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New Version of Personal Information Protection Act and Personal Information Protection & Administration System

I.Summary

In 1995, the Computer-Processed Personal Data Protection Law was implemented in the Republic of China.  With the constant development of information technology and the limitations in the application of the legislation, the design of the original legal system is no longer consistent with practical requirements. Considering the increasing number of incidents of personal data leaks, discussions were carried out over a long period of time and the new version of the Personal Information Protection Act was passed after three readings in April, 2010. The title of the law was changed to Personal Information Protection Act. The new system has been officially implemented since 1 October, 2012. The new Act not only revised the provisions of the law in a comprehensive way, but also significantly increased the obligations and responsibilities of enterprises. In terms of civil liability, the maximum amount of compensation for a single incident is 200 Million NTD. For domestic industries, how to effectively respond to the requirements under the Personal Information Protection Act and adopt proper corresponding measures to lower the risk has become a key task for enterprise operation.

II. Main Points

1. Implementation of the Enforcement Rules of the Personal Information Protection Act

Personal information protection can be said the most concerned issue in Taiwan recently. As a matter of fact, the Computer-Processed Personal Data Protection Law was established in Taiwan as early as August 1995. After more than 10 years of development, computer and information technology has evolved significantly, and many emerging business models such as E-commerce are extensively collecting personal data. It has become increasingly important to properly protect personal privacy. However, the previous Computer-Processed Personal Data Protection Law was only applicable to certain industries, i.e. the following 8 specific industries: the credit investigation business, hospital, school, telecommunication business, financial business, securities business, insurance business, and mass media. And other business was  designated by the Ministry of Justice and the central government authorities in charge of concerned enterprises. In addition, the law only protected personal information that was processed by “computer or automatic equipment”.  Personal information that was not computer processed was not included.  There were clearly no sufficient regulations for the protection of personal data privacy and interest.

There were numerous incidents of personal data leaks. Among the top 10 consumer news issued by the Consumer Protection Committee of the Executive Yuan in 2007, “incidents of personal data leaks through E-commerce and TV shopping” was on the top of the list. This provoked the Ministry of Justice and the Ministry of Economic Affairs to “jointly designate” the retail industry without physical boutique (including 3 transaction models: online shopping, catalogue shopping and TV shopping) to be governed by the Computer-Processed Personal Data Protection Law since 1 July 2010.

To allow the provisions of the personal information protection legal system to meet the environment of rapid change, the Executive Yuan proposed a Draft Amendment to the Computer-Processed Personal Data Protection Law very early and changed the title to the Personal Information Protection Act. The draft was discussed many times in the Legislative Yuan. Personal Information Protection Act was finally passed after three readings in April 2010, which was officially published by the Office of the President on 26 May.

Although the new law was passed in April 2010, to allow sufficient time for enterprises and the public to understand and comply the new law, the new version of the personal information protection law was not implemented on the date of publication. In accordance with Article 56 of the Act, the date of implementation was to be further established by the Executive Yuan. After discussions over a long period of time, the Executive Yuan decided for the Personal Information Protection Act to be officially implemented on 1 October 2012. However, the implementation of two articles is withheld: Article 6 of the Act about the principal prohibition against the collection, processing and use of special personal information and Article 54 about the obligation to notice the Party within one year for personal information indirectly acquired before the implementation of the new law.

In terms of the personal data protection legal system, other than the most important Personal Data Protection Act, the enforcement rules established in accordance with the main law also play a key role. The previous Enforcement Rules of the Computer-Processed Personal Data Protection Law were published and implemented on 1 May, 1996. Considering that the Computer-Processed Personal Data Protection Law was amended in 2010 and that its title has been changed to the Personal Data Protection Act, the Ministry of Justice also followed the amended provisions under the new law and actively studied the Draft Amendment to the Enforcement Rules of the Computer-Processed Personal Data Protection Act. After it was confirmed that the new version of the Personal Data Protection Act would be officially launched on 1 October 2012, the Ministry of Justice announced officially the amended enforcement rules on 26 September, 2012. The title of the enforcement rules was also amended to the Enforcement Rules of the Personal Data Protection Act. The new version of personal data protection law and enforcement rules was thus officially launched, creating a brand new era for the promotion of personal data protection in Taiwan.

