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학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
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논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 발행연도
- 2017.11
- 수록면
- 169 - 192 (24page)
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초록· 키워드
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In its core, Industry 4.0 refers to the change of production processes under conditions of adaptive intelligent production systems. Instead of being governed by a centrally controlled and in advance optimized process of production, the change aims at a continuous self-optimization of the process, which seems to be possible only through continuous generation and processing of information and its governance by artificial intelligence, in particular machine learning technologies.
The following presentation will focus on the emerging data economy. However, the debate on data and its adequate legal framework was dominated for a long time by the data protection issue related to personal data and constitutional questions of self-determination in times of ubiquitous data generation in a connected world. Industry 4.0 shifts the attention to machine generated, non-personal data, its role in the innovation process and an adequate regulatory framework between rights of exclusion and rights of access. This turns out to be an important political question in the EU and Germany and leads to the discussion of various concepts and instruments to ensure the free flow of data on the one side and the need for protection of machine-generated data on the other side.
Before I display the current framework and its applicability to data and data sets, I will outline some characteristics of data, because the concept of data is not well defined. Data are often understood as representing the real world or attributes or characteristics thereof and they are taken on its face value, treated as being neutral, objective, pre-analytic in nature and as conveying the information. This might be called a container approach. However, data are in fact framed technically, economically, ethically, temporally and so on. I follow the hypothesis, that data do not exist independently of the context they are generated and interpreted within. Therefore, it is more about relations between different data and data sets instead of following a container approach. This has a lot of consequences with regard to the question of “data ownership”, which is a hot topic of the current discussion. I will display in the following, that neither the law of property or intellectual property covers currently non-personal data as a subject of protection. In fact, the governance framework is mainly a contractual one, often accompanied by factual arrangement, which obviously are sufficient for most of the business actors. This is compatible with economic analysis of the problem. It might be a more productive approach to think about data as an infrastructure of the data driven economy which would bring rights to access data pools, standards of data, interoperability etc. to the fore.
The following presentation will focus on the emerging data economy. However, the debate on data and its adequate legal framework was dominated for a long time by the data protection issue related to personal data and constitutional questions of self-determination in times of ubiquitous data generation in a connected world. Industry 4.0 shifts the attention to machine generated, non-personal data, its role in the innovation process and an adequate regulatory framework between rights of exclusion and rights of access. This turns out to be an important political question in the EU and Germany and leads to the discussion of various concepts and instruments to ensure the free flow of data on the one side and the need for protection of machine-generated data on the other side.
Before I display the current framework and its applicability to data and data sets, I will outline some characteristics of data, because the concept of data is not well defined. Data are often understood as representing the real world or attributes or characteristics thereof and they are taken on its face value, treated as being neutral, objective, pre-analytic in nature and as conveying the information. This might be called a container approach. However, data are in fact framed technically, economically, ethically, temporally and so on. I follow the hypothesis, that data do not exist independently of the context they are generated and interpreted within. Therefore, it is more about relations between different data and data sets instead of following a container approach. This has a lot of consequences with regard to the question of “data ownership”, which is a hot topic of the current discussion. I will display in the following, that neither the law of property or intellectual property covers currently non-personal data as a subject of protection. In fact, the governance framework is mainly a contractual one, often accompanied by factual arrangement, which obviously are sufficient for most of the business actors. This is compatible with economic analysis of the problem. It might be a more productive approach to think about data as an infrastructure of the data driven economy which would bring rights to access data pools, standards of data, interoperability etc. to the fore.
목차
〈ABSTRACT〉
Ⅰ. Industry 4. - A Multifaceted Notion
Ⅱ. The Emerging Data Economy
Ⅲ. What do We Mean When We Talk About Data?
Ⅳ. The Incomplete Governance Framework for Data
Ⅴ. Some Remarks on Economics of Data
Ⅵ. Conclusions
〈References〉
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