Info
- Utilizzare la checkbox di selezione a fianco di ciascun documento per attivare le funzionalità di stampa, invio email, download nei formati disponibili del (i) record.
The Economics of Big Science [[electronic resource] ] : Essays by Leading Scientists and Policymakers / / edited by Hans Peter Beck, Panagiotis Charitos
| The Economics of Big Science [[electronic resource] ] : Essays by Leading Scientists and Policymakers / / edited by Hans Peter Beck, Panagiotis Charitos |
| Autore | Beck Hans Peter |
| Edizione | [1st ed. 2021.] |
| Pubbl/distr/stampa | Springer Nature, 2021 |
| Descrizione fisica | 1 online resource (VIII, 137 p. 26 illus., 24 illus. in color.) |
| Disciplina | 539.7 |
| Collana | Science Policy Reports |
| Soggetto topico |
Nuclear physics
Economic policy Space sciences Big data Capital investments Particle and Nuclear Physics R & D/Technology Policy Space Sciences (including Extraterrestrial Physics, Space Exploration and Astronautics) Big Data Investment Appraisal |
| Soggetto genere / forma | Conference papers and proceedings. |
| Soggetto non controllato |
Particle and Nuclear Physics
R & D/Technology Policy Space Sciences (including Extraterrestrial Physics, Space Exploration and Astronautics) Big Data Investment Appraisal Nuclear and Particle Physics Economics Space Physics Finance Investing in fundamental science Societal benefits / value of science Measuring socio-economic impact of science Benefits from fundamental research Big science projects finance/costs Cost of large-scale scientific projects Societal value of fundamental science Open Access Particle & high-energy physics Research & development management Astronautics Databases Investment & securities |
| ISBN | 3-030-52391-8 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Introduction -- Towards a Sustainable European Research Infrastructures Ecosystem -- Economics of Science in the Time of Data Economy and Gigabit Society -- The SKA Approach to Sustainable Research -- The European Spallation Source: Designing a Sustainable Research Infrastructure for Europe -- Optimising the Benefits from Research Institutes -- Rethinking the Socio-economic Value of Big Science: Lessons from the FCC Study -- Socio-Economic Impact Assessments of ESA Programmes: A Brief Overview -- Designing a Socio-Economic Impact Framework for Research Infrastructures: Preliminary Lessons from the RI-PATHS Project -- Findings from the LHC/HL-LHC Programme -- Designing a Research Infrastructure with Impact in Mind -- Leveraging the Economic Potential of FCC’s Technologies and Processes -- How to Value Public Science Employing Social Big Data? -- R&D, Innovative Collaborations and the Role of Public Policies -- Large-Scale Investment in Science: Economic Impact and Social Justice -- Investing in Fundamental Research: For Whom? A Philosopher’s Perspective -- Investing in Fundamental Research: Evaluation of the Benefits that the UK Has Derived from CERN -- Fundamental Science Drives Innovation -- Epilogue: Productive Collisions—Blue-Sky Science and Today’s Innovations. |
| Record Nr. | UNISA-996466747603316 |
Beck Hans Peter
|
||
| Springer Nature, 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
The Elements of Big Data Value [[electronic resource] ] : Foundations of the Research and Innovation Ecosystem
| The Elements of Big Data Value [[electronic resource] ] : Foundations of the Research and Innovation Ecosystem |
| Autore | Curry Edward |
| Pubbl/distr/stampa | Cham, : Springer International Publishing AG, 2021 |
| Descrizione fisica | 1 online resource (412 p.) |
| Altri autori (Persone) |
MetzgerAndreas
ZillnerSonja PazzagliaJean-Christophe García RoblesAna |
| Soggetto topico |
Information retrieval
Business & management Research & development management Information technology industries Databases |
| Soggetto non controllato |
Information Storage and Retrieval
Business and Management, general Innovation/Technology Management The Computer Industry Big Data Innovation and Technology Management Technology Commercialization Digital Transformation Innovation Spaces Data-Driven Innovation Data Analytics Technology Management Data Ecosystems Data Protection Big Data Business Models Open Access Information retrieval Data warehousing Business & Management Research & development management Industrial applications of scientific research & technological innovation Information technology industries Databases |