II. Personal Data Administration System and Information Privacy Protection Charter

Before the amendment to the Personal Data Protection Act was passed, the Legislative Yuan made a proposal to the government in June 2008 to promote a privacy administration and protection certification system in Taiwan, in reference to foreign practices. In August of the following year, the Strategic Review Board of the Executive Yuan passed a resolution to promote the E-Commerce Personal Data Administration and Information Security Action Plan. In December of the same year, approval was granted for the plan to be included in the key government promotion plans from 2010 to 2013.

Based on this action plan, since October 2010, the Ministry of Economic Affairs has asked the Institution for Information Industry to execute an E-Commerce Personal Data Administration System Setup Plan.  Since 2012, the E-Commerce Personal Data Administration System Promotion Plan and the Taiwan Personal Information Protection and Administration System (TPIPAS) have been established and promoted, with the objective of procuring enterprises to, while complying with the personal data protection legal system, properly protect consumers’ personal information through the establishment of an internal administration mechanism and ensuring that the introducing enterprises meet the requirements of the system. The issuance of the Data Privacy Protection Mark (dp.mark) was also used as an objective benchmark for consumers to judge the enterprise’s ability to maintain privacy.  

Regarding the introduction of the personal data administration system, enterprises should establish a content administration mechanism step by step in accordance with the Regulations for Taiwan Personal Information Protection and Administration System. Such system also serves as the review benchmark to decide whether domestic enterprises can acquire the Data Privacy Protection Mark (dp.mark). Since domestic enterprises did not have experience in establishing internal personal data administration system in the past, starting 2011, under the Taiwan Personal Information Protection and Administration System, enterprises received assistance in the training of system professionals such as Personal Data Administrators and Personal Data Internal Appraisers. Quality personal data administrators can help enterprises establish complete internal systems. Internal appraisers play the role of confirming whether the systems established by the enterprises are consistent with the system requirements. As of 2012, there are almost 100 enterprises in Taiwan that participate in the training of system staff and a total of 426 administrators and 131 internal appraisers.  In terms of the introduction of TPIPAS, in additional to the establishment and introduction of administration systems by qualified administrators, enterprises can also seek assistance from external professional consulting institutions. Under the Taiwan Personal Information Protection and Administration System, applications for registration of consulting institutions became available in 2012. Qualified system consulting institutions are published on the system website. Today 9 qualified consulting institutions have completed their registrations, providing enterprises with personal data consulting services.

After an enterprise completes the establishment of its internal administration system, it may file an application for certification under the Taiwan Personal Information Protection and Administration System.  The certification process includes two steps: “written review” and “site review”. After the enterprise passing certification, it is qualified to use the Data Privacy Protection Mark (dp.mark). Today 7 domestic companies have passed TPIPAS certification and acquired the dp.mark: 7net, FamiPort, books.com.tw, LOTTE, GOHAPPY, PAYEASY and Sinya Digital, reinforcing the maintenance of consumer privacy information through the introduction of personal data administration system.

III. Event Analysis

The Taiwan Personal Information Protection and Administration System (TPIPAS) is a professional personal data administration system established based on the provisions of the latest version of the domestic Personal Data Protection Act, in reference to the latest requirements of personal data protection by international organizations and the experience of main countries in promoting personal data administration system. In accordance with the practical requirements to protect personal data by industries, TPIPAS converted professional legal conditions into an internal personal data administration procedure to effectively assist industries to establish a complete and proper personal data administration system and to comply with the requirements of personal data legislations. With the launch of the new version of the Personal Data Protection Act, introducing TPIPAS and acquiring dp.mark are the best strategies for enterprises to lower the risk from the personal data protection law and to upgrade internal personal data administration capability.

