Enabling Product Design Reuse by Long-term Preservation of Engineering Knowledge

In the highly competitive engineering industry, product innovations are created with the help of a product lifecycle management (PLM) tool chain. In order to support fast-paced product development, a major company goal is the reuse of product designs and product descriptions. Due to the product’s complexity, the design of a product not only consists of geometry data but also of valuable engineering knowledge that is created during the various PLM phases. The need to preserve such intellectual capital leads engineering companies to introduce knowledge management and archiving their machine-readable formal representation. However, archived knowledge is in danger of becoming unusable since it is very likely that knowledge semantics and knowledge representation will evolve over long time periods, for example during the 50 operational years of some products. Knowledge evolution and knowledge representation technology changes are crucial issues since a reuse of the archived product information can only be ensured if its rationale and additional knowledge are interpretable with future software and technologies. Therefore, in order to reuse design data fully, knowledge about the design must also be migrated to be interoperable with future design systems and knowledge representation methods. This paper identifies problems, issues, requirements, challenges and solutions that arise while tackling the long-term preservation of engineering knowledge

Evaluating Enterprize Delivery Using the TYPUS Metrics and the KILT Mode

The goal of this work is the technical, ecological, environmental and social examination of the life-cycle (LC) of any product (consumable, service, production) using the TYPUS metrics and the KILT model. The life-cycle starts when the idea of a product is born and lasts until complete dismissal through design, implementation and operation, etc. In the first phases requirements’ specification, analysis, several design steps (global plan, detailed design, assembly design, etc.) are followed by part manufacturing, assembly, testing, diagnostics and operation, advertisement, service, maintenance, etc. Then finally disassembly and dismissal are coming, but dismissal can be substituted by re-cycling (e.g. melting the metals) or re-use (used parts applications). Qualitative and quantitative evaluations of enterprise results are supported by the new models and metrics

Chemical information matters: an e-Research perspective on information and data sharing in the chemical sciences

Recently, a number of organisations have called for open access to scientific information and especially to the data obtained from publicly funded research, among which the Royal Society report and the European Commission press release are particularly notable. It has long been accepted that building research on the foundations laid by other scientists is both effective and efficient. Regrettably, some disciplines, chemistry being one, have been slow to recognise the value of sharing and have thus been reluctant to curate their data and information in preparation for exchanging it. The very significant increases in both the volume and the complexity of the datasets produced has encouraged the expansion of e-Research, and stimulated the development of methodologies for managing, organising, and analysing "big data". We review the evolution of cheminformatics, the amalgam of chemistry, computer science, and information technology, and assess the wider e-Science and e-Research perspective. Chemical information does matter, as do matters of communicating data and collaborating with data. For chemistry, unique identifiers, structure representations, and property descriptors are essential to the activities of sharing and exchange. Open science entails the sharing of more than mere facts: for example, the publication of negative outcomes can facilitate better understanding of which synthetic routes to choose, an aspiration of the Dial-a-Molecule Grand Challenge. The protagonists of open notebook science go even further and exchange their thoughts and plans. We consider the concepts of preservation, curation, provenance, discovery, and access in the context of the research lifecycle, and then focus on the role of metadata, particularly the ontologies on which the emerging chemical Semantic Web will depend. Among our conclusions, we present our choice of the "grand challenges" for the preservation and sharing of chemical information

