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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).

 

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※The opening and sharing of scientific data- The Data Policy of the U.S. National Institutes of Health,STLI, https://stli.iii.org.tw/en/article-detail.aspx?no=55&tp=2&i=168&d=8594 (Date:2025/04/04)
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Tsai, Li-Ting
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Reviews on Taiwan Constitutional Court's Judgment no. 13 of 2022

Reviews on Taiwan Constitutional Court's Judgment no. 13 of 2022 2022/11/24 I.Introduction 　　In 2012, the Taiwan Human Rights Promotion Association and other civil groups believe that the National Health Insurance Administration released the national health insurance database and other health insurance data for scholars to do research without consent, which may be unconstitutional and petitioned for constitutional interpretation. 　　Taiwan Human Rights Promotion Association believes that the state collects, processes, and utilizes personal data on a large scale with the "Personal Data Protection Law", but does not set up another law of conduct to control the exercise of state power, which has violated the principle of legal retention; the data is provided to third-party academic research for use, and the parties involved later Excessive restrictions on the right to withdraw go against the principle of proportionality. 　　The claimant criticized that depriving citizens of their prior consent and post-control rights to medical data is like forcing all citizens to unconditionally contribute data for use outside the purpose before they can use health insurance. The personal data law was originally established to "avoid the infringement of personality rights and promote the rational use of data", but in the insufficient and outdated design of the regulations, it cannot protect the privacy of citizens' information from infringement, and it is easy to open the door to the use of data for other purposes. 　　In addition, even if the health insurance data is de-identified, it is still "individual data" that can distinguish individuals, not "overall data." Health insurance data can be connected with other data of the Ministry of Health and Welfare, such as: physical and mental disability files, sexual assault notification files, etc., and you can also apply for bringing in external data or connecting with other agency data. Although Taiwan prohibits the export of original data, the risk of re-identification may also increase as the number of sources and types of data concatenated increases, as well as unspecified research purposes. 　　The constitutional court of Taiwan has made its judgment on the constitutionality of the personal data usage of National Health Insurance research database. The judgment, released on August 12, 2022, states that Article 6 of Personal Data Protection Act(PDPA), which asks“data pertaining to a natural person's medical records, healthcare, genetics, sex life, physical examination and criminal records shall not be collected, processed or used unless where it is necessary for statistics gathering or academic research by a government agency or an academic institution for the purpose of healthcare, public health, or crime prevention, provided that such data, as processed by the data provider or as disclosed by the data collector, may not lead to the identification of a specific data subject”does not violate Intelligible principle and Principle of proportionality. Therefore, PDPA does not invade people’s right to privacy and remains constitutional. 　　However, the judgment finds the absence of independent supervisory authority responsible for ensuring Taiwan institutions and bodies comply with data protection law, can be unconstitutional, putting personal data protection system on the borderline to failure. Accordingly, laws and regulations must be amended to protect people’s information privacy guaranteed by Article 22 of Constitution of the Republic of China (Taiwan). 　　In addition, the judgment also states it is unconstitutional that Articles 79 and 80 of National Health Insurance Law and other relevant laws lack clear provisions in terms of store, process, external transmission of Personal health insurance data held by Central Health Insurance Administration of the Ministry of Health and Welfare. 　　Finally, the Central Health Insurance Administration of the Ministry of Health and Welfare provides public agencies or academic research institutions with personal health insurance data for use outside the original purpose of collection. According to the overall observation of the relevant regulations, there is no relevant provision that the parties can request to “opt-out”; within this scope, it violates the intention of Article 22 of the Constitution to protect people's right to information privacy. II.Independent supervisory authority 　　According to Article 3 of Central Regulations and Standards Act, government agencies can be divided into independent agencies that can independently exercise their powers and operate autonomously, and non- independent agencies that must obey orders from their superiors. In Taiwan, the so-called "dedicated agency"(專責機關) does not fall into any type of agency defined by the Central Regulations and Standards Act. Dedicated agency should be interpreted as an agency that is responsible for a specific business and here is no other agency to share the business. 　　The European Union requires member states to set up independent regulatory agencies (refer to Articles 51 and 52 of General Data Protection Regulation (GDPR)). In General Data Protection Regulation and the adequacy reference guidelines, the specific requirements for personal data supervisory agencies are as follows: the country concerned should have one or more independent supervisory agencies; they should perform their duties completely independently and cannot seek or accept instructions; the supervisory agencies should have necessary and practicable powers, including the power of investigation; it should be considered whether its staff and budget can effectively assist its implementation. Therefore, in order to pass the EU's adequacy certification and implement the protection of people's privacy and information autonomy, major countries have set up independent supervisory agencies for personal data protection based on the GDPR standards. 　　