468 research outputs found

    Digital approaches to construction compliance checking: Validating the suitability of an ecosystem approach to compliance checking

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    The lifecycle of the built environment is governed by complex regulations, requirements and standards. Ensuring compliance against these requirements is a complicated process, affecting the entire supply chain and often incurring significant costs, delay and uncertainty. Many of the processes, and elements within these processes, are formalised and supported by varying levels of digitisation and automation. This ranges from energy simulation, geometric checking, to building information modelling based checking. However, there are currently no unifying standards or integrating technology to tie regulatory efforts together to enable the widespread adoption of automated compliance processes. This has left many current technical approaches, while advanced and robust, isolated. However, the increasing maturity of asset datasets/information models, means that integration of data/tools is now feasible. This paper will propose and validate a new approach of solving the problem of automated compliance checking through the use of an ecosystem of compliance checking services. This work has identified a clear research gap. How automated compliance checking in the construction sector can move beyond sole reliance on BIM data, and tightly coupled integration with software tools, to provide an extensible enough system to integrate the current isolated software elements currently used within compliance checking processes. To test this approach, an architecture for an ecosystem of compliance services will be specified. To validate this architecture, a prototype version will be developed and validated against requirements derived from the weaknesses of current approaches. This validation has found that a distributed ecosystem can perform accurately and successfully, whilst providing advantages in terms of scalability and extensibility. This approach provides a route to the increased adoption of automated compliance checking, overcoming the issues of relying on one computer system/application to perform all aspects of this process

    A BIM - GIS Integrated Information Model Using Semantic Web and RDF Graph Databases

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    In recent years, 3D virtual indoor and outdoor urban modelling has become an essential geospatial information framework for civil and engineering applications such as emergency response, evacuation planning, and facility management. Building multi-sourced and multi-scale 3D urban models are in high demand among architects, engineers, and construction professionals to achieve these tasks and provide relevant information to decision support systems. Spatial modelling technologies such as Building Information Modelling (BIM) and Geographical Information Systems (GIS) are frequently used to meet such high demands. However, sharing data and information between these two domains is still challenging. At the same time, the semantic or syntactic strategies for inter-communication between BIM and GIS do not fully provide rich semantic and geometric information exchange of BIM into GIS or vice-versa. This research study proposes a novel approach for integrating BIM and GIS using semantic web technologies and Resources Description Framework (RDF) graph databases. The suggested solution's originality and novelty come from combining the advantages of integrating BIM and GIS models into a semantically unified data model using a semantic framework and ontology engineering approaches. The new model will be named Integrated Geospatial Information Model (IGIM). It is constructed through three stages. The first stage requires BIMRDF and GISRDF graphs generation from BIM and GIS datasets. Then graph integration from BIM and GIS semantic models creates IGIMRDF. Lastly, the information from IGIMRDF unified graph is filtered using a graph query language and graph data analytics tools. The linkage between BIMRDF and GISRDF is completed through SPARQL endpoints defined by queries using elements and entity classes with similar or complementary information from properties, relationships, and geometries from an ontology-matching process during model construction. The resulting model (or sub-model) can be managed in a graph database system and used in the backend as a data-tier serving web services feeding a front-tier domain-oriented application. A case study was designed, developed, and tested using the semantic integrated information model for validating the newly proposed solution, architecture, and performance

    CIDOC CRM as the basis of the Electronic State Register of Immovable Cultural Heritage of Ukraine

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    Abstract. The article is the final in a series of articles on Conceptual Provisions for the Creation of a New Electronic State Register of Immovable Cultural Heritage (CH) of Ukraine. These provisions correspond to the components of the Solutions Framework (SoFr) of special Spatial Information Systems (SpIS) defined in the monograph [15]. The special SpIS of the new registry of the CH of Ukraine should belong to the class of Atlas Geoinformation Systems (AGIS), which is described in [14]. The first queue of AGIS – AGIS-CH1 – is proposed as the first queue of the new electronic State Register of Immovable CH of Ukraine. The first queue should include, at least, three components that are simultaneously SoFr packages: Products-Processes-Basics. The conceptual provisions of AGIS-CH1 describe these three most important components of the architectural pattern of AGIS-CH1: AGIS-CH1.Products, Part 1 [17]; AGIS-CH1.Processes, Part 2 [18], AGIS-CH1.Basics, Part 3, consisting of two subparts, 3.1 and 3.2. Subpart 3.1 is described in the article [19]. This article describes subpart 3.2, which is called "Basics. CIDOC CRM". It consists of two main sections. The first of these initially examines the prerequisites that lead to the use of CIDOC CRM. Such prerequisites are two evolutions: system and subject. System evolution claims that the time has come to consider the registry of the CH of Ukraine as a SpIS of the Web 3.0 Formation, also known as the Semantic Web, especially if we have in mind the creation of a new registry. Subject evolution refers to the evolution of understanding of the domain of cultural heritage. From the review of this issue in the monograph [4], it is obvious that modern CH registers should be "process" rather than "product". In order to proceed to the consideration of CIDOC CRM with a better understanding of the essence of the issue, the CHARM model (Cultural Heritage Abstract Reference Model) was considered. CIDOC CRM can also be considered as such, but CHARM is described in an excellent monograph [4] that is practically applicable, unlike the scattered articles on CIDOC CRM. The second of the two main sections of the article deals with CIDOC CRM and its use. We do not describe CIDOC CRM completely. Attention is paid only to its "spatial" and "process" parts. In addition, attention is paid to the use of CIDOC CRM. For this, the information from the website (https://www.cidoc-crm.org/how-i-can-use-cidoc-crm, 2023-jun-26) is used first. Then there is some initial information about the Arches software platform. We offer the Arches platform for the implementation of AGIS-CH1. Key words: Solutions Framework (SoFr), Atlas geoinformation system (AGIS), Basics of AGIS SoFr, register of CH as the first queue of AGIS

