Exploring user and system requirements of linked data visualization through a visual dashboard approach

One of the open problems in SemanticWeb research is which tools should be provided to users to explore linked data. This is even more urgent now that massive amount of linked data is being released by governments worldwide. The development of single dedicated visualization applications is increasing, but the problem of exploring unknown linked data to gain a good understanding of what is contained is still open. An effective generic solution must take into account the user’s point of view, their tasks and interaction, as well as the system’s capabilities and the technical constraints the technology imposes. This paper is a first step in understanding the implications of both, user and system by evaluating our dashboard-based approach. Though we observe a high user acceptance of the dashboard approach, our paper also highlights technical challenges arising out of complexities involving current infrastructure that need to be addressed while visualising linked data. In light of the findings, guidelines for the development of linked data visualization (and manipulation) are provided

Configuring Semantic Web Interfaces by Data Mapping

We demonstrate how to develop Web-based user interfaces for Semantic Web applications using commonly available, off-the-shelf Web widget libraries. By formally defining the underlying data model that is assumed by these widgets, Semantic Web application developers can use familiar RDF constructs to map their own data to the model implemented by the Widgets. As an example, we briefly describe the interface model underlying our own framework, and provide concrete examples showing how it has been used to create Semantic Web applications in two different domains. We conclude by discussing the advantages and limitations of our approach

BlogForever D2.6: Data Extraction Methodology

This report outlines an inquiry into the area of web data extraction, conducted within the context of blog preservation. The report reviews theoretical advances and practical developments for implementing data extraction. The inquiry is extended through an experiment that demonstrates the effectiveness and feasibility of implementing some of the suggested approaches. More specifically, the report discusses an approach based on unsupervised machine learning that employs the RSS feeds and HTML representations of blogs. It outlines the possibilities of extracting semantics available in blogs and demonstrates the benefits of exploiting available standards such as microformats and microdata. The report proceeds to propose a methodology for extracting and processing blog data to further inform the design and development of the BlogForever platform

Proceedings of the First International Workshop on Mashup Personal Learning Environments

Wild, F., Kalz, M., & Palmér, M. (Eds.) (2008). Proceedings of the First International Workshop on Mashup Personal Learning Environments (MUPPLE08). September, 17, 2008, Maastricht, The Netherlands: CEUR Workshop Proceedings, ISSN 1613-0073. Available at http://ceur-ws.org/Vol-388.The work on this publication has been sponsored by the TENCompetence Integrated Project (funded by the European Commission's 6th Framework Programme, priority IST/Technology Enhanced Learning. Contract 027087 [http://www.tencompetence.org]) and partly sponsored by the LTfLL project (funded by the European Commission's 7th Framework Programme, priority ISCT. Contract 212578 [http://www.ltfll-project.org

Thesaurus-based search in large heterogeneous collections

In cultural heritage, large virtual collections are coming into existence. Such collections contain heterogeneous sets of metadata and vocabulary concepts, originating from multiple sources. In the context of the E-Culture demonstrator we have shown earlier that such virtual collections can be effectively explored with keyword search and semantic clustering. In this paper we describe the design rationale of ClioPatria, an open-source system which provides APIs for scalable semantic graph search. The use of ClioPatria’s search strategies is illustrated with a realistic use case: searching for ”Picasso”. We discuss details of scalable graph search, the required OWL reasoning functionalities and show why SPARQL queries are insufficient for solving the search problem

