Italian center for Astronomical Archives publishing solution: modular and distributed

The Italian center for Astronomical Archives tries to provide astronomical data resources as interoperable services based on IVOA standards. Its VO expertise and knowledge comes from active participation within IVOA and VO at European and international level, with a double-fold goal: learn from the collaboration and provide inputs to the community. The first solution to build an easy to configure and maintain resource publisher conformant to VO standards proved to be too optimistic. For this reason it has been necessary to re-think the architecture with a modular system built around the messaging concept, where each modular component speaks to the other interested parties through a system of broker-managed queues. The first implemented protocol, the Simple Cone Search, shows the messaging task architecture connecting the parametric HTTP interface to the database backend access module, the logging module, and allows multiple cone search resources to be managed together through a configuration manager module. Even if relatively young, it already proved the flexibility required by the overall system when the database backend changed from MySQL to PostgreSQL+PgSphere. Another implementation test has been made to leverage task distribution over multiple servers to serve simultaneously: FITS cubes direct linking, cubes cutout and cubes positional merging. Currently the implementation of the SIA-2.0 standard protocol is ongoing while for TAP we will be adapting the TAPlib library. Alongside these tools a first administration tool (TASMAN) has been developed to ease the build up and maintenance of TAP_SCHEMA-ta including also ObsCore maintenance capability. Future work will be devoted at widening the range of VO protocols covered by the set of available modules, improve the configuration management and develop specific purpose modules common to all the service components.Comment: SPIE Astronomical Telescopes + Instrumentation 2018, Software and Cyberinfrastructure for Astronomy V, pre-publishing draft proceeding (reduced abstract

Core Services in the Architecture of the National Digital Library for Science Education (NSDL)

We describe the core components of the architecture for the (NSDL) National Science, Mathematics, Engineering, and Technology Education Digital Library. Over time the NSDL will include heterogeneous users, content, and services. To accommodate this, a design for a technical and organization infrastructure has been formulated based on the notion of a spectrum of interoperability. This paper describes the first phase of the interoperability infrastructure including the metadata repository, search and discovery services, rights management services, and user interface portal facilities

Towards adaptive e-learning applications based on Semantic Web Services

The current state of the art in supporting E-Learning objectives is primarily based on providing a learner with learning content by using metadata standards like ADL SCORM 2004 or IMS Learning Design. By following this approach, several issues can be observed including high development costs due to a limited reusability across different standards and learning contexts. To overcome these issues, our approach changes this data-centric paradigm to a highly dynamic service-oriented approach. By following this approach, learning objectives are supported based on a automatic allocation of services instead of a manual composition of learning data. Our approach is fundamentally based on current Semantic Web Service (SWS) technology and considers mappings between different learning metadata standards as well as ontological concepts for E-Learning. Since our approach is based on a dynamic selection and invocation of SWS appropriate to achieve a given learning objective within a specific learning context, it enables the dynamic adaptation to specific learning needs as well as a high level of reusability across different learning contexts

A semantic web services-based infrastructure for context-adaptive process support

Current technologies aimed at supporting processes whether it is a business or learning process - primarily follow a metadata- and data-centric paradigm. Whereas process metadata is usually based on a specific standard specification - such as the Business Process Modeling Notation (BPMN) or the IMS Learning Design Standard - the allocation of resources is done manually at design-time, and the used data is often specific to one process context only. These facts limit the reusability of process models across different standards and contexts. To overcome these issues, we introduce an innovative Semantic Web Service-based framework aimed at changing the current paradigm to a context-adaptive service-oriented approach. Following the idea of layered semantic abstractions, our approach supports the development of abstract semantic process model - reusable across different contexts and standards - that enables a dynamic adaptation to specific actor needs and objectives. To illustrate the application of our framework and establish its feasibility, we describe a prototypical application in the E-Learning domain

Adressing context-awareness and standards interoperability in e-learning: a service-oriented framework based on IRS III

Current technologies aimed at supporting learning goals primarily follow a data and metadata-centric paradigm. They provide the learner with appropriate learning content packages containing the learning process description as well as the learning resources. Whereas process metadata is usually based on a certain standard specification – such as ADL SCORM or the IMS Learning Design – the used learning resources – data or services - are specific to pre-defined learning contexts, and they are allocated manually at design-time. Therefore, a content package cannot consider the actual learning context, since this is only known at runtime of a learning process. These facts limit the reusability of a content package across different standards and contexts. To overcome these issues, this paper proposes an innovative Semantic Web Service-based approach that changes this data- and metadata-based paradigm to a context-adaptive service-oriented approach. In this approach, the learning process is semantically described as a standard-independent process model decomposed into several learning goals. These goals are accomplished at runtime, based on the automatic allocation of the most appropriate service. As a result, we address the dynamic adaptation to specific context and - providing the appropriate mappings to established metadata standards - we enable the reuse of the defined semantic learning process model across different standards. To illustrate the application of our approach and to prove its feasibility, a prototypical application based on an initial use case scenario is proposed

Context-adaptive learning designs by using semantic web services

IMS Learning Design (IMS-LD) is a promising technology aimed at supporting learning processes. IMS-LD packages contain the learning process metadata as well as the learning resources. However, the allocation of resources - whether data or services - within the learning design is done manually at design-time on the basis of the subjective appraisals of a learning designer. Since the actual learning context is known at runtime only, IMS-LD applications cannot adapt to a specific context or learner. Therefore, the reusability is limited and high development costs have to be taken into account to support a variety of contexts. To overcome these issues, we propose a highly dynamic approach based on Semantic Web Services (SWS) technology. Our aim is moving from the current data- and metadata-based to a context-adaptive service-orientated paradigm We introduce semantic descriptions of a learning process in terms of user objectives (learning goals) to abstract from any specific metadata standards and used learning resources. At runtime, learning goals are accomplished by automatically selecting and invoking the services that fit the actual user needs and process contexts. As a result, we obtain a dynamic adaptation to different contexts at runtime. Semantic mappings from our standard-independent process models will enable the automatic development of versatile, reusable IMS-LD applications as well as the reusability across multiple metadata standards. To illustrate our approach, we describe a prototype application based on our principles