Reuse Of Information Research Articles

Content-based multi-criteria similarity assessment of CAD assembly models

The use of Digital Mock-Up (DMU) has become mainstream to support the engineering activities all along the Product Development Process. Over the years, companies generate large databases containing digital models and documents related to their products. Considering complex products, the DMU can be composed of several hundred thousand parts assembled together in assembly trees containing tens of sub-assemblies, and representing several terabytes of data. The ability to retrieve existing models is crucial for the competitiveness of companies, as it can help to leverage existing solutions, results and knowledge associated with previous products. To speed up the access to this large amount of reusable information, CAD models search approaches have been proposed, including the so-called content-based search techniques which do not rely on metadata and data organization but exploit the implicit knowledge embedded in the models. As part of a system for the retrieval of CAD assembly models, this paper introduces a set of four measures to evaluate assembly similarities according to multiple criteria. These measures are combined to assess three different levels of similarity (local, partial and global). The local measure only considers the contribution of the parts that are similar in the compared assemblies, while partial and global measures take also into account the number of similar parts compared to the total number of parts in the query and in the target model. Moreover, an ad-hoc visualization interface has been designed to clearly highlight the different similarities and to allow a fast identification of the target models. The validation of the proposed method is discussed, the dataset used to this aim is provided with the specification of the adopted ground truth and some examples of the obtained results are shown.

Physics-based simulation ontology: an ontology to support modelling and reuse of data for physics-based simulation

The current work presents an ontology developed for physics-based simulation in engineering design, called Physics-based Simulation Ontology (PSO). The purpose of the ontology is to assist in modelling the physical phenomenon of interest in a veridical manner, while capturing the necessary and reusable information for physics-based simulation solvers. The development involved extending an existing upper ontology, Basic Formal Ontology (BFO), to define lower-level terms of PSO. PSO has two parts – PSO-Physics, which consists of terms and relations used to model physical phenomena based on the perspective of classical mechanics involving partial differential equations, and PSO-Sim, which consists of terms used to represent the information artefacts that are about the physical phenomena modelled with PSO-Physics. The former terms are used to model the physical phenomenon of interest independent of solver-specific interpretations, which can be reused across different solvers, while the latter terms are used to instantiate solver-specific input data. A case study involving two simulation solvers was conducted to demonstrate this capability of PSO. Discussion around the benefits and limitations of using BFO for the current work is also provided, which should be valuable for any future work that extends an existing upper ontology to develop ontologies for engineering applications.

The Design of FluxML: A Universal Modeling Language for 13C Metabolic Flux Analysis.

13C metabolic flux analysis (MFA) is the method of choice when a detailed inference of intracellular metabolic fluxes in living organisms under metabolic quasi-steady state conditions is desired. Being continuously developed since two decades, the technology made major contributions to the quantitative characterization of organisms in all fields of biotechnology and health-related research. 13C MFA, however, stands out from other “-omics sciences,” in that it requires not only experimental-analytical data, but also mathematical models and a computational toolset to infer the quantities of interest, i.e., the metabolic fluxes. At present, these models cannot be conveniently exchanged between different labs. Here, we present the implementation-independent model description language FluxML for specifying 13C MFA models. The core of FluxML captures the metabolic reaction network together with atom mappings, constraints on the model parameters, and the wealth of data configurations. In particular, we describe the governing design processes that shaped the FluxML language. We demonstrate the utility of FluxML to represent many contemporary experimental-analytical requirements in the field of 13C MFA. The major aim of FluxML is to offer a sound, open, and future-proof language to unambiguously express and conserve all the necessary information for model re-use, exchange, and comparison. Along with FluxML, several powerful computational tools are supplied for easy handling, but also to maintain a maximum of flexibility. Altogether, the FluxML collection is an “all-around carefree package” for 13C MFA modelers. We believe that FluxML improves scientific productivity as well as transparency and therewith contributes to the efficiency and reproducibility of computational modeling efforts in the field of 13C MFA.

