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Big Data, Databases and Ownership Rights in the Cloud 2020 ed. [Kõva köide]

  • Formaat: Hardback, 308 pages, kõrgus x laius: 235x155 mm, kaal: 670 g, 6 Illustrations, color; 10 Illustrations, black and white; XXV, 308 p. 16 illus., 6 illus. in color., 1 Hardback
  • Sari: Perspectives in Law, Business and Innovation
  • Ilmumisaeg: 12-Nov-2019
  • Kirjastus: Springer Verlag, Singapore
  • ISBN-10: 9811503486
  • ISBN-13: 9789811503481
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Big Data, Databases and Ownership Rights in the Cloud 2020 ed.Suurem pilt
  • Formaat: Hardback, 308 pages, kõrgus x laius: 235x155 mm, kaal: 670 g, 6 Illustrations, color; 10 Illustrations, black and white; XXV, 308 p. 16 illus., 6 illus. in color., 1 Hardback
  • Sari: Perspectives in Law, Business and Innovation
  • Ilmumisaeg: 12-Nov-2019
  • Kirjastus: Springer Verlag, Singapore
  • ISBN-10: 9811503486
  • ISBN-13: 9789811503481
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9789811503481.html

Two of the most important developments of this new century are the emergence of cloud computing and big data. However, the uncertainties surrounding the failure of cloud service providers to clearly assert ownership rights over data and databases during cloud computing transactions and big data services have been perceived as imposing legal risks and transaction costs. This lack of clear ownership rights is also seen as slowing down the capacity of the Internet market to thrive. Click-through agreements drafted on a take-it-or-leave-it basis govern the current state of the art, and they do not allow much room for negotiation. The novel contribution of this book proffers a new contractual model advocating the extension of the negotiation capabilities of cloud customers, thus enabling an automated and machine-readable framework, orchestrated by a cloud broker.

Cloud computing and big data are constantly evolving and transforming into new paradigms where cloud brokers are predicted to play a vital role as innovation intermediaries adding extra value to the entire life cycle. This evolution will alleviate the legal uncertainties in society by means of embedding legal requirements in the user interface and related computer systems or its code. This book situates the theories of law and economics and behavioral law and economics in the context of cloud computing and takes database rights and ownership rights of data as prime examples to represent the problem of collecting, outsourcing, and sharing data and databases on a global scale. It does this by highlighting the legal constraints concerning ownership rights of data and databases and proposes finding a solution outside the boundaries and limitations of the law.

By allowing cloud brokers to establish themselves in the market as entities coordinating and actively engaging in the negotiation of service-level agreements (SLAs), individual customers as well as small and medium-sized enterprises could efficiently and effortlessly choose a cloud provider that best suits their needs. This approach, which the author calls “plan-like architectures,” endeavors to create a more trustworthy cloud computing environment and to yield radical new results for the development of the cloud computing and big data markets. 