| ISBN | 3-030-68176-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNISA-996464495403316 |
|
Curry Edward
|
||
| Cham, : Springer International Publishing AG, 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
The Elements of Big Data Value : Foundations of the Research and Innovation Ecosystem
| The Elements of Big Data Value : Foundations of the Research and Innovation Ecosystem |
| Autore | Curry Edward |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Cham, : Springer International Publishing AG, 2021 |
| Descrizione fisica | 1 online resource (412 p.) |
| Altri autori (Persone) |
MetzgerAndreas
ZillnerSonja PazzagliaJean-Christophe García RoblesAna |
| Collana | Computer Science Series |
| Soggetto topico |
Information retrieval
Business & management Research & development management Information technology industries Databases |
| Soggetto non controllato |
Information Storage and Retrieval
Business and Management, general Innovation/Technology Management The Computer Industry Big Data Innovation and Technology Management Technology Commercialization Digital Transformation Innovation Spaces Data-Driven Innovation Data Analytics Technology Management Data Ecosystems Data Protection Big Data Business Models Open Access Information retrieval Data warehousing Business & Management Research & development management Industrial applications of scientific research & technological innovation Information technology industries Databases |
| ISBN | 3-030-68176-9 |
| Classificazione | BUS042000BUS070030BUS087000COM021000COM030000 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Foreword -- Foreword -- Foreword -- Preface -- Acknowledgements -- Contents -- Editors and Contributors -- Part I: Ecosystem Elements of Big Data Value -- The European Big Data Value Ecosystem -- 1 Introduction -- 2 What Is Big Data Value? -- 3 Strategic Importance of Big Data Value -- 4 Developing a European Big Data Value Ecosystem -- 4.1 Challenges -- 4.2 A Call for Action -- 4.3 The Big Data Value PPP (BDV PPP) -- 4.4 Big Data Value Association -- 5 The Elements of Big Data Value -- 5.1 Ecosystem Elements of Big Data Value -- 5.2 Research and Innovation Elements of Big Data Value -- 5.3 Business, Policy and Societal Elements of Big Data Value -- 5.4 Emerging Elements of Big Data Value -- 6 Summary -- References -- Stakeholder Analysis of Data Ecosystems -- 1 Introduction -- 2 Stakeholder Analysis -- 3 Who Is a Stakeholder? -- 4 Methodology -- 4.1 Phase 1: Case Studies -- 4.2 Phase 2: Cross-Case Analysis -- 5 Sectoral Case Studies -- 6 Cross-Case Analysis -- 6.1 Technology Adoption Stage -- 6.2 Data Value Chain -- 6.3 Strategic Impact of IT -- 6.4 Stakeholder Characteristics -- 6.5 Stakeholder Influence -- 7 Summary -- References -- A Roadmap to Drive Adoption of Data Ecosystems -- 1 Introduction -- 2 Challenges for the Adoption of Big Data Value -- 3 Big Data Value Public-Private Partnership -- 3.1 The Big Data Value Ecosystem -- 4 Five Mechanism to Drive Adoption -- 4.1 European Innovation Spaces (i-Spaces) -- 4.2 Lighthouse Projects -- 4.3 Technical Projects -- 4.4 Platforms for Data Sharing -- 4.4.1 Industrial Data Platforms (IDP) -- 4.4.2 Personal Data Platforms (PDP) -- 4.5 Cooperation and Coordination Projects -- 5 Roadmap for Adoption of Big Data Value -- 6 European Data Value Ecosystem Development -- 7 Summary -- References -- Achievements and Impact of the Big Data Value Public-Private Partnership: The Story so Far.
1 Introduction -- 2 The Big Data Value PPP -- 2.1 BDV PPP Vision and Objectives for European Big Data Value -- 2.2 Big Data Value Association (BDVA) -- 2.3 BDV PPP Objectives -- 2.4 BDV PPP Governance -- 2.5 BDV PPP Monitoring Framework -- 3 Main Activities and Achievements During 2018 -- 3.1 Mobilisation of Stakeholders, Outreach, Success Stories -- 4 Monitored Achievements and Impact of the PPP -- 4.1 Achievement of the Goals of the PPP -- 4.2 Progress Achieved on KPIs -- 4.2.1 Private Investments -- 4.2.2 Job Creation, New Skills and Job Profiles -- 4.2.3 Impact of the BDV PPP on SMEs -- 4.2.4 Innovations Emerging from Projects -- 4.2.5 Supporting Major Sectors and Major Domains with Big Data Technologies and Applications -- 4.2.6 Experimentation -- 4.2.7 SRIA Implementation and Update -- 4.2.8 Technical Projects -- 4.2.9 Macro-economic KPIs -- 4.2.10 Contributions to Environmental Challenges -- 4.2.11 Standardisation Activities with European Standardisation Bodies -- 5 Summary and Outlook -- References -- Part II: Research and Innovation Elements of Big Data Value -- Technical Research Priorities for Big Data -- 1 Introduction -- 2 Methodology -- 2.1 Technology State of the Art and Sector Analysis -- 2.2 Subject Matter Expert Interviews -- 2.3 Stakeholder Workshops -- 2.4 Requirement Consolidation -- 2.5 Community Survey -- 3 Research Priorities for Big Data Value -- 3.1 Priority `Data Management´ -- 3.1.1 Challenges -- 3.1.2 Outcomes -- 3.2 Priority `Data Processing Architectures´ -- 3.2.1 Challenges -- 3.2.2 Outcomes -- 3.3 Priority `Data Analytics´ -- 3.3.1 Challenges -- 3.3.2 Outcomes -- 3.4 Priority `Data Visualisation and User Interaction´ -- 3.4.1 Challenges -- 3.4.2 Outcomes -- 3.5 Priority `Data Protection´ -- 3.5.1 Challenges -- 3.5.2 Outcomes -- 4 Big Data Standardisation -- 5 Engineering and DevOps for Big Data -- 5.1 Challenges. 5.2 Outcomes -- 6 Illustrative Scenario in Healthcare -- 7 Summary -- References -- A Reference Model for Big Data Technologies -- 1 Introduction -- 2 Reference Model -- 2.1 Horizontal Concerns -- 2.1.1 Data Visualisation and User Interaction -- 2.1.2 Data Analytics -- 2.1.3 Data Processing Architectures -- 2.1.4 Data Protection -- 2.1.5 Data Management -- 2.1.6 Cloud and High-Performance Computing (HPC) -- 2.1.7 IoT, CPS, Edge and Fog Computing -- 2.2 Vertical Concerns -- 2.2.1 Big Data Types and Semantics -- 2.2.2 Standards -- 2.2.3 Communication and Connectivity -- 2.2.4 Cybersecurity -- 2.2.5 Engineering and DevOps for Building Big Data Value Systems -- 2.2.6 Marketplaces, Industrial Data Platforms and Personal Data Platforms (IDPs/PDPs), Ecosystems for Data Sharing and Innovat... -- 3 Transforming Transport Case Study -- 3.1 Data Analytics -- 3.2 Data Visualisation -- 3.3 Data Management -- 3.4 Assessing the Impact of Big Data Technologies -- 3.5 Use Case Conclusion -- 4 Summary -- References -- Data Protection in the Era of Artificial Intelligence: Trends, Existing Solutions and Recommendations for Privacy-Preserving T... -- 1 Introduction -- 1.1 Aim of the Chapter -- 1.2 Context -- 2 Challenges to Security and Privacy in Big Data -- 3 Current Trends and Solutions in Privacy-Preserving Technologies -- 3.1 Trend 1: User-Centred Data Protection -- 3.2 Trend 2: Automated Compliance and Tools for Transparency -- 3.3 Trend 3: Learning with Big Data in a Privacy-Friendly and Confidential Way -- 3.4 Future Direction for Policy and Technology Development: Implementing the Old and Developing the New -- 4 Recommendations for Privacy-Preserving Technologies -- References -- A Best Practice Framework for Centres of Excellence in Big Data and Artificial Intelligence -- 1 Introduction -- 2 Innovation Ecosystems and Centres of Excellence. 2.1 What Are Centres of Excellence? -- 3 Methodology -- 4 Best Practice Framework for Big Data and Artificial Intelligence Centre of Excellence -- 4.1 Environment -- 4.1.1 Industry -- 4.1.2 Policy -- 4.1.3 Societal -- 4.2 Strategic Capabilities -- 4.2.1 Strategy -- 4.2.2 Governance -- 4.2.3 Structure -- 4.2.4 Funding -- 4.2.5 People -- 4.2.6 Culture -- 4.3 Operational Capabilities -- 4.4 Impact -- 4.4.1 Economic Impact -- 4.4.2 Scientific Impact -- 4.4.3 Societal Impact -- 4.4.4 Impact Measured Through KPIs -- 5 How to Use the Framework -- 5.1 Framework in Action -- 6 Critical Success Factors for Centres of Excellence -- 6.1 Challenges -- 6.2 Success Factors -- 6.3 Mechanisms to Address Challenges -- 6.4 Ideal Situation -- 7 Summary -- References -- Data Innovation Spaces -- 1 Introduction -- 2 Introduction to the European Data Innovation Spaces -- 3 Key Elements of an i-Space -- 4 Role of an i-Space and its Alignment with Other Initiatives -- 5 BDVA i-Spaces Certification Process -- 6 Impact of i-Spaces in Their Local Innovation Ecosystems -- 7 Cross-Border Collaboration: Towards a European Federation of i-Spaces -- 8 Success Stories -- 8.1 CeADAR: Ireland´s Centre for Applied Artificial Intelligence -- 8.2 CINECA -- 8.3 EGI -- 8.4 EURECAT/Big Data CoE Barcelona -- 8.5 ITAINNOVA/Aragon DIH -- 8.6 ITI/Data Cycle Hub -- 8.7 Know-Center -- 8.8 NCSR Demokritos/Attica Hub for the Economy of Data and Devices (ahedd) -- 8.9 RISE/ICE by RISE -- 8.10 Smart Data Innovation Lab (SDIL) -- 8.11 TeraLab -- 8.12 Universidad Politécnica de Madrid/Madrid´s i-Space for Sustainability/AIR4S DIH -- 9 Summary -- Reference -- Part III: Business, Policy, and Societal Elements of Big Data Value -- Big Data Value Creation by Example -- 1 Introduction -- 2 How Can Big Data Transform Everyday Mobility and Logistics?. 