According to this research, most countries have 5 to 10 commissioners that independently exercise their powers to supervise data exchange and personal data protection. In order to implement the powers and avoid unnecessary conflicts of interests among personnel, most of the commissioners are full-time professionals. Article 3 of Basic Code Governing Central Administrative Agencies Organizations defines independent agency as "A commission-type collegial organization that exercises its powers and functions independently without the supervision of other agencies, and operates autonomously unless otherwise stipulated." It is similar to Japan, South Korea, and the United States. III.Right to Opt-out 　　The judgment pointed out that the parties still have the right to control afterwards the personal information that is allowed to be collected, processed and used without the consent of the parties or that meets certain requirements. Although Article 11 of PDPA provides for certain parties to exercise the right to control afterwards, it does not cover all situations in which personal data is used, such as: legally collecting, processing or using correct personal data, and its specific purpose has not disappeared, In the event that the time limit has not yet expired, so the information autonomy of the party cannot be fully protected, the subject, cause, procedure, effect, etc. of the request for suspension of use should be clearly stipulated in the revised law, and exceptions are not allowed. 　　The United Kingdom is of great reference. In 2017, after the British Information Commissioner's Office (ICO) determined that the data sharing agreement between Google's artificial intelligence DeepMind and the British National Health Service (NHS) violated the British data protection law, the British Department of Health and Social Care proposed National data opt-out Directive in May, 2018. British health and social care-related institutions may refer to the National Data Opt-out Operational Policy Guidance Document published by the National Health Service in October to plan the mechanism for exercising patient's opt-out right. The guidance document mainly explains the overall policy on the exercise of the right to opt-out, as well as the specific implementation of suggested practices, such as opt-out response measures, methods of exercising the opt-out right, etc. 　　National Data Opt-out Operational Policy Guidance Document also includes exceptions and restrictions on the right to opt-out. The Document stipulates that exceptions may limit the right to Opt-out, including: the sharing of patient data, if it is based on the consent of the parties (consent), the prevention and control of infectious diseases (communicable disease and risks to public health), major public interests (overriding) Public interest), statutory obligations, or cooperation with judicial investigations (information required by law or court order), health and social care-related institutions may exceptionally restrict the exercise of the patient's right to withdraw. 　　What needs to be distinguished from the situation in Taiwan is that when the UK first collected public information and entered it into the NHS database, there was already a law authorizing the NHS to search and use personal information of the public. The right to choose to enter or not for the first time; and after their personal data has entered the NHS database, the law gives the public the right to opt-out. Therefore, the UK has given the public two opportunities to choose through the enactment of special laws to protect public's right to information autonomy. 　　At present, the secondary use of data in the health insurance database does not have a complete legal basis in Taiwan. At the beginning, the data was automatically sent in without asking for everyone’s consent, and there was no way to withdraw when it was used for other purposes, therefore it was s unconstitutional. Hence, in addition to thinking about what kind of provisions to add to the PDPA as a condition for "exception and non-request for cessation of use", whether to formulate a special law on secondary use is also worthy of consideration by the Taiwan government. IV.De-identification 　　According to the relevant regulations of PDPA, there is no definition of "de-identification", resulting in a conceptual gap in the connotation. In other words, what angle or standard should be used to judge that the processed data has reached the point where it is impossible to identify a specific person. In judicial practice, it has been pointed out that for "data recipients", if the data has been de-identified, the data will no longer be regulated by PDPA due to the loss of personal attributes, and it is even further believed that de-identification is not necessary. 　　However, the Judgment No. 13 of Constitutional Court, pointed out that through de-identification measures, ordinary people cannot identify a specific party without using additional information, which can be regarded as personal data of de-identification data. Therefore, the judge did not give an objective standard for de-identification, but believed that the purpose of data utilization and the risk of re-identification should be measured on a case-by-case basis, and a strict review of the constitutional principle of proportionality should be carried out. So far, it should be considered that the interpretation of the de-identification standard has been roughly finalized. V.Conclusions 　　The judge first explained that if personal information is processed, the type and nature of the data can still be objectively restored to indirectly identify the parties, no matter how simple or difficult the restoration process is, if the data is restored in a specific way, the parties can still be identified. personal information. Therefore, the independent control rights of the parties to such data are still protected by Article 22 of the Constitution. 　　Conversely, when the processed data objectively has no possibility to restore the identification of individuals, it loses the essence of personal data, and the parties concerned are no longer protected by Article 22 of the Constitution. 　　Based on this, the judge declared that according to Article 6, Item 1, Proviso, Clause 4 of the PDPA, the health insurance database has been processed so that the specific party cannot be identified, and it is used by public agencies or academic research institutions for medical and health purposes. Doing necessary statistical or academic research complies with the principles of legal clarity and proportionality, and does not violate the Constitution. 　　However, the judge believes that the current personal data law or other relevant regulations still lack an independent supervision mechanism for personal data protection, and the protection of personal information privacy is insufficient. In addition, important matters such as personal health insurance data can be stored, processed, and transmitted externally by the National Health Insurance Administration in a database; the subject, purpose, requirements, scope, and method of providing external use; and organizational and procedural supervision and protection mechanisms, etc. Articles 79 and 80 of the Health Insurance Law and other relevant laws lack clear provisions, so they are determined to be unconstitutional. 　　In the end, the judge found that the relevant laws and regulations lacked the provisions that the parties can request to stop using the data, whether it is the right of the parties to request to stop, or the procedures to be followed to stop the use, there is no relevant clear text, obviously the protection of information privacy is insufficient. Therefore, regarding unconstitutional issues, the Constitutional Court ordered the relevant agencies to amend the Health Insurance Law and related laws within 3 years, or formulate specific laws.