Report of the Stanford Linked Data Workshop

The Stanford University Libraries and Academic Information Resources (SULAIR) with the Council on Library and Information Resources (CLIR) conducted at week-long workshop on the prospects for a large scale, multi-national, multi-institutional prototype of a Linked Data environment for discovery of and navigation among the rapidly, chaotically expanding array of academic information resources. As preparation for the workshop, CLIR sponsored a survey by Jerry Persons, Chief Information Architect emeritus of SULAIR that was published originally for workshop participants as background to the workshop and is now publicly available. The original intention of the workshop was to devise a plan for such a prototype. However, such was the diversity of knowledge, experience, and views of the potential of Linked Data approaches that the workshop participants turned to two more fundamental goals: building common understanding and enthusiasm on the one hand and identifying opportunities and challenges to be confronted in the preparation of the intended prototype and its operation on the other. In pursuit of those objectives, the workshop participants produced:1. a value statement addressing the question of why a Linked Data approach is worth prototyping;2. a manifesto for Linked Libraries (and Museums and Archives and …);3. an outline of the phases in a life cycle of Linked Data approaches;4. a prioritized list of known issues in generating, harvesting & using Linked Data;5. a workflow with notes for converting library bibliographic records and other academic metadata to URIs;6. examples of potential “killer apps” using Linked Data: and7. a list of next steps and potential projects.This report includes a summary of the workshop agenda, a chart showing the use of Linked Data in cultural heritage venues, and short biographies and statements from each of the participants

Remanufacturing and product design: designing for the 7th generation

The following is taken directly from the research report. This report investigates Design for Remanufacture in terms of both detailed product design and the business context in which Design for Remanufacture may operate. Key Study Objectives • To understand the link between design and remanufacture • To understand how Design for Remanufacture can lead to increased innovation and Sustainable Development (SD) • To identify proactive strategies to further Design for Remanufactur

Invest to Save: Report and Recommendations of the NSF-DELOS Working Group on Digital Archiving and Preservation

Digital archiving and preservation are important areas for research and development, but there is no agreed upon set of priorities or coherent plan for research in this area. Research projects in this area tend to be small and driven by particular institutional problems or concerns. As a consequence, proposed solutions from experimental projects and prototypes tend not to scale to millions of digital objects, nor do the results from disparate projects readily build on each other. It is also unclear whether it is worthwhile to seek general solutions or whether different strategies are needed for different types of digital objects and collections. The lack of coordination in both research and development means that there are some areas where researchers are reinventing the wheel while other areas are neglected. Digital archiving and preservation is an area that will benefit from an exercise in analysis, priority setting, and planning for future research. The WG aims to survey current research activities, identify gaps, and develop a white paper proposing future research directions in the area of digital preservation. Some of the potential areas for research include repository architectures and inter-operability among digital archives; automated tools for capture, ingest, and normalization of digital objects; and harmonization of preservation formats and metadata. There can also be opportunities for development of commercial products in the areas of mass storage systems, repositories and repository management systems, and data management software and tools.

Requirements traceability in model-driven development: Applying model and transformation conformance

The variety of design artifacts (models) produced in a model-driven design process results in an intricate relationship between requirements and the various models. This paper proposes a methodological framework that simplifies management of this relationship, which helps in assessing the quality of models, realizations and transformation specifications. Our framework is a basis for understanding requirements traceability in model-driven development, as well as for the design of tools that support requirements traceability in model-driven development processes. We propose a notion of conformance between application models which reduces the effort needed for assessment activities. We discuss how this notion of conformance can be integrated with model transformations

An Initial Maturity Model for Information Governance

This report details the maturity model for information governance which will be used to assess the E-ARK Project use cases. The method that guides the application of this maturity model will then be detailed in deliverable 7.5, A Maturity Model consists of a number of entities, including “maturity levels” (often six) which are, from the lowest to the highest, (0) Non Existent, (1) Initial, (2) Basic, (3) Intermediate, (4) Advanced and (5) Optimizing. Each process can have its own Maturity Model, which expresses quantitatively the maturity level of an organization regarding a certain process. A Maturity Model provides also a way for organizations to see clearly what they must accomplish in order to pass to the next maturity level. The use of maturity models is wide spread and accepted, both in industry and academia. There are numerous maturity models, at least one for each of the most trending topics in such areas as Information Technology or Information Systems. Maturity Models are widely used and accepted because of their simplicity and effectiveness. They can easily help understanding the current level of maturity of a certain aspect in a meaningful way, so that stakeholders can clearly identify strengths and weaknesses requiring improvement, and thus prioritise what must be done in order to reach a higher level. This can be used to show the outcomes that will result from that effort, enabling stakeholders to decide if the outcomes justify the effort