    What do data portals do? Tracing the politics of online devices for making data public

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    Managing healthcare transformation towards P5 medicine (Published in Frontiers in Medicine)

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    Health and social care systems around the world are facing radical organizational, methodological and technological paradigm changes to meet the requirements for improving quality and safety of care as well as efficiency and efficacy of care processes. In this they’re trying to manage the challenges of ongoing demographic changes towards aging, multi-diseased societies, development of human resources, a health and social services consumerism, medical and biomedical progress, and exploding costs for health-related R&D as well as health services delivery. Furthermore, they intend to achieve sustainability of global health systems by transforming them towards intelligent, adaptive and proactive systems focusing on health and wellness with optimized quality and safety outcomes. The outcome is a transformed health and wellness ecosystem combining the approaches of translational medicine, 5P medicine (personalized, preventive, predictive, participative precision medicine) and digital health towards ubiquitous personalized health services realized independent of time and location. It considers individual health status, conditions, genetic and genomic dispositions in personal social, occupational, environmental and behavioural context, thus turning health and social care from reactive to proactive. This requires the advancement communication and cooperation among the business actors from different domains (disciplines) with different methodologies, terminologies/ontologies, education, skills and experiences from data level (data sharing) to concept/knowledge level (knowledge sharing). The challenge here is the understanding and the formal as well as consistent representation of the world of sciences and practices, i.e. of multidisciplinary and dynamic systems in variable context, for enabling mapping between the different disciplines, methodologies, perspectives, intentions, languages, etc. Based on a framework for dynamically, use-case-specifically and context aware representing multi-domain ecosystems including their development process, systems, models and artefacts can be consistently represented, harmonized and integrated. The response to that problem is the formal representation of health and social care ecosystems through an system-oriented, architecture-centric, ontology-based and policy-driven model and framework, addressing all domains and development process views contributing to the system and context in question. Accordingly, this Research Topic would like to address this change towards 5P medicine. Specifically, areas of interest include, but are not limited: • A multidisciplinary approach to the transformation of health and social systems • Success factors for sustainable P5 ecosystems • AI and robotics in transformed health ecosystems • Transformed health ecosystems challenges for security, privacy and trust • Modelling digital health systems • Ethical challenges of personalized digital health • Knowledge representation and management of transformed health ecosystems Table of Contents: 04 Editorial: Managing healthcare transformation towards P5 medicine Bernd Blobel and Dipak Kalra 06 Transformation of Health and Social Care Systems—An Interdisciplinary Approach Toward a Foundational Architecture Bernd Blobel, Frank Oemig, Pekka Ruotsalainen and Diego M. Lopez 26 Transformed Health Ecosystems—Challenges for Security, Privacy, and Trust Pekka Ruotsalainen and Bernd Blobel 36 Success Factors for Scaling Up the Adoption of Digital Therapeutics Towards the Realization of P5 Medicine Alexandra Prodan, Lucas Deimel, Johannes Ahlqvist, Strahil Birov, Rainer Thiel, Meeri Toivanen, Zoi Kolitsi and Dipak Kalra 49 EU-Funded Telemedicine Projects – Assessment of, and Lessons Learned From, in the Light of the SARS-CoV-2 Pandemic Laura Paleari, Virginia Malini, Gabriella Paoli, Stefano Scillieri, Claudia Bighin, Bernd Blobel and Mauro Giacomini 60 A Review of Artificial Intelligence and Robotics in Transformed Health Ecosystems Kerstin Denecke and Claude R. Baudoin 73 Modeling digital health systems to foster interoperability Frank Oemig and Bernd Blobel 89 Challenges and solutions for transforming health ecosystems in low- and middle-income countries through artificial intelligence Diego M. López, Carolina Rico-Olarte, Bernd Blobel and Carol Hullin 111 Linguistic and ontological challenges of multiple domains contributing to transformed health ecosystems Markus Kreuzthaler, Mathias Brochhausen, Cilia Zayas, Bernd Blobel and Stefan Schulz 126 The ethical challenges of personalized digital health Els Maeckelberghe, Kinga Zdunek, Sara Marceglia, Bobbie Farsides and Michael Rigb

