Sciunits: Reusable Research Objects

Science is conducted collaboratively, often requiring knowledge sharing about computational experiments. When experiments include only datasets, they can be shared using Uniform Resource Identifiers (URIs) or Digital Object Identifiers (DOIs). An experiment, however, seldom includes only datasets, but more often includes software, its past execution, provenance, and associated documentation. The Research Object has recently emerged as a comprehensive and systematic method for aggregation and identification of diverse elements of computational experiments. While a necessary method, mere aggregation is not sufficient for the sharing of computational experiments. Other users must be able to easily recompute on these shared research objects. In this paper, we present the sciunit, a reusable research object in which aggregated content is recomputable. We describe a Git-like client that efficiently creates, stores, and repeats sciunits. We show through analysis that sciunits repeat computational experiments with minimal storage and processing overhead. Finally, we provide an overview of sharing and reproducible cyberinfrastructure based on sciunits gaining adoption in the domain of geosciences

Building a Systematic Legacy System Modernization Approach

A systematic legacy system modernizing approach represents a new approach for modernizing legacy systems. Systematic legacy system modernization has software reuse as an integral part of modernization. We have developed a modernization approach which uses software architecture reconstruction to find reusable components within the legacy system. The practice of software development and modernization continues to shift towards the reuse of components from legacy systems to handle the complexities of software development. Modernization of a legacy system requires reuse of software artefacts from legacy system to conserve the business rules and improve the system’s quality attributes. Software reuse is an integral part of our systematic legacy modernization approach. Software should be considered as an asset and reuse of these assets is essential to increase the return on the development costs. Software reuse ranges from reuse of ideas to algorithms to any documents that are created during the software development life cycle. Software reuse has many potential benefits which include increased software quality, and decreased software development cost and time. Demands for lower software production and maintenance costs, faster delivery of systems and increased quality can only be met by widespread and systematic software reuse. In spite of all these benefits software reuse adoption is not widespread in the software development communities. Software reuse cannot possibly become an engineering discipline so long as issues and concerns have not been clearly understood and dealt with. We have conducted two surveys to understand the issues and concerns of software reuse in the Conventional Software Engineering (CSE) Community and the Software Product Line (SPL) Community where reuse is an integral part of the product development. The quantitative and qualitative analysis of our surveys identified the critical factors which affect and inhibit software engineers and developers adopting software reuse. Software reuse has been talked about in generic terms in software product lines. Though software reuse is a core concept in SPL it has however failed to become a standardized practice. The survey conducted on the SPL Community investigates how software reuse is adopted in SPL so as to provide the necessary degree of support for engineering software product line applications and to identify some of the issues and concerns in software reuse. The identified issues and concerns have helped us to understand the difference between software reuse in the CSE and SPL Communities. It has also given us an indication of how both communities can learn good software reuse practices from each other in order to develop a common software reuse process. Based on the outcome of our surveys we have developed a systematic software reuse process, called the Knowledge Based Software Reuse (KBSR) Process, which incorporates a Repository of reusable software assets to build a systematic legacy system modernization approach. Being able to reuse software artefacts, be it software requirement specification, design, or code, would greatly enhance software productivity and reliability. All of these software artefacts can go in the Knowledge Based Software Reuse Repository and be candidates for reuse

A Multidisciplinary Approach to the Reuse of Open Learning Resources

Educational standards are having a significant impact on e-Learning. They allow for better exchange of information among different organizations and institutions. They simplify reusing and repurposing learning materials. They give teachers the possibility of personalizing them according to the student’s background and learning speed. Thanks to these standards, off-the-shelf content can be adapted to a particular student cohort’s context and learning needs. The same course content can be presented in different languages. Overall, all the parties involved in the learning-teaching process (students, teachers and institutions) can benefit from these standards and so online education can be improved. To materialize the benefits of standards, learning resources should be structured according to these standards. Unfortunately, there is the problem that a large number of existing e-Learning materials lack the intrinsic logical structure required, and further, when they have the structure, they are not encoded as required. These problems make it virtually impossible to share these materials. This thesis addresses the following research question: How to make the best use of existing open learning resources available on the Internet by taking advantage of educational standards and specifications and thus improving content reusability?In order to answer this question, I combine different technologies, techniques and standards that make the sharing of publicly available learning resources possible in innovative ways. I developed and implemented a three-stage tool to tackle the above problem. By applying information extraction techniques and open e-Learning standards to legacy learning resources the tool has proven to improve content reusability. In so doing, it contributes to the understanding of how these technologies can be used in real scenarios and shows how online education can benefit from them. In particular, three main components were created which enable the conversion process from unstructured educational content into a standard compliant form in a systematic and automatic way. An increasing number of repositories with educational resources are available, including Wikiversity and the Massachusetts Institute of Technology OpenCourseware. Wikivesity is an open repository containing over 6,000 learning resources in several disciplines and for all age groups [1]. I used the OpenCourseWare repository to evaluate the effectiveness of my software components and ideas. The results show that it is possible to create standard compliant learning objects from the publicly available web pages, improving their searchability, interoperability and reusability

Advanced Knowledge Technologies at the Midterm: Tools and Methods for the Semantic Web