1 Introduction
1(18)
1.1 Problem Statement
6(2)
1.2 Summary of the Key Points Analyzed
8(1)
1.3 The Structure of This Book
9(3)
1.4 Methodology
12(2)
References
14(5)
Part I Fundamental Legal, Theoretical and Technical Issues
2 Database Rights in Big Data and the Cloud---Main Legal Considerations
19(32)
2.1 Introduction
19(1)
2.2 On the Legal Issues of Databases
20(8)
2.2.1 International Legal Framework
20(2)
2.2.2 Database Protection in the European Legal Framework: Justification for the Double Scheme of Protection
22(3)
2.2.3 The Necessity for the Legal Protection of Databases in the Cloud
25(1)
2.2.4 Motivations for Introducing the Database Right in the EU
26(2)
2.3 Database Rights: Legal Concepts and Main European Court Decisions
28(10)
2.3.1 "Obtaining" and "Creating" Data and the "Spin-Off Doctrine" in the Eyes of the CJEU
33(3)
2.3.2 Right to Access Information and "Sole Source" Databases
36(2)
2.3.3 Sui Generis Right Term of Protection
38(1)
2.4 Big Data and the Sui Generis Right Dilemma
38(4)
2.5 Database Right and Contract Law
42(4)
2.6 Summary and Interim Remarks
46(1)
References
46(5)
3 Brokers, Clouds and Databases---The Good, the Bad and the Ugly
51(28)
3.1 Introduction
51(1)
3.2 Databases: Background and Technical Definition
52(3)
3.2.1 A Few Examples of Databases in the Cloud
54(1)
3.3 Cloud Computing and Brokerage Scenarios
55(9)
3.3.1 Literature Review and Background Considerations
55(2)
3.3.2 The Cloud Metaphor
57(2)
3.3.3 Advantages of Cloud Computing: Main Capabilities
59(4)
3.3.4 Disadvantages of Cloud Computing: Some Related Technical and Legal Issues
63(1)
3.4 Cloud Deployment Models
64(4)
3.4.1 Public Cloud
65(1)
3.4.2 Private Cloud
66(1)
3.4.3 Community Cloud
66(1)
3.4.4 Hybrid Cloud
67(1)
3.5 Cloud Service Models
68(2)
3.5.1 Software as a Service (SaaS)
68(1)
3.5.2 Platform as a Service (PaaS)
69(1)
3.5.3 Infrastructure as a Service (IaaS)
69(1)
3.5.4 Software Infrastructure as a Service (SlaaS)
70(1)
3.6 Cloud Service Brokerage
70(2)
3.7 Summary and Interim Remarks
72(1)
References
73(6)
4 Law and Economics---Five Core Principles in the Cloud
79(30)
4.1 Introduction
79(1)
4.2 Literature Review and Background Considerations: The Three Schools of Thought
80(4)
4.2.1 Positive Law and Economics (Chicago-Style)
81(2)
4.2.2 Normative Law and Economics (Yale-Style)
83(1)
4.2.3 Functional School of Law and Economics (Virginia-Style)
84(1)
4.3 Combining the Three Schools of Thought: Five Core Principles
84(15)
4.3.1 Reducing Transaction Costs in the Cloud: "Filling the Gaps" in SLAs
85(3)
4.3.2 Turning Technological Negative Externalities into External Benefits: The "Bee Metaphor"
88(3)
4.3.3 "Ownership" Rights of Data as a Commons: Transforming "Tragedy" into "Comedy"
91(4)
4.3.4 Institutional Alternatives: The Foucault Pendulum of "Imperfect Choices in the Cloud"
95(2)
4.3.5 Social Network Analysis (SNA): Cloud Brokers as a Hub
97(2)
4.4 Summary and Interim Remarks
99(1)
References
100(9)
Part II A New Theoretical Framework
5 Plan-Like Architectures
109(24)
5.1 Introduction
109(1)
5.2 Plan Theory: We Are All Planning Agents
110(11)
5.2.1 Shared Agency Theory: From Individual Plans to Joint Plans
112(4)
5.2.2 Laws Are Plans
116(1)
5.2.3 Simple Logic of Planning
117(3)
5.2.4 Exclusionary Reasons
120(1)
5.3 Plan Theory in the Cloud: Plan-Like Architectures
121(7)
5.3.1 Brokers as Main Planners
121(3)
5.3.2 Code and Architecture Design
124(3)
5.3.3 SLAs as Plans
127(1)
5.4 Summary and Interim Remarks
128(1)
References
129(4)
6 Plans, Brokers and Trust
133(50)
6.1 Introduction
133(2)
6.2 Literature Review and Background Considerations
135(20)
6.2.1 Attitudes of Trust (and Distrust) Within Plan Theory
138(3)
6.2.2 Different Notions of Trust: A Kaleidoscopic and Critical View
141(12)
6.2.3 Delimiting the Concept of Trust
153(2)
6.3 The Role of Cloud Brokers for Strengthening Mutual Trust
155(15)
6.3.1 The Double Nature of Trust
158(2)
6.3.2 Deferring Accountability to Cloud Brokers
160(1)
6.3.3 Risk, Vulnerability and Threat
161(2)
6.3.4 Trust and Reputation: Beyond Track Records
163(3)
6.3.5 Gaining User's Trust Through Websites and Social Networks
166(2)
6.3.6 Blockchain 2.0: The "Trust Machine"
168(2)
6.4 Trust and Plan-Like Architectures: How It All Fits Together
170(1)
6.5 Summary and Interim Remarks
171(1)
References
172(11)
7 Framing Choice Architectures
183(28)
7.1 Introduction
183(2)