    Geographic information extraction from texts

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    A large volume of unstructured texts, containing valuable geographic information, is available online. This information – provided implicitly or explicitly – is useful not only for scientific studies (e.g., spatial humanities) but also for many practical applications (e.g., geographic information retrieval). Although large progress has been achieved in geographic information extraction from texts, there are still unsolved challenges and issues, ranging from methods, systems, and data, to applications and privacy. Therefore, this workshop will provide a timely opportunity to discuss the recent advances, new ideas, and concepts but also identify research gaps in geographic information extraction

    WiFi-Based Human Activity Recognition Using Attention-Based BiLSTM

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    Recently, significant efforts have been made to explore human activity recognition (HAR) techniques that use information gathered by existing indoor wireless infrastructures through WiFi signals without demanding the monitored subject to carry a dedicated device. The key intuition is that different activities introduce different multi-paths in WiFi signals and generate different patterns in the time series of channel state information (CSI). In this paper, we propose and evaluate a full pipeline for a CSI-based human activity recognition framework for 12 activities in three different spatial environments using two deep learning models: ABiLSTM and CNN-ABiLSTM. Evaluation experiments have demonstrated that the proposed models outperform state-of-the-art models. Also, the experiments show that the proposed models can be applied to other environments with different configurations, albeit with some caveats. The proposed ABiLSTM model achieves an overall accuracy of 94.03%, 91.96%, and 92.59% across the 3 target environments. While the proposed CNN-ABiLSTM model reaches an accuracy of 98.54%, 94.25% and 95.09% across those same environments

    Graphie: A network-based visual interface for the UK's primary legislation [version 1; peer review: 2 approved]

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    Background: legislation.gov.uk is a platform that enables users to explore and navigate the many sections of the UK’s legal corpus through its well-designed searching and browsing features. However, there is room for improvement as it lacks the ability to easily move between related sections or Acts and only presents a text-only rendering of provisions. With Graphie, our novel navigational tool (graphie.quantlaw.co.uk), we aim to address this limitation by presenting alternative visualizations of legal documents using both text and graphs. Methods: The building block of Graphie is Sofia, an offline data pipeline designed to support different data visualizations by parsing and modelling data provided by legislation.gov.uk in open access form. Results: Graphie provides a network representation of the hierarchical structure of an Act of Parliament, which is typically organized in a tree-like fashion according to the content and information contained in each sub-branch. Nodes in Graphie represent sections of an Act (or individual provisions), while links embody the hierarchical connections between them. The legal map provided by Graphie is easily navigable by hovering on nodes, which are also color-coded and numbered to provide easily accessible information about the underlying content. The full textual content of each node is also available on a dedicated hyperlinked canvas. Conclusions: While we focus on the Housing Act 2004 for illustrative purposes, our platform is scalable, versatile, and provides users with a unified toolbox to visualize and explore the UK legal corpus in a fast and user-friendly way

    Decisioning 2022 : Collaboration in knowledge discovery and decision making: Applications to sustainable agriculture

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    Sustainable agriculture is one of the Sustainable Development Goals (SDG) proposed by UN (United Nations), but little systematic work on Knowledge Discovery and Decision Making has been applied to it. Knowledge discovery and decision making are becoming active research areas in the last years. The era of FAIR (Findable, Accessible, Interoperable, Reusable) data science, in which linked data with a high degree of variety and different degrees of veracity can be easily correlated and put in perspective to have an empirical and scientific perception of best practices in sustainable agricultural domain. This requires combining multiple methods such as elicitation, specification, validation, technologies from semantic web, information retrieval, formal concept analysis, collaborative work, semantic interoperability, ontological matching, specification, smart contracts, and multiple decision making. Decisioning 2022 is the first workshop on Collaboration in knowledge discovery and decision making: Applications to sustainable agriculture. It has been organized by six research teams from France, Argentina, Colombia and Chile, to explore the current frontier of knowledge and applications in different areas related to knowledge discovery and decision making. The format of this workshop aims at the discussion and knowledge exchange between the academy and industry members.Laboratorio de Investigación y Formación en Informática Avanzad
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