The University of Edinburgh and research sponsors are authorised to reproduce and distribute reprints and on-line copies for their purposes notwithstanding any copyright annotation hereon. The views and conclusions contained herein are the author’s and shouldn’t be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of other parties.In a celebrated essay on the new electronic media, Marshall McLuhan wrote in 1962:Our private senses are not closed systems but are endlessly translated into each other in that experience which we call consciousness. Our extended senses, tools, technologies, through the ages, have been closed systems incapable of interplay or collective awareness. Now, in the electric age, the very instantaneous nature of co-existence among our technological instruments has created a crisis quite new in human history. Our extended faculties and senses now constitute a single field of experience which demands that they become collectively conscious. Our technologies, like our private senses, now demand an interplay and ratio that makes rational co-existence possible. As long as our technologies were as slow as the wheel or the alphabet or money, the fact that they were separate, closed systems was socially and psychically supportable. This is not true now when sight and sound and movement are simultaneous and global in extent. (McLuhan 1962, p.5, emphasis in original)Over forty years later, the seamless interplay that McLuhan demanded between our technologies is still barely visible. McLuhan’s predictions of the spread, and increased importance, of electronic media have of course been borne out, and the worlds of business, science and knowledge storage and transfer have been revolutionised. Yet the integration of electronic systems as open systems remains in its infancy.Advanced Knowledge Technologies (AKT) aims to address this problem, to create a view of knowledge and its management across its lifecycle, to research and create the services and technologies that such unification will require. Half way through its sixyear span, the results are beginning to come through, and this paper will explore some of the services, technologies and methodologies that have been developed. We hope to give a sense in this paper of the potential for the next three years, to discuss the insights and lessons learnt in the first phase of the project, to articulate the challenges and issues that remain.The WWW provided the original context that made the AKT approach to knowledge management (KM) possible. AKT was initially proposed in 1999, it brought together an interdisciplinary consortium with the technological breadth and complementarity to create the conditions for a unified approach to knowledge across its lifecycle. The combination of this expertise, and the time and space afforded the consortium by the IRC structure, suggested the opportunity for a concerted effort to develop an approach to advanced knowledge technologies, based on the WWW as a basic infrastructure.The technological context of AKT altered for the better in the short period between the development of the proposal and the beginning of the project itself with the development of the semantic web (SW), which foresaw much more intelligent manipulation and querying of knowledge. The opportunities that the SW provided for e.g., more intelligent retrieval, put AKT in the centre of information technology innovation and knowledge management services; the AKT skill set would clearly be central for the exploitation of those opportunities.The SW, as an extension of the WWW, provides an interesting set of constraints to the knowledge management services AKT tries to provide. As a medium for the semantically-informed coordination of information, it has suggested a number of ways in which the objectives of AKT can be achieved, most obviously through the provision of knowledge management services delivered over the web as opposed to the creation and provision of technologies to manage knowledge.AKT is working on the assumption that many web services will be developed and provided for users. The KM problem in the near future will be one of deciding which services are needed and of coordinating them. Many of these services will be largely or entirely legacies of the WWW, and so the capabilities of the services will vary. As well as providing useful KM services in their own right, AKT will be aiming to exploit this opportunity, by reasoning over services, brokering between them, and providing essential meta-services for SW knowledge service management.Ontologies will be a crucial tool for the SW. The AKT consortium brings a lot of expertise on ontologies together, and ontologies were always going to be a key part of the strategy. All kinds of knowledge sharing and transfer activities will be mediated by ontologies, and ontology management will be an important enabling task. Different applications will need to cope with inconsistent ontologies, or with the problems that will follow the automatic creation of ontologies (e.g. merging of pre-existing ontologies to create a third). Ontology mapping, and the elimination of conflicts of reference, will be important tasks. All of these issues are discussed along with our proposed technologies.Similarly, specifications of tasks will be used for the deployment of knowledge services over the SW, but in general it cannot be expected that in the medium term there will be standards for task (or service) specifications. The brokering metaservices that are envisaged will have to deal with this heterogeneity.The emerging picture of the SW is one of great opportunity but it will not be a wellordered, certain or consistent environment. It will comprise many repositories of legacy data, outdated and inconsistent stores, and requirements for common understandings across divergent formalisms. There is clearly a role for standards to play to bring much of this context together; AKT is playing a significant role in these efforts. But standards take time to emerge, they take political power to enforce, and they have been known to stifle innovation (in the short term). AKT is keen to understand the balance between principled inference and statistical processing of web content. Logical inference on the Web is tough. Complex queries using traditional AI inference methods bring most distributed computer systems to their knees. Do we set up semantically well-behaved areas of the Web? Is any part of the Web in which semantic hygiene prevails interesting enough to reason in? These and many other questions need to be addressed if we are to provide effective knowledge technologies for our content on the web

Component-based software engineering

To solve the problems coming with the current software development methodologies, component-based software engineering has caught many researchers\u27 attention recently. In component-based software engineering, a software system is considered as a set of software components assembled together instead of as a set of functions from the traditional perspective. Software components can be bought from third party vendors as off-the-shelf components and be assembled together. Component-based software engineering, though very promising, needs to solve several core issues before it becomes a mature software development strategy. The goal of this dissertation is to establish an infrastructure for component-based software development. The author identifies and studies some of the core issues such as component planning, component building, component assembling, component representation, and component retrieval. A software development process model is developed in this dissertation to emphasize the reuse of existing software components. The software development process model addresses how a software system should be planned and built to maximize the reuse of software components. It conducts domain engineering and application engineering simultaneously to map a software system to a set of existing components in such a way that the development of a software system can reuse the existing software components to the full extent. Besides the planning of software development based on component technology, the migration and integration of legacy systems, most of which are non-component-based systems, to the component-based software systems are studied. A framework and several methodologies are developed to serve as the guidelines of adopting component technology in legacy systems. Component retrieval is also studied in this dissertation. One of the most important issues in component-based software engineering is how to find a software component quickly and accurately in a component repository. A component representation framework is developed in this dissertation to represent software components. Based on the component representation framework, an efficient searching method that combines neural network, information retrieval, and Bayesian inference technology is developed. Finally a prototype component retrieval system is implemented to demonstrate the correctness and feasibility of the proposed method