Fostering Data Sharing in Multidisciplinary Research Communities: A Case Study in the Geospatial Domain

The sharing of research data allows for information reuse and knowledge advancement but its realization is often a challenge and seldom successful in practice. We propose a workflow for the design of a User Support System (USS) aimed at tutoring research groups in data sharing by considering their social and domain backgrounds. Our engagement approach focuses on multidisciplinary geospatial research, particularly when interoperable data sharing is required. Specifically, we first characterize the research community on the basis of the behavior and competences in data management by its groups and then target the needs of the latter with specific facilities. We address for the first time in literature the issue of modeling research groups as targets of the USS and provide a roadmap to standardize USS activities across different communities. We describe the implementation of the workflow in the context of an Italian research project and we assess the impact of the USS in terms of increase in the number of nodes and resources in the project’s data infrastructure, and of fulfilment of the expectations by the research groups.

Metainformation scenarios in Digital Humanities: Characterization and conceptual modelling strategies

Requirements for the analysis, interpretation and reuse of information are becoming more and more ambitious as we generate larger and more complex datasets. This is leading to the development and widespread use of information about information, often called metainformation (or metadata) in most disciplines. The Digital Humanities are not an exception. We often assume that metainformation helps us in documenting information for future reference by recording who has created it, when and how, among other aspects. We also assume that recording metainformation will facilitate the tasks of interpreting information at later stages. However, some works have identified some issues with existing metadata approaches, related to 1) the proliferation of too many “standards” and difficulties to choose between them; 2) the generalized assumption that metadata and data (or metainformation and information) are essentially different, and the subsequent development of separate sets of languages and tools for each (introducing redundant models); and 3) the combination of conceptual and implementation concerns within most approaches, violating basic engineering principles of modularity and separation of concerns. Some of these problems are especially relevant in Digital Humanities.In addition, we argue here that the lack of characterization of the scenarios in which metainformation plays a relevant role in humanistic projects often results in metainformation being recorded and managed without a specific purpose in mind. In turn, this hinders the process of decision making on issues such as what metainformation must be recorded in a specific project, and how it must be conceptualized, stored and managed.This paper presents a review of the most used metadata approaches in Digital Humanities and, taking a conceptual modelling perspective, analyses their major issues as outlined above. It also describes what the most common scenarios for the use of metainformation in Digital Humanities are, presenting a characterization that can assist in the setting of goals for metainformation recording and management in each case. Based on these two aspects, a new approach is proposed for the conceptualization, recording and management of metainformation in the Digital Humanities, using the ConML conceptual modelling language, and adopting the overall view that metainformation is not essentially different to information. The proposal is validated in Digital Humanities scenarios through case studies employing real-world datasets.

Clustering and retrieval of mechanical CAD assembly models based on multi-source attributes information

Abstract Content-based CAD assembly model retrieval focuses more on the similarity measure of geometry and topology information, which can hardly meet designers’ design requirements in the product conceptual design process. To search quickly and effectively the CAD assembly models related with product design requirements information for assembly model reuse, inspire designers’ design thought and product design innovation in the product conceptual design phase, a novel approach for CAD assembly model clustering and retrieval based on multi-source attributes information is proposed. First, the CAD assembly model is represented by attribute adjacency graph (AAG) with multiple attributes information, and the similarity between assembly models is evaluated comprehensively by considering part information and assembly relationship information. Then, a weighted graph is constructed for assembly clustering in model repository. Meanwhile, an improved spectral clustering algorithm is given to divide CAD assembly models into different assembly clusters. Subsequently, indexing model is established for each assembly cluster. After that, the process of assembly retrieval based on indexing model mechanism is given in detail. Finally, experiments on the prototype system verify effectiveness and feasibility of the proposed approach for assembly clustering and retrieval.

Quantum Entanglement in Deep Learning Architectures.

Modern deep learning has enabled unprecedented achievements in various domains. Nonetheless, employment of machine learning for wave function representations is focused on more traditional architectures such as restricted Boltzmann machines (RBMs) and fully connected neural networks. In this Letter, we establish that contemporary deep learning architectures, in the form of deep convolutional and recurrent networks, can efficiently represent highly entangled quantum systems. By constructing tensor network equivalents of these architectures, we identify an inherent reuse of information in the network operation as a key trait which distinguishes them from standard tensor network-based representations, and which enhances their entanglement capacity. Our results show that such architectures can support volume-law entanglement scaling, polynomially more efficiently than presently employed RBMs. Thus, beyond a quantification of the entanglement capacity of leading deep learning architectures, our analysis formally motivates a shift of trending neural-network-based wave function representations closer to the state-of-the-art in machine learning.