Local Radiance

Recent years have seen a proliferation of web applications based on content management systems (CMS). Using a CMS, non-technical content authors are able to define custom content types to support their needs. These content type names and the attribute names in each content type are typically domain-specific and meaningful to the content authors. The ability of a CMS to support a multitude of content types allows for endless creation and customization but also leads to a large amount of heterogeneity within a single application. While this meaningful heterogeneity is beneficial, it introduces the problem of how to write reusable functionality (e.g., general purpose widgets) that can work across all the different types. Traditional information integration can solve the problem of schema heterogeneity by defining a single global schema that captures the shared semantics of the heterogeneous (local) schemas. Functionality and queries can then be written against the global schema and return data from local sources in the form of the global schema, but the meaningful local semantics (such as type and attribute names) are not returned. Mappings are also complex and require skilled developers to create. Here we propose a system that we call \textit{local radiance} (LR) that captures both global shared semantics as well as local, beneficial heterogeneity. We provide a formal definition of our system that includes domain structures---small, global schema fragments that represent shared domain-specific semantics--- and canonical structures---domain-independent global schema fragments used to build generic global widgets. We define mappings between local, domain, and canonical levels. Our query language extends the relational algebra to support queries that radiate local semantics to the domain and canonical levels as well as inserting and updating heterogeneous local data from generic global widgets. We characterize the expressive power of our mapping language and show how it can be used to perform complex data and metadata transformations. Through a user study, we evaluate the ability of non-technical users to perform mapping tasks and find that it is both understandable and usable. We report on the ongoing development (in CMSs and a relational database) of LR systems, demonstrate how widgets can be built using local radiance, and show how LR is being used in a number of online public educational repositories

enabling a research data management beyond data heterogeneity

A primary goal of a research infrastructure for data management should be to enable efficient data discovery and integration of heterogeneous data. The German Federation for Biological Data (GFBio) was envisioned by this goal. The basic component, that enables such interoperability and serves as a backbone for such a platform, is the GFBio Terminology Service (GFBio TS). It acts as a semantic platform for accessing, developing and reasoning over terminological resources within the biological and environmental domain. A RESTful API gives access to these terminological resources in a uniform way regardless of their degree of complexity and whether they are internally stored or externally accessed through their web services. Additionally, a set of widgets with an intrinsic API connection are made available for an easy integration in applications and web interfaces. Based on the requirements of the GFBio partners, we describe the added value that is provided by the GFBio Terminology Service with practical scenarios but also, what challenges we still face. We conclude by describing our current activities and future developments

MACE – Enriching Architectural Learning Objects for Experience Multiplication.

Stefaner, M., Dalla Vecchia, E., Condotta, M., Wolpers, M., Specht, M., Apelt, M., Duval, E. (2007) MACE – Enriching Architectural Learning Objects for Experience Multiplication. In: Duval, E., Klamma, R., & Wolpers, M. (eds.) EC-TEL 2007. LNCS 4753; Berlin, Heidelberg: Springer; pp. 322-336.Education in architecture requires access to a broad range of architectural learning material to develop flexibility and creativity in design. The learning material is compromised of digital information captured in textual and visual media including single images, videos, description of architectural concepts or complete architectural projects, i.e. digital artifacts on different aggregation levels. The repositories storing such information are not interrelated and do not provide unified access so that retrieval of architectural learning objects is cumbersome and time consuming. In this paper, we describe how an infrastructure of federated architectural learning repositories will provide unique, integrated access facilities for high quality architectural content. The integration of various types of content, usage, social and contextual metadata enables users to develop multiple perspectives and navigation paths that support experience multiplication for the user. A service– oriented software architecture that is based on open standards, and a flexible user interface design solutions based on widgets ensure easy integration and re- combinability of contents, metadata and functionalities

Generating collaborative systems for digital libraries: A model-driven approach

This is an open access article shared under a Creative Commons Attribution 3.0 Licence (http://creativecommons.org/licenses/by/3.0/). Copyright @ 2010 The Authors.The design and development of a digital library involves different stakeholders, such as: information architects, librarians, and domain experts, who need to agree on a common language to describe, discuss, and negotiate the services the library has to offer. To this end, high-level, language-neutral models have to be devised. Metamodeling techniques favor the definition of domainspecific visual languages through which stakeholders can share their views and directly manipulate representations of the domain entities. This paper describes CRADLE (Cooperative-Relational Approach to Digital Library Environments), a metamodel-based framework and visual language for the definition of notions and services related to the development of digital libraries. A collection of tools allows the automatic generation of several services, defined with the CRADLE visual language, and of the graphical user interfaces providing access to them for the final user. The effectiveness of the approach is illustrated by presenting digital libraries generated with CRADLE, while the CRADLE environment has been evaluated by using the cognitive dimensions framework