7.2 Literature Review and Background Considerations
185(11)
7.2.1 Two Ways of Thinking: "Fast" and "Slow"
188(1)
7.2.2 Nudge Theory and Cloud Brokerage Architectures
189(5)
7.2.3 Behavioral Market Failures, Different Types of Nudges and Soft Paternalism
194(2)
7.3 Turning Nudges into Simpler and More Effective SLAs
196(6)
7.3.1 Warning Signs for Risk Management in Cloud Brokerage
198(2)
7.3.2 Default Rules and Information Disclosure as Prime Nudges
200(2)
7.4 The Relation Between Plans, Nudges and Choice Architectures
202(1)
7.5 Summary and Interim Remarks
203(1)
References
203(8)
Part III A New Contractual Model
8 New Template for SLAs
211(50)
8.1 Introduction
211(2)
8.2 Background Considerations: SLAs and XML
213(2)
8.3 Empirical Study and Optimized Solutions
215(17)
8.3.1 Database Rights and the "Legal Glocalization" Conundrum
217(1)
8.3.2 Click-Through or Negotiated Terms? A Blended Approach
218(3)
8.3.3 "Ownership" Rights in Consumer Data
221(4)
8.3.4 "Ownership" Rights in Biological Data
225(7)
8.4 A Sui Generis Contractual Framework
232(22)
8.4.1 Automated Framework: The "Dead Man's Switch"
234(1)
8.4.2 XML-Based Description Schema
235(2)
8.4.3 Brokerage Workflow Process
237(3)
8.4.4 Unified Modeling Language and Pseudo-code
240(2)
8.4.5 Legal Questions for the Extraction of the Pseudo-code
242(12)
8.5 Summary and Interim Remarks
254(1)
References
254(7)
9 Towards a Legal Risk Assessment
261(36)
9.1 Introduction
261(2)
9.2 Risk Assessment: Literature Review, Motivation and Justification
263(4)
9.3 Risk Assessment Methodology
267(2)
9.3.1 High Level Analysis of the System
268(1)
9.3.2 Identifying the Assets Involved
268(1)
9.3.3 Identifying the Threats in Each Cloud Deployment Scenario
268(1)
9.4 Embracing Legal Risks and Enhancing Legal Interoperability
269(3)
9.5 Conventional Databases Versus Big Data: Striking the Right Balance
272(4)
9.5.1 Territorial Scope of Protection
273(1)
9.5.2 "Ownership" Rights of New Data Generated by Big Data
274(1)
9.5.3 Lack of International Legal and Contractual Standards
275(1)
9.6 Risk Assessment Techniques and Typical Actors Involved in Brokering WS-Agreements
276(2)
9.6.1 Typical Actors Involved
276(1)
9.6.2 Risk Assessment Techniques
277(1)
9.7 Risk Inventory Design for the Identification of Legal Risks
278(2)
9.8 Different Stages of Risk Assessment in Cloud Brokerage Scenarios (CBS)
280(3)
9.9 Use Case Scenarios: Examples
283(9)
9.9.1 Use Case 1: Cloud Services in Business Transactions
285(4)
9.9.2 Use Case 2: Genetic Research Projects Within Clinical Trials Scenarios
289(3)
9.10 Summary and Interim Remarks
292(1)
References
292(5)
10 Conclusion---Main Findings and Contributions to the Current Knowledge
297(6)
10.1 Theoretical Contribution
297(1)
10.2 Scientific Contribution
298(3)
References
301(2)
Index 303
Dr. Marcelo Corrales Compagnucci is Attorney-at-Law specializing in intellectual property (IP), information technology (IT) and corporate law. His research interests are the legal issues involved in disruptive innovation technologies. He is currently a Postdoctoral Researcher at the Centre for Advanced Studies in Biomedical Innovation Law (CeBIL), Faculty of Law, University of Copenhagen in Denmark. His past activities have included working as a consultant and lawyer for law firms and IT companies. He was also a research associate with the Institute for Legal Informatics (IRI) at Leibniz Unvirsität Hannover in Germany, and a visiting research fellow in various research centers around the world, including the Max Planck Institute for Comparative and International Private Law (Hamburg), the Max Planck Institute for Innovation and Competition (Munich), the Shepherd and Wedderburn Centre for Research in Intellectual Property and Technology (SCRIPT) within the University of Edinburgh in Scotland, and the Academia Sinica in Taiwan. He has a Doctor of Laws (LL.D.) degree from Kyushu University in Japan. He also holds a Master of Laws (LL.M.) in international economics and business law from Kyushu University, and an LL.M. in law and information technology and an LL.M. in European intellectual property law, both from the University of Stockholm in Sweden. He has several publications in the field of IT & IP Law. His most recent publications include New Technology, Big Data and the Law (Springer, 2017); Robotics, AI and the Future of Law (Springer, 2018); and Legal Tech, Smart Contracts and Blockchain (Springer, 2019).