※New Version of Personal Information Protection Act and Personal Information Protection & Administration System,STLI, https://stli.iii.org.tw/en/article-detail.aspx?no=105&tp=2&i=168&d=6370 (Date:2023/06/08)
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Blockchain and General Data Protection Regulation (GDPR) compliance issues (2019)

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Finally, we discuss the common technical characteristics of blockchain and how it is applicable to GDPR. 1. Data on the blockchain is personal data protected by GDPR? 　　First of all, starting from the technical characteristics of the blockchain, blockchain technology is commonly decentralized, anonymous, immutable, trackable and encrypted. The other five major characteristics are immutability, authenticity, transparency, uniqueness, and collective consensus. 　　Further, the blockchain is an open, decentralized ledger technology that can effectively verify and permanently store transactions between two parties, and can be proved. 　　It is a distributed database, all users on the chain can access to the database and the history record, also can directly verify transaction records. Each nodes use peer-to-peer transmission for upload or transfer information without third-party intermediation, which is the unique “decentralization” feature of the blockchain. 　　In addition, the node or any user on the chain has a unique and identifiable set of more than 30 alphanumeric addresses, but the user may choose to be anonymous or provide identification, which is also a feature of transparency with pseudonymity[2]; Data on blockchain is irreversibility of records. 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(1) What is Anonymization? 　　According to Opinion 05/2014 on Anonymization Techniques by Article 29 Data Protection Working Party of the European Union, “anonymization” is a technique applied to personal data in order to achieve irreversible de-identification[4]. 　　And it also said the “Hash function” of blockchain is a pseudonymization technology, the personal data is possible to be re-identified. Therefore it’s not an “anonymization”, the data on the blockchain may still be the personal data stipulated by the GDPR. 　　As the blockchain evolves, it will be possible to develop technologies that are not regulated by GDPR, such as part of the encryption process, which will be able to pass the court or European data protection authorities requirement of anonymization. There are also many compliance solutions which use technical in the industry, such as avoiding transaction data stored directly on the chain. 2. International data transmission 　　Furthermore, in accordance with Article 3 of the GDPR, “This Regulation applies to the processing of personal data in the context of the activities of an establishment of a controller or a processor in the Union, regardless of whether the processing takes place in the Union or not. This Regulation applies to the processing of personal data of data subjects who are in the Union by a controller or processor not established in the Union, where the processing activities are related to: (a) the offering of goods or services, irrespective of whether a payment of the data subject is required, to such data subjects in the Union; or (b) the monitoring of their behaviour as far as their behaviour takes place within the Union”.[5] 　　In other words, GDPR applies only when the data on the blockchain is not anonymized, and involves the processing of personal data of EU citizens. 