Applying graph matching techniques to enhance reuse of plant design information

This article investigates how graph matching can be applied to process plant design data in order to support the reuse of previous designs. A literature review of existing graph matching algorithms is performed, and a group of algorithms is chosen for further testing. A use case from early phase plant design is presented. A methodology for addressing the use case is proposed, including graph simplification algorithms and node similarity measures, so that existing graph matching algorithms can be applied in the process plant domain. The proposed methodology is evaluated empirically on an industrial case consisting of design data from several pulp and paper plants.

Explaining Download Patterns in Open Government Data: Citizen participation or private enterprise?

Open data remains one of the most significant current trends in public administration, with hundreds of projects around the world seeking to open up stores of public sector information for future re-use. However, as open data has grown, a critical literature has also emerged which questions who the true beneficiaries of open data are, as well as highlighting the high costs it places on government. Hence systematic research on the actual outcomes of open data projects is urgently needed. This article seeks to explain the factors which promote greater levels of downloads of open government data. We show that the use of profit making datasets far exceeds those which could be used to enhance government transparency or service delivery. We also show that well updated datasets with high quality metadata are more likely to be downloaded. We conclude by supporting currently developing calls for prioritisation in open government data programmes.

Modular Ontology Learning with Topic Modelling over Core Ontology

Nowadays, modular domain ontology, where each module represents a subdomain of the ontology domain, facilitates the reuse of information and provides users with domain-specific knowledge. In this paper, we focus on modular taxonomy learning from text, where each module collects terms with the same topic insights, and in parallel we manage to discover hypernym and 'related' relations among those collected terms.However, it is difficult to automatically fit terms into modules and discover relations.We propose to employ twice trainedLDAto partition termsof each subdomain, and relate subdomains into modules of ontology. Meanwhile, we apply core concept replacement and subdomain knowledge supplementation as supportive information embedding technique over the corpus. This shows that the twice trained LDA strategy can effectively identify topic-relevant terms into subdomains, with nearly two-fold precision comparing to that of normal LDA training. The combination of core concept replacement and subdomain knowledge supplementation contributes to significant improvements in modular taxonomy learning.

The behaviour and attitudes of Kempton Park communities with reference to reusing domestic waste

The reuse of domestic waste is an integral part of the domestic waste minimisation process to remove waste from the waste stream. The main objectives of this study were: to determine whether or not households participate in domestic waste reuse activities and the type of activities involved; where they receive information on waste reuse; the behaviour and attitude towards reuse and recommendations based on the findings of the study. This study adopted a quantitative approach describing suburban communities' attitudes and behaviour towards waste reuse. The investigation was non-experimental, cross-sectional and descriptive. Structured questions were used through a simple random sampling method. Results indicated that respondents reused domestic waste, their domestic reuse information was obtained from the media and internet, reusing of waste was a positive activity that would help future generations and it could help save money. Recommendations were made that formal programmes would assist residents to reuse waste efficiently and that government departments and environmental health practitioners should be better sources of information for reuse.

Knowledge Management Contributions in Project Management

Abstract The two concepts, knowledge management and project management have been steadily developing in recent years, with the current effort being the creation of a synergic effect from the two. The article demonstrates the need for a structured framework to group and facilitate the reuse of information and the generation of new knowledge in project management. In this context, knowledge management meets these requirements, providing a tool for improving project management practices. The article contains a review of the advantages and benefits that developers can get by adopting and implementing a project management strategy. An important contribution of the article is to develop a way to apply knowledge management in project management. This starts from the idea that a knowledge management cycle consists of four stages, which can also be applied in project management, and the knowledge passing through these stages goes through a filter, improves and generates a new knowledge.

