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ویرایش: 2024
نویسندگان: Ian Gordon. Neil Thompson
سری:
ISBN (شابک) : 3031510070, 9783031510076
ناشر: Springer
سال نشر: 2024
تعداد صفحات: 380
زبان: English
فرمت فایل : PDF (درصورت درخواست کاربر به PDF، EPUB یا AZW3 تبدیل می شود)
حجم فایل: 8 مگابایت
در صورت تبدیل فایل کتاب Data and the Built Environment: A Practical Guide to Building a Better World Using Data (Digital Innovations in Architecture, Engineering and Construction) به فرمت های PDF، EPUB، AZW3، MOBI و یا DJVU می توانید به پشتیبان اطلاع دهید تا فایل مورد نظر را تبدیل نمایند.
توجه داشته باشید کتاب داده ها و محیط ساخته شده: راهنمای عملی برای ساختن دنیایی بهتر با استفاده از داده ها (نوآوری های دیجیتال در معماری، مهندسی و ساخت و ساز) نسخه زبان اصلی می باشد و کتاب ترجمه شده به فارسی نمی باشد. وبسایت اینترنشنال لایبرری ارائه دهنده کتاب های زبان اصلی می باشد و هیچ گونه کتاب ترجمه شده یا نوشته شده به فارسی را ارائه نمی دهد.
Acknowledgements Contents About the Authors List of Figures List of Tables 1 Purpose and Pedantry 1.1 Why This Book and Why Now? 1.2 Structure of This Book 1.3 Intended Outcomes of This Book 1.4 Building on Established Practice 1.5 Definitions 1.5.1 Physical Things 1.5.2 Data, Information, Knowledge, Insight, Wisdom 1.5.3 Time 1.5.4 Organisations and Friction 1.5.5 Types of Data 1.6 Conclusion References 2 The Challenge of the Built Environment 2.1 Data and the Built Environment 2.2 What Makes Built Environment Data Different? 2.3 Designing Equity: Planning, Cartography, Geography… and Data 2.4 Measuring Value Through Societal Outcomes 2.4.1 Delivering New Economic Infrastructure to Drive Improved Outcomes for People and Nature 2.4.2 Place-Based Regeneration and Delivery 2.4.3 Addressing the Need for Infrastructure Using a Platform Approach 2.4.4 Retrofitting Existing Buildings to Achieve Net Zero Greenhouse Gas Emissions 2.4.5 Optimising the Environmental Performance of Our Existing Built Environment 2.4.6 A Purpose-Driven Sector 2.5 Building for Extinction: Data and Survival 2.5.1 Lowering the Carbon Impact of Construction 2.5.2 Increasing the Operational Sustainability of the Built Environment 2.5.3 Supporting the Decarbonisation of Transport and Industry 2.6 Safety 2.7 Ownership and Incentives 2.7.1 Public Versus Private 2.7.2 Data As Scorekeeper 2.8 Data Sharing 2.8.1 Sharing Commercial Data 2.8.2 Location Data for Transport Operations 2.9 Interoperability 2.9.1 Delivering Interoperability at the Mega Scale 2.10 Data as a Valued Asset 2.11 Conclusion References 3 Background Reading 3.1 Relevant Standards 3.1.1 Quality Management (ISO 9001 and BS 99001) 3.1.2 Design and Construction (BS 1192, ISO 19650) 3.1.3 Operations, Maintenance, and Asset Management (BS 8536, PAS 55, ISO 55000) 3.1.4 Heritage and Restoration 3.2 Relevant Publications 3.2.1 Transforming Infrastructure Performance (TIP)—Roadmap 2030 (IPA, 2021) 3.2.2 Government Soft Landings (CDBB, 2019) 3.2.3 Construction Playbook (Cabinet Office, 2020) 3.2.4 Data for the Public Good (National Infrastructure Commission, 2017) 3.2.5 Flourishing Systems (CDBB/CSIC, 2020) 3.2.6 Independent Review of Building Regulations and Fire Safety: Hackitt Review (MHCLG, 2018) 3.3 Relevant Regulation and Legislation 3.3.1 Keeping Staff Safe 3.3.2 Keeping Occupants Safe 3.3.3 Protecting the Natural Environment 3.3.4 Keeping Data Safe 3.3.5 Making Data Transparent 3.3.6 Encouraging Data Best Practice Through Regulation 3.4 Conclusion References 4 Data and Organisational Culture 4.1 Introduction: Meaning in Data 4.2 Data Culture 4.2.1 What Does It Even Mean to Make Data-Driven Decisions? 