Open Access Metadata for Journals in Directory of Open Access Journals: Who, How, and What Scheme?

Open access (OA) is a form of publication that allows some level of free access to scholarly publications. The Directory of Open Access Journals (DOAJ) is a repository to which OA journals may apply and upload content to increase discoverability. OA also refers to metadata that is freely available for harvesting. In making metadata open access, standards for schemes and protocols are needed to facilitate interoperability. For open access journals, such as those listed in the DOAJ, providing open access metadata in a form that promotes interoperability is essential for discoverability of their content. This paper investigates what standards exist or are emerging, who within journals is creating the metadata for DOAJ journals, and how are those journals and DOAJ sharing the metadata for articles. Moreover, since creating metadata requires specialized knowledge of both librarians and programmers, it is imperative that journals wanting to publish with OA metadata formulate plans to coordinate these experts and to be sure their efforts are compatible with current standards and protocols

The MMT API: A Generic MKM System

The MMT language has been developed as a scalable representation and interchange language for formal mathematical knowledge. It permits natural representations of the syntax and semantics of virtually all declarative languages while making MMT-based MKM services easy to implement. It is foundationally unconstrained and can be instantiated with specific formal languages. The MMT API implements the MMT language along with multiple backends for persistent storage and frontends for machine and user access. Moreover, it implements a wide variety of MMT-based knowledge management services. The API and all services are generic and can be applied to any language represented in MMT. A plugin interface permits injecting syntactic and semantic idiosyncrasies of individual formal languages.Comment: Conferences on Intelligent Computer Mathematics (CICM) 2013 The final publication is available at http://link.springer.com

Distributing workflows over a ubiquitous P2P network

This paper discusses issues in the distribution of bundled workflows across ubiquitous peer-to-peer networks for the application of music information retrieval. The underlying motivation for this work is provided by the DART project, which aims to develop a novel music recommendation system by gathering statistical data using collaborative filtering techniques and the analysis of the audio itsel, in order to create a reliable and comprehensive database of the music that people own and which they listen to. To achieve this, the DART scientists creating the algorithms need the ability to distribute the Triana workflows they create, representing the analysis to be performed, across the network on a regular basis (perhaps even daily) in order to update the network as a whole with new workflows to be executed for the analysis. DART uses a similar approach to BOINC but differs in that the workers receive input data in the form of a bundled Triana workflow, which is executed in order to process any MP3 files that they own on their machine. Once analysed, the results are returned to DART's distributed database that collects and aggregates the resulting information. DART employs the use of package repositories to decentralise the distribution of such workflow bundles and this approach is validated in this paper through simulations that show that suitable scalability is maintained through the system as the number of participants increases. The results clearly illustrate the effectiveness of the approach

New generation E-learning technology by Web Services.

This paper discusses a new approach to build infrastructures for E-Learning systems for Learning Software Organizations on the basis of Web Services. A requirements context is developed to determine which type of E-Learning applications that can be Web Service Enabled. This is illustrated with a case study on an Encapsulated Software Teaching Environment. Additional facilities, such as didactical agents and deep personalization to facilitate Learning Software Organizations are discussed at the end.

Development of grid frameworks for clinical trials and epidemiological studies

E-Health initiatives such as electronic clinical trials and epidemiological studies require access to and usage of a range of both clinical and other data sets. Such data sets are typically only available over many heterogeneous domains where a plethora of often legacy based or in-house/bespoke IT solutions exist. Considerable efforts and investments are being made across the UK to upgrade the IT infrastructures across the National Health Service (NHS) such as the National Program for IT in the NHS (NPFIT) [1]. However, it is the case that currently independent and largely non-interoperable IT solutions exist across hospitals, trusts, disease registries and GP practices – this includes security as well as more general compute and data infrastructures. Grid technology allows issues of distribution and heterogeneity to be overcome, however the clinical trials domain places special demands on security and data which hitherto the Grid community have not satisfactorily addressed. These challenges are often common across many studies and trials hence the development of a re-usable framework for creation and subsequent management of such infrastructures is highly desirable. In this paper we present the challenges in developing such a framework and outline initial scenarios and prototypes developed within the MRC funded Virtual Organisations for Trials and Epidemiological Studies (VOTES) project [2]