3. Identification of data controllers and data processors 　　Therefore, if the encryption technology involves the public storage of EU citizens' personal data and passes it to a third-party controller, it may be identified as the “data controller” under Article 4 of GDPR, and all nodes and miners of the platform may be deemed as the “co-controller” of the data, and be assumed joint responsibility with the data controller by GDPR. For example, the parties can claim the right to delete data from the data controller. 　　In addition, a blockchain operator may be identified as a “processor”, for example, Backend as a Service (BaaS) products, the third parties provide network infrastructure for users, and let users manage and store personal data. Such Cloud Services Companies provide online services on behalf of customers, do not act as “data controllers”. Some commentators believe that in the case of private chains or alliance chains, such as land records transmission, inter-bank customer information sharing, etc., compared to public chain applications: such as cryptocurrencies (Bitcoin for example), is not completely decentralized, and more likely to meet GDPR requirements[6]. For example, in the case of a private chain or alliance chain, it is a closed platform, which contains only a small number of trusted nodes, is more effective in complying with the GDPR rules. 4. Data subject claims 　　In accordance with Article 17 of the GDPR, The data subject shall have the right to obtain from the controller the erasure of personal data concerning him or her without undue delay and the controller shall have the obligation to erase personal data without undue delay under some grounds. 　　Off-chain storage technology can help the blockchain industry comply with GDPR rules, allowing offline storage of personal data, or allow trusted nodes to delete the private key of encrypted information, which leaving data that cannot be read and identified on the chain. If the data is in accordance with the definition of anonymization by GDPR, there is no room for GDPR to be applied. IV. Conclusion 　　In summary, it’s seem that the application of blockchain to GDPR may include: (a) being difficulty to identified the data controllers and data processors after the data subject upload their data. (b) the nature of decentralized storage is transnational storage, and Whether the country where the node is located, is meets the “adequacy decision” of Article 45 of the GDPR. 　　If it cannot be met, then it needs to consider whether it conforms to the transfers subject to appropriate safeguards of Article 46, or the derogations for specific situations of Article 49 of the GDPR. Reference: [1] How to Trade Cryptocurrency: A Guide for (Future) Millionaires, https://wikijob.com/trading/cryptocurrency/how-to-trade-cryptocurrency [2] DONNA K. HAMMAKER, HEALTH RECORDS AND THE LAW 392 (5TH ED. 2018). [3] Iansiti, Marco, and Karim R. Lakhani, The Truth about Blockchain, Harvard Business Review 95, no. 1 (January-February 2017): 118-125, available at https://hbr.org/2017/01/the-truth-about-blockchain [4] Article 29 Data Protection Working Party, Opinion 05/2014 on Anonymisation Techniques (2014), https://www.pdpjournals.com/docs/88197.pdf [5] Directive 95/46/EC (General Data Protection Regulation), https://eur-lex.europa.eu/legal-content/EN/TXT/HTML/?uri=CELEX:32016R0679&from=EN [6] Queen Mary University of London, Are blockchains compatible with data privacy law? https://www.qmul.ac.uk/media/news/2018/hss/are-blockchains-compatible-with-data-privacy-law.html