4.2.2 Time and Decision-Making 4.2.3 Case Study: Data ‘Friction’ and the Music Industry 4.3 Stakeholder Engagement and Communities of Practice 4.4 Writing a Data Strategy 4.5 Your Data Vision Statement 4.6 Data Principles (and Ethics) 4.7 Data Capabilities 4.8 Use Cases 4.9 Data Outcomes and Benefits 4.9.1 Sectoral Benefits 4.9.2 Organisational Benefits 4.10 Data Roles and Skills 4.11 Conclusion References 5 Delivering Data Capability 5.1 Data Foundations/Precursors 5.1.1 Data Governance and Data Empowerment 5.1.2 Pragmatic Enterprise Data Architecture 5.1.3 A Practical Philosophy (a Data Dogma) 5.1.4 Ontology (Common Data Models) 5.1.5 How to Build and Use an Ontology for Construction 5.1.6 Starting with an ‘Entry-Level’ Taxonomy or Business Glossary 5.1.7 Search and Classification 5.1.8 Unstructured Data Management 5.2 Delivering Successful Data Projects 5.2.1 Delivering Through Traditional IT Functions 5.2.2 Working with Legacy Practices 5.2.3 Working for Construction Projects 5.2.4 Delivering into Operational IT 5.2.5 Working Through Governance 5.3 Procuring Successful Data Projects 5.3.1 Ensuring Your Scope of Work is Deliverable 5.3.2 Competing and Evaluating 5.3.3 Ways of Working 5.3.4 Managing Ecosystems and Dependencies 5.3.5 Making Effective Use of Terms and Conditions 5.3.6 Procuring Across the Life Cycle of a Service 5.4 Conclusion References 6 Radical Technologies 6.1 On Complexity 6.2 On Technology 6.3 Digital Construction and Building Information Modelling (BIM) 6.3.1 Definitions 6.3.2 Dimensions and a Data-First Approach 6.3.3 Emerging Technologies: Bridging the Gap Between Digital and Reality 6.3.4 Digital Heritage: Working with old and unique assets 6.3.5 Geospatial Information Systems (GIS) 6.4 Data Analytics and Business Intelligence (BI) 6.4.1 Process 6.4.2 Staff and Stakeholders 6.4.3 Prototyping and Scaling 6.4.4 Infrastructure—Warehouses, Lakes, Mesh 6.4.5 Human Psychology and BI 6.5 Data Science and Artificial Intelligence (AI) 6.5.1 The Sub-four-minute Mile 6.5.2 Definitions 6.6 Emergent Behaviour: Applying the AI Paradigm Shift to the Built Environment 6.6.1 Primer: AI, LLMs, and Software 2.0 6.6.2 To AI or to Automate? 6.6.3 Categorising Our Problems 6.6.4 Specialist Built Environment Models 6.6.5 Predictive Analytics 6.6.6 Data Science on Built Environment Projects 6.7 Information, Everywhere: The Paradigm Shifts of IoT and Cloud Computing 6.7.1 What Is Smart? 6.7.2 The Drawbacks and Ethics of Smart Places 6.8 Digital Rehearsal 6.8.1 Parametric and Generative Design 6.9 Digital Twins 6.9.1 Smart Buildings Versus Digital Twins 6.9.2 Industrial Digital Twins 6.9.3 From Construction to Operations 6.9.4 Architecture 6.9.5 National Digital Twinning 6.9.6 Digital Twinning Across Industrial Sectors 6.10 Conclusion References 7 How to Be a Data Person 7.1 How to Be a Data Person 7.2 How to Be a Person 7.3 How to Set a Positive Example 7.4 How to Be Conscious of Your Biases 7.5 How to Be Ethical 7.6 How to Be Open Minded and Work with Others 7.7 How to Sell a Narrative 7.8 How to Make Product Love, and Not Be Ruled by It 7.9 How to Take Accountability and How to Lead 7.10 How to Grow Talent 7.11 How to Respect Your Own Time and Your Mind 7.12 How to Learn 7.13 How to Think About Mental Health 7.14 How Not to Take It All Personally 7.15 How to Take Sustainability Seriously 7.16 Epilogue: Of Bytes and Bricks References