Open Synthesis: on the need for evidence synthesis to embrace Open Science

The Open Science movement can be broadly summarised as aiming to promote integrity, repeatability and transparency across all aspects of research, from data collection to publication. Systematic reviews and systematic maps aim to provide a reliable synthesis of the evidence on a particular topic, making use of methods that seek to maximise repeatability and comprehensives whilst minimising subjectivity and bias. The central tenet of repeatability is operationalised by transparently reporting methodological activities in detail, such that all actions could be replicated and verified. To date, evidence synthesis has only partially embraced Open Science, typically striving for Open Methodology and Open Access, and occasionally providing sufficient information to be considered to have Open Data for some published reviews. Evidence synthesis communities needs to better embrace Open Science not only to balance knowledge access and increase efficiency, but also to increase reliability, trust and reuse of information collected and synthesised within a review: concepts fundamental to systematic reviews and maps. All aspects of Open Science should be embraced: Open Methodology, Open Data, Open Source and Open Access. In doing so, evidence synthesis can be made more equal, more efficient and more trustworthy. I provide concrete recommendations of how CEE and others can fully embrace Open Synthesis.

Research on Wind Power Equipment Selection System Based on Axiomatic and Knowledge

With the changes of product market requirement and fierce competition, there are kinds of wind power equipments. Combined with the current situation and development trend of wind power enterprise, the establishment of wind power equipment selection system for wind farm design would be proposed and researched. Axiomatic design method is adopted to realize express of customer requirement analysis, and mapping relationship between function demands and design parameters are researched. Wind power equipment selection model based on knowledge is adopted and studied, the reuse of resource is actualized mostly by management of model information and knowledge. Axiomatic design method is adopted to design the platform system, and wind power equipment selection system structure would be established by the method, knowledge of related field and wind power equipment selection process are embed in the system. The reusability method for wind power equipment selection is researched, which realized the reuse of model, information, data and knowledge for wind power equipment selection process. The system structure of wind power equipment selection for wind farm design will be established by the above theories and methods, which would improve wind power equipment selection effectively.

Raising interoperability among base registries: The evolution of the Linked Base Registry for addresses in Flanders

The transformation of society towards a digital economy and government austerity creates a new context leading to changing roles for both government and private sector. Boundaries between public and private services are blurring, enabling government and private sector to collaborate and share responsibilities. In Belgium, the regional Government of Flanders embedded the re-use of public sector information in its legislation and published a data portal containing well over 4000 Open Datasets. Due to a lack of interoperability, interconnecting and interpreting these sources of information remain challenges for public administrations, businesses and citizens. To dissolve the boundaries between the data silos, the Flemish government applied Linked Data design principles in an operational public sector context. This paper discusses the trends we have identified while ‘rewiring’ the Authentic Source for addresses to a Linked Base Registry. We observed the impact on multiple interoperability levels; namely on the legal, organisational, semantic and technical level. In conclusion Linked Data can increase semantic and technical interoperability and lead to a better adoption of government information in the public and private sector. We strongly believe that the insights from the past thirteen years in the region of Flanders could speed up processes in other countries that are facing the complexity of raising technical and semantic interoperability.

Value of hospital electronic health records for clinical research: contribution of the European project EHR4CR

Electronic health records in hospitals contribute to improving the quality of care by enabling better management of clinical information. The databases thus constituted facilitate the exchange of health information with healthcare providers and optimize multidisciplinary coordination for better therapeutic results. The EHR4CR (Electronic Health Records for Clinical Research) European project has developed an innovative pilot platform enabling the reuse of this digital information for clinical research. By enhancing and speeding up clinical research procedures, this innovative approach makes it possible to conduct clinical trials more efficiently, faster, and more economically.

Evolving semantic annotations through multiple versions of controlled medical terminologies

The extensive use of semantic annotations in the medical domain to enhance information retrieval or encode clinical notes to improving information reuse and sharing demands for high quality annotations generation and services for guaranteeing their validity over time. In this paper we present the extension of an existing framework supporting the (semi-)automatic maintenance of semantic annotations rendered outdated by the evolution of the knowledge organization system they are extracted from. This is done by the adding new rules and improving existing ones to overcome some shortcomings of the framework. We also propose an experimental evaluation of the extension using seven successive versions of four standard controlled terminologies within the domain.