3 Digitalizing Forestry by Harnessing the Power of Big Data -- 4 GATE: First Big Data Centre of Excellence in Bulgaria -- 5 Beyond Privacy: Ethical and Societal Implications of Data Science -- 6 A Three-Year Journey to Insights and Investment -- 7 Scaling Up Data-Centric Start-Ups -- 8 Campaign Booster -- 9 AI Technology Meets Animal Welfare to Sustainably Feed the World -- 10 Creating the Next Generation of Smart Manufacturing with Federated Learning -- 11 Towards Open and Agile Big Data Analytics in Financial Sector -- 12 Electric Vehicles for Humans -- 13 Enabling 5G in Europe -- 14 Summary -- References -- Business Models and Ecosystem for Big Data -- 1 Introduction -- 2 Big Data Business Approaches -- 2.1 Optimisation and Improvements -- 2.2 Upgrading and Revaluation -- 2.3 Monetising -- 2.4 Breakthrough -- 3 Data-Driven Business Opportunities -- 4 Leveraging the Data Ecosystems -- 4.1 Data-Sharing Ecosystem -- 4.2 Data Innovation Ecosystems -- 4.3 Value Networks in a Business Ecosystem -- 5 Data-Driven Innovation Framework and Success Stories -- 5.1 The Data-Driven Innovation Framework -- 5.2 Examples of Success Stories -- 5.2.1 Selectionnist -- 5.2.2 Arable -- 6 Conclusion -- References -- Innovation in Times of Big Data and AI: Introducing the Data-Driven Innovation (DDI) Framework -- 1 Introduction -- 2 Data-Driven Innovation -- 2.1 What Are Business Opportunities? -- 2.2 Characteristics of Data-Driven Innovation -- 2.3 How to Screen Data-Driven Innovation? -- 3 The ``Making-of´´ the DDI Framework -- 3.1 State-of-the-Art Analysis -- 3.2 DDI Ontology Building -- 3.3 Data Collection and Coding -- 3.3.1 Selection Criteria -- 3.3.2 Sample Data Generation -- 3.3.3 Coding of Data -- 3.4 Data Analysis -- 4 Findings of the Empirical DDI Research Study -- 4.1 General Findings -- 4.2 Value Proposition -- 4.3 Data -- 4.4 Technology. 4.5 Network Strategies. |
| Record Nr. | UNINA-9910488709403321 |
|
Curry Edward
|
||
| Cham, : Springer International Publishing AG, 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
The Innovation revolution in agriculture : a roadmap to value creation / / edited by Hugo Campos
| The Innovation revolution in agriculture : a roadmap to value creation / / edited by Hugo Campos |
| Autore | Campos Hugo |
| Edizione | [First edition, 2021.] |
| Pubbl/distr/stampa | Springer Nature, 2021 |
| Descrizione fisica | 1 online resource (xix, 234 pages) : colour illustrations; digital, PDF file(s) |
| Disciplina | 630 |
| Soggetto topico |
Agriculture
Management Industrial management |
| Soggetto non controllato |
Agriculture
Innovation/Technology Management Business and Management value creation business model agricultural innovation open innovation design thinking open access Agricultural science Research & development management Industrial applications of scientific research & technological innovation |
| ISBN | 3-030-50991-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Foreword -- The Quest for Innovation: Addressing User Needs and Value Creation -- Productivity in Agriculture for a Sustainable Future -- Open innovation and value creation in crop genetics -- Rethinking adoption and diffusion as a collective social process. Towards an interactional perspective -- Development of Sustainable Business Models for Innovation in the Swedish Agri-sector - Resource-effective Producer or Stewardship-based Entrepreneur? -- Innovating at marketing and distributing nutritious foods at the Base of the Pyramid (BoP) - Insights from 2SCALE, the largest incubator for inclusive agribusiness in Africa -- Innovation and the quest to feed the world -- Digital Technologies, Big Data, and Agricultural Innovation -- Index. |
| Record Nr. | UNINA-9910420942003321 |
|
Campos Hugo
|
||
| Springer Nature, 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||