The Key Elements for Data Intermediaries to Deliver Their Promise

The Key Elements for Data Intermediaries to Deliver Their Promise 2022/12/13 　　As human history enters the era of data economy, data has become the new oil. It feeds artificial intelligence algorithms that are disrupting how advertising, healthcare, transportation, insurance, and many other industries work. The excitement of having data as a key production input lies in the fact that it is a non-rivalrous good that does not diminish by consumption.[1] However, the fact that people are reluctant in sharing data due to privacy and trade secrets considerations has been preventing countries to realize the full value of data. [2] 　　To release more data, policymakers and researchers have been exploring ways to overcome the trust dilemma. Of all the discussions, data intermediaries have become a major solution that governments are turning to. This article gives an overview of relevant policy developments concerning data intermediaries and a preliminary analysis of the key elements that policymakers should consider for data intermediaries to function well. I. Policy and Legal developments concerning data intermediaries 　　In order to unlock data’s full value, many countries have started to focus on data intermediaries. For example, in 2021, the UK’s Department for Digital, Culture, Media and Sport (DCMS) commissioned the Centre for Data Ethics and Innovation (CDEI) to publish a report on data intermediaries[3] , in response to the 2020 National Data Strategy.[4] In 2020, the European Commission published its draft Data Governance Act (DGA)[5] , which aims to build up trust in data intermediaries and data altruism organizations, in response to the 2020 European Strategy for Data.[6] The act was adopted and approved in mid-2022 by the Parliament and Council; and will apply from 24 September 2023.[7] The Japanese government has also promoted the establishment of data intermediaries since 2019, publishing guidance to establish regulations on data trust and data banks.[8] II. Key considerations for designing effective data intermediary policy 1.Evaluate which type of data intermediary works best in the targeted country 　　From CDEI’s report on data intermediaries and the confusion in DGA’s various versions of data intermediary’s definition, one could tell that there are many forms of data intermediaries. In fact, there are at least eight types of data intermediaries, including personal information management systems (PIMS), data custodians, data exchanges, industrial data platforms, data collaboratives, trusted third parties, data cooperatives, and data trusts.[9] Each type of data intermediary was designed to combat data-sharing issues in specific countries, cultures, and scenarios. Hence, policymakers need to evaluate which type of data intermediary is more suitable for their society and market culture, before investing more resources to promote them. 　　For example, data trust came from the concept of trust—a trustee managing a trustor’s property rights on behalf of his interest. This practice emerged in the middle ages in England and has since developed into case law.[10] Thus, the idea of data trust is easily understood and trusted by the British people and companies. As a result, British people are more willing to believe that data trusts will manage their data on their behalf in their best interest and share their valuable data, compared to countries without a strong legal history of trusts. With more people sharing their data, trusts would have more bargaining power to negotiate contract terms that are more beneficial to data subjects than what individual data owners could have achieved. However, this model would not necessarily work for other countries without a strong foundation of trust law. 2.Quality signals required to build trust: A government certificate system can help overcome the lemon market problem 　　The basis of trust in data intermediaries depends largely on whether the service provider is really neutral in its actions and does not reuse or sell off other parties’ data in secret. However, without a suitable way to signal their service quality, the market would end up with less high-quality service, as consumers would be reluctant to pay for higher-priced service that is more secure and trustworthy when they have no means to verify the exact quality.[11] This lemon market problem could only be solved by a certificate system established by actors that consumers trust, which in most cases is the government. 　　The EU government clearly grasped this issue as a major obstacle to the encouragement of trust in data intermediaries and thus tackles it with a government register and verification system. According to the Data Government Act, data intermediation services providers who intend to provide services are required to notify the competent authority with information on their legal status, form, ownership structure, relevant subsidiaries, address, public website, contact details, the type of service they intend to provide, the estimated start date of activities…etc. This information would be provided on a website for consumers to review. In addition, they can request the competent authority to confirm their legal compliance status, which would in turn verify them as reliable entities that can use the ‘data intermediation services provider recognised in the Union’ label. 3.Overcoming trust issues with technology that self-enforces privacy: privacy-enhancing technologies (PETs) 　　Even if there are verified data intermediation services available, businesses and consumers might still be reluctant to trust human organizations. A way to boost trust is to adopt technologies that self-enforces privacy. A real-world example is OpenSAFELY, a data intermediary implementing privacy-enhancing technologies (PETs) to provide health data sharing in a secure environment. Through a federated analytics system, researchers are able to conduct research with large volumes of healthcare data, without the ability to observe any data directly. Under such protection, UK NHS is willing to share its data for research purposes. The accuracy and timeliness of such research have provided key insights to inform the UK government in decision-making during the COVID-19 pandemic. 　　With the benefits it can bring, unsurprisingly, PETs-related policies