A New System Development Framework Driven by a Model-Based Testing Approach Bridged by Information Flow

As complexity increases, model-based approaches have become standard in the systems engineering community. However, engineers from different domains approach the system/component development at different levels of abstraction. Information gaps are created because of their different perspectives. In addition, although systems have become more complex, requiring more attention to testing, system methodologies have not kept up. A new framework is needed to bridge the information gaps between the different domains. To take full advantage of both model-based approaches and testing, we propose a new framework, in the form of a new design structure matrix, for complex system development (CSD) that more effectively utilizes information flow from model-based testing (MBT). Toward the goal of being broadly applicable, the framework was designed to be fundamental, flexible, and scalable. A case study of a powertrain design demonstrates how the proposed framework bridges gaps in early development stages. The analysis of both simulation and field testing results has shown that utilization of feedback from MBT refines requirements by closing information gaps earlier. All the information loops in the framework match the information loops in the case study. Furthermore, the framework, because of CSD's iterative nature, has potential in improving information reuse.

Governance Challenges to Promoting Data Readiness and Data Linkage for Not-for-Profit Organizational Service Data

IntroductionData collected by myriad not-for-profit (NFPs) agencies while providing social services represent a significant untapped source of intelligence. While much research has been conducted on the governance and capacity to share administrative and research data, little work has been done in the area of NFP data sources.
 Objectives and ApproachSix NFP agencies in Calgary participated in a data sharing project to measure various aspects of poverty. This collaboration required understanding the legal, ethical, policy and data challenges to working with data collected in the NFP sector. This case study will expose (a) the legal analysis on legal and governance issues for, and obligations of, NFPs when aiming to share and re-use information beyond service delivery in Alberta, Canada; and (b) the practical and policy challenges faced by the NFPs and repository. The legal analysis involved a systematic search of academic and grey literature; relevant legislation and case-law (especially privacy law).
 ResultsThe legal analysis demonstrated three key things. First, in many circumstances an NFP is not held to any information-handling legal obligations. This does not absolve NFPs from social privacy expectations, especially involving vulnerable populations. Second, privacy best practices are available to NFPs from other more-regulated sectors and from NFP sector standards. The trifecta of purpose, reasonableness and minimal extent are critical. Third, adhering to privacy best practices would not be overly costly, more efficient, and less risky of negative publicity and lost public trust from privacy complaints. These findings informed the NFP data sharing project. The six participant NFPs varied greatly in their approach to consent, governance and information-handling, which affected their data-readiness for cross-organizational data linkage and analysis.
 Conclusion/ImplicationsUnlike government, most NFPs have limited experience with data linkage. This paper informs ethical approaches to include NFP data in broad cross-sector data linkage. Appropriate data governance is imperative for data sharing amongst NFPs, researchers and public organizations, which promotes community service delivery, evaluation and improvements to benefit vulnerable families.

‘Sharing my stories’: genealogists and participatory heritage

ABSTRACTThe vision of an online participatory culture involving communities contributing information and engaging with digitized collections via the social Web has been challenged by the reality of low response rates to many digital cultural heritage projects. This study examines factors that encourage or discourage genealogists, a group generally motivated to share and exchange information, to contribute to DCH projects. The aim is to determine how they prefer to share information and knowledge and investigate if genealogists from indigenous communities have different preferences. Semi-structured interviews were conducted with six members of the New Zealand Society of Genealogists. The interview data were used to inform the design of an online survey questionnaire, which was distributed to other members of NZSG. The findings showed that respondents were willing to share information and were motivated to establish reciprocal relationships fundamental to building online communities. Lack of knowledge about cultural heritage databases and concerns over ownership, control and the reuse of information however, were identified as factors that discouraged sharing, especially for researchers of Māori genealogy. The survey findings suggest that cultural heritage institutions (CHIs) need to nurture relationships and earn the trust of the community from which information is being solicited. Effective consultation and communication and having clear policies in place about use and reuse of information shared could facilitate these. Further research into encouraging the exchange of information between CHIs and the indigenous communities is particularly important as many remain conflicted between their desire to share and to protect their family history and knowledge.