A Configurable Matchmaking Framework for Electronic Marketplaces

E-marketplaces constitute a major enabler of B2B and B2C e-commerce activities. This paper proposes a framework for one of the central activities of e-marketplaces: matchmaking of trading intentions lodged by market participants. The framework identifies a core set of concepts and functions that are common to all types of marketplaces and can serve as the basis for describing the distinct styles of matchmaking employed within various market mechanisms. A prototype implementation of the framework based on Web services technology is presented, illustrating its ability to be dynamically configured to meet specific market needs and its potential to serve as a foundation for more fully fledged e-marketplace frameworks

Lightweight Data Integration Frameworks for Clinical Research

Research data from a single clinical study is often spread across multiple applications and systems. We present a reusable, lightweight, secure framework for automatically integrating and querying study data from heterogeneous sources in order to answer routine, operational questions for researchers

Innovative Evaluation System – IESM: An Architecture for the Database Management System for Mobile Application

As the mobile applications are constantly facing a rapid development in the recent years especially in the academic environment such as student response system [1-8] used in universities and other educational institutions; there has not been reported an effective and scalable Database Management System to support fast and reliable data storage and retrieval. This paper presents Database Management Architecture for an Innovative Evaluation System based on Mobile Learning Applications. The need for a relatively stable, independent and extensible data model for faster data storage and retrieval is analyzed and investigated. It concludes by emphasizing further investigation for high throughput so as to support multimedia data such as video clips, images and documents

A Model-Based Approach to Impact Analysis Using Model Differencing

Impact analysis is concerned with the identification of consequences of changes and is therefore an important activity for software evolution. In modelbased software development, models are core artifacts, which are often used to generate essential parts of a software system. Changes to a model can thus substantially affect different artifacts of a software system. In this paper, we propose a modelbased approach to impact analysis, in which explicit impact rules can be specified in a domain specific language (DSL). These impact rules define consequences of designated UML class diagram changes on software artifacts and the need of dependent activities such as data evolution. The UML class diagram changes are identified automatically using model differencing. The advantage of using explicit impact rules is that they enable the formalization of knowledge about a product. By explicitly defining this knowledge, it is possible to create a checklist with hints about development steps that are (potentially) necessary to manage the evolution. To validate the feasibility of our approach, we provide results of a case study.Comment: 16 pages, 5 figures, In: Proceedings of the 8th International Workshop on Software Quality and Maintainability (SQM), ECEASST Journal, vol. 65 201

AiiDA: Automated Interactive Infrastructure and Database for Computational Science

Computational science has seen in the last decades a spectacular rise in the scope, breadth, and depth of its efforts. Notwithstanding this prevalence and impact, it is often still performed using the renaissance model of individual artisans gathered in a workshop, under the guidance of an established practitioner. Great benefits could follow instead from adopting concepts and tools coming from computer science to manage, preserve, and share these computational efforts. We illustrate here our paradigm sustaining such vision, based around the four pillars of Automation, Data, Environment, and Sharing. We then discuss its implementation in the open-source AiiDA platform (http://www.aiida.net), that has been tuned first to the demands of computational materials science. AiiDA's design is based on directed acyclic graphs to track the provenance of data and calculations, and ensure preservation and searchability. Remote computational resources are managed transparently, and automation is coupled with data storage to ensure reproducibility. Last, complex sequences of calculations can be encoded into scientific workflows. We believe that AiiDA's design and its sharing capabilities will encourage the creation of social ecosystems to disseminate codes, data, and scientific workflows.Comment: 30 pages, 7 figure