data summaries as seed, interfaces to eight large real-world datasets can discover each other within 7 minutes. Hypermedia-based client-side querying shows a promising gain of up to 50% in execution time, but demands algorithms that visit a higher number of interfaces to improve result completeness

Logic programming and metadata specifications

Artificial intelligence (AI) ideas and techniques are critical to the development of intelligent information systems that will be used to collect, manipulate, and retrieve the vast amounts of space data produced by 'Missions to Planet Earth.' Natural language processing, inference, and expert systems are at the core of this space application of AI. This paper presents logic programming as an AI tool that can support inference (the ability to draw conclusions from a set of complicated and interrelated facts). It reports on the use of logic programming in the study of metadata specifications for a small problem domain of airborne sensors, and the dataset characteristics and pointers that are needed for data access

Grids and the Virtual Observatory

We consider several projects from astronomy that benefit from the Grid paradigm and associated technology, many of which involve either massive datasets or the federation of multiple datasets. We cover image computation (mosaicking, multi-wavelength images, and synoptic surveys); database computation (representation through XML, data mining, and visualization); and semantic interoperability (publishing, ontologies, directories, and service descriptions)

Publishing metadata of geospatial indicators as Linked Open Data: a policy-oriented approach

Ponencias, comunicaciones y pósters presentados en el 17th AGILE Conference on Geographic Information Science "Connecting a Digital Europe through Location and Place", celebrado en la Universitat Jaume I del 3 al 6 de junio de 2014.Geospatial indicators are becoming increasingly important for governments in monitoring and underpinning policy planning and political decision making. Currently, the discovery, viewing and sharing of these indicators is often made possible through geoportals that are developed according the concepts of Spatial Data Infrastructures (SDIs). However, this type of ‘business information’ exceeds the scope of traditional SDIs that solely focus on the common spatial aspects constituting a generic location context. The concept of an ‘augmented’ SDI adopting Linked Data principles reveals meanwhile much potential in integrating disparate reference and non-spatial business data but requires a formal revision of underlying standards. In this study we propose an alternative and policy-oriented viewpoint for publishing geospatial indicators as Linked Open Data. Focussing on metadata, we have elaborated a profile of the Data Catalog Vocabulary (DCAT) for describing geospatial indicators, including additional information on the related policy assessments, spatial characteristics, the provenance, and the measurement variables and dimensions of indicators. By implementing the vocabulary in an existing monitoring system it allows us to discuss the benefits and drawbacks of this approach

Extending the 5S Framework of Digital Libraries to support Complex Objects, Superimposed Information, and Content-Based Image Retrieval Services

Advanced services in digital libraries (DLs) have been developed and widely used to address the required capabilities of an assortment of systems as DLs expand into diverse application domains. These systems may require support for images (e.g., Content-Based Image Retrieval), Complex (information) Objects, and use of content at fine grain (e.g., Superimposed Information). Due to the lack of consensus on precise theoretical definitions for those services, implementation efforts often involve ad hoc development, leading to duplication and interoperability problems. This article presents a methodology to address those problems by extending a precisely specified minimal digital library (in the 5S framework) with formal definitions of aforementioned services. The theoretical extensions of digital library functionality presented here are reinforced with practical case studies as well as scenarios for the individual and integrative use of services to balance theory and practice. This methodology has implications that other advanced services can be continuously integrated into our current extended framework whenever they are identified. The theoretical definitions and case study we present may impact future development efforts and a wide range of digital library researchers, designers, and developers

In the Name of the Name : RDF Literals, ER Attributes, and the Potential to Rethink the Structures and Visualizations of Catalogs

The aim of this study is to contribute to the field of machine-processable bibliographic data that is suitable for the Semantic Web. We examine the Entity Relationship (ER) model, which has been selected by IFLA as a “conceptual framework” in order to model the FR family (FRBR, FRAD, and RDA), and the problems ER causes as we move towards the Semantic Web. Subsequently, while maintaining the semantics of the aforementioned standards but rejecting the ER as a conceptual framework for bibliographic data, this paper builds on the RDF (Resource Description Framework) potential and documents how both the RDF and Linked Data’s rationale can affect the way we model bibliographic data. In this way, a new approach to bibliographic data emerges where the distinction between description and authorities is obsolete. Instead, the integration of the authorities with descriptive information becomes fundamental so that a network of correlations can be established between the entities and the names by which the entities are known. Naming is a vital issue for human cultures because names are not random sequences of characters or sounds that stand just as identifiers for the entities—they also have socio-cultural meanings and interpretations. Thus, instead of describing indivisible resources, we could describe entities that appear in a variety of names on various resources. In this study, a method is proposed to connect the names with the entities they represent and, in this way, to document the provenance of these names by connecting specific resources with specific names

Knowledge Representation with Ontologies: The Present and Future

Recently, we have seen an explosion of interest in ontologies as artifacts to represent human knowledge and as critical components in knowledge management, the semantic Web, business-to-business applications, and several other application areas. Various research communities commonly assume that ontologies are the appropriate modeling structure for representing knowledge. However, little discussion has occurred regarding the actual range of knowledge an ontology can successfully represent