The opening and sharing of scientific data- The Data Policy of the U.S. National Institutes of Health

The opening and sharing of scientific data- The Data Policy of the U.S. National Institutes of Health Li-Ting Tsai 　　Scientific research improves the well-being of all mankind, the data sharing on medical and health promote the overall amount of energy in research field. For promoting the access of scientific data and research findings which was supported by the government, the U.S. government affirmed in principle that the development of science was related to the retention and accesses of data. The disclosure of information should comply with legal restrictions, and the limitation by time as well. For government-sponsored research, the data produced was based on the principle of free access, and government policies should also consider the actual situation of international cooperation[1]Furthermore, the access of scientific research data would help to promote scientific development, therefore while formulating a sharing policy, the government should also consider the situation of international cooperation, and discuss the strategy of data disclosure based on the principle of free access. 　　In order to increase the effectiveness of scientific data, the U.S. National Institutes of Health (NIH) set up the Office of Science Policy (OSP) to formulate a policy which included a wide range of issues, such as biosafety (biosecurity), genetic testing, genomic data sharing, human subjects protections, the organization and management of the NIH, and the outputs and value of NIH-funded research. Through extensive analysis and reports, proposed emerging policy recommendations.[2] At the level of scientific data sharing, NIH focused on "genes and health" and "scientific data management". The progress of biomedical research depended on the access of scientific data; sharing scientific data was helpful to verify research results. Researchers integrated data to strengthen analysis, promoted the reuse of difficult-generated data, and accelerated research progress.[3] NIH promoted the use of scientific data through data management to verify and share research results. 　　For assisting data sharing, NIH had issued a data management and sharing policy (DMS Policy), which aimed to promote the sharing of scientific data funded or conducted by NIH.[4] DMS Policy defines “scientific data.” as “The recorded factual material commonly accepted in the scientific community as of sufficient quality to validate and replicate research findings, regardless of whether the data are used to support scholarly publications. Scientific data do not include laboratory notebooks, preliminary analyses, completed case report forms, drafts of scientific papers, plans for future research, peer reviews, communications with colleagues, or physical objects, such as laboratory specimens.”[5] In other words, for determining scientific data, it is not only based on whether the data can support academic publications, but also based on whether the scientific data is a record of facts and whether the research results can be repeatedly verified. 　　In addition, NIH, NIH research institutes, centers, and offices have had expected sharing of data, such as: scientific data sharing, related standards, database selection, time limitation, applicable and presented in the plan; if not applicable, the researcher should propose the data sharing and management methods in the plan. NIH also recommended that the management and sharing of data should implement the FAIR (Findable, Accessible, Interoperable and Reusable) principles. The types of data to be shared should first in general descriptions and estimates, the second was to list meta-data and other documents that would help to explain scientific data. NIH encouraged the sharing of scientific data as soon as possible, no later than the publication or implementation period.[6] It was said that even each research project was not suitable for the existing sharing strategy, when planning a proposal, the research team should still develop a suitable method for sharing and management, and follow the FAIR principles. 　　The scientific research data which was provided by the research team would be stored in a database which was designated by the policy or funder. NIH proposed a list of recommended databases lists[7], and described the characteristics of ideal storage databases as “have unique and persistent identifiers, a long-term and sustainable data management plan, set up metadata, organizing data and quality assurance, free and easy access, broad and measured reuse, clear use guidance, security and integrity, confidentiality, common format, provenance and data retention policy”[8]. That is to say, the design of the database should be easy to search scientific data, and should maintain the security, integrity and confidentiality and so on of the data while accessing them. 　　In the practical application of NIH shared data, in order to share genetic research data, NIH proposed a Genomic Data Sharing (GDS) Policy in 2014, including NIH funding guidelines and contracts; NIH’s GDS policy applied to all NIHs Funded research, the generated large-scale human or non-human genetic data would be used in subsequent research. [9] This can effectively promote genetic research forward. 　　The GDS policy obliged researchers to provide genomic data; researchers who access genomic data should also abide by the terms that they used the Controlled-Access Data for research.[10] After NIH approved, researchers could use the NIH Controlled-Access Data for secondary research.[11] Reviewed by NIH Data Access Committee, while researchers accessed data must follow the terms which was using Controlled-Access Data for research reason.[12] The Genomic Summary Results (GSR) was belong to NIH policy,[13] and according to the purpose of GDS policy, GSR was defined as summary statistics which was provided by researchers, and non-sensitive data was included to the database that was designated by NIH.[14] Namely. NIH used the application and approval of control access data to strike a balance between the data of limitation access and scientific development. 　　For responding the COVID-19 and accelerating the development of treatments and vaccines, NIH's data sharing and management policy alleviated the global scientific community’s need for opening and sharing scientific data. This policy established data sharing as a basic component in the research process.[15] In conclusion, internalizing data sharing in the research process will help to update the research process globally and face the scientific challenges of all mankind together. [1]NATIONAL SCIENCE AND TECHNOLOGY COUNCIL, COMMITTEE ON SCIENCE, SUBCOMMITEE ON INTERNATIONAL ISSUES, INTERAGENCY WORKING GROUP ON OPEN DATA SHARING POLICY, Principles For Promoting Access To Federal Government-Supported Scientific Data And Research Findings Through International Scientific Cooperation (2016), 1, organized from Principles, at 5-8, https://obamawhitehouse.archives.gov/sites/default/files/microsites/ostp/NSTC/iwgodsp_principles_0.pdf (last visited December 14, 2020). [2]About Us, Welcome to NIH Office of Science Policy, NIH National Institutes of Health Office of Science Policy, https://osp.od.nih.gov/about-us/ (last visited December 7, 2020). [3]NIH Data Management and Sharing Activities Related to Public Access and Open Science, NIH National Institutes of Health Office of Science Policy, https://osp.od.nih.gov/scientific-sharing/nih-data-management-and-sharing-activities-related-to-public-access-and-open-science/ (last visited December 10, 2020). [4]Final NIH Policy for Data Management and Sharing, NIH National Institutes of Health Office of Extramural Research, Office of The Director, National Institutes of Health (OD), https://grants.nih.gov/grants/guide/notice-files/NOT-OD-21-013.html (last visited December 11, 2020). [5]Final NIH Policy for Data Management and Sharing, NIH National Institutes of Health Office of Extramural Research, Office of The Director, National Institutes of Health (OD), https://grants.nih.gov/grants/guide/notice-files/NOT-OD-21-013.html (last visited December 12, 2020). [6]Supplemental Information to the NIH Policy for Data Management and Sharing: Elements of an NIH Data Management and Sharing Plan, Office of The Director, National Institutes of Health (OD), https://grants.nih.gov/grants/guide/notice-files/NOT-OD-21-014.html (last visited December 13, 2020). [7]The list of databases in details please see：Open Domain-Specific Data Sharing Repositories, NIH National Library of Medicine, https://www.nlm.nih.gov/NIHbmic/domain_specific_repositories.html (last visited December 24, 2020). [8]Supplemental Information to the NIH Policy for Data Management and Sharing: Selecting a Repository for Data Resulting from NIH-Supported Research, Office of The Director, National Institutes of Health (OD), https://grants.nih.gov/grants/guide/notice-files/NOT-OD-21-016.html (last visited December 13, 2020). [9]NIH Genomic Data Sharing, National Institutes of Health Office of Science Policy, https://osp.od.nih.gov/scientific-sharing/genomic-data-sharing/ (last visited December 15, 2020). [10]NIH Genomic Data Sharing Policy, National Institutes of Health (NIH), https://grants.nih.gov/grants/guide/notice-files/NOT-OD-14-124.html (last visited December 17, 2020). [11]NIH Genomic Data Sharing Policy, National Institutes of Health (NIH), https://grants.nih.gov/grants/guide/notice-files/NOT-OD-14-124.html (last visited December 17, 2020). [12]id. [13]NIH National Institutes of Health Turning Discovery into Health, Responsible Use of Human Genomic Data An Informational Resource, 1, at 6, https://osp.od.nih.gov/wp-content/uploads/Responsible_Use_of_Human_Genomic_Data_Informational_Resource.pdf (last visited December 17, 2020). [14]Update to NIH Management of Genomic Summary Results Access, National Institutes of Health (NIH), https://grants.nih.gov/grants/guide/notice-files/NOT-OD-19-023.html (last visited December 17, 2020). [15]Francis S. Collins, Statement on Final NIH Policy for Data Management and Sharing, National Institutes of Health Turning Discovery Into Health, https://www.nih.gov/about-nih/who-we-are/nih-director/statements/statement-final-nih-policy-data-management-sharing (last visited December 14, 2020).

Legal Opinion Led to Science and Technology Law: By the Mechanism of Policy Assessment of Industry and Social Needs

With the coming of the Innovation-based economy era, technology research has become the tool of advancing competitive competence for enterprises and academic institutions. Each country not only has begun to develop and strengthen their competitiveness of industrial technology but also has started to establish related mechanism for important technology areas selected or legal analysis. By doing so, they hope to promote collaboration of university-industry research, completely bring out the economic benefits of the R & D. and select the right technology topics. To improve the depth of research cooperation and collect strategic advice, we have to use legislation system, but also social communication mechanism to explore the values and practical recommendations that need to be concerned in policy-making. This article in our research begins with establishing a mechanism for collecting diverse views on the subject, and shaping more efficient dialogue space. Finally, through the process of practicing, this study effectively collects important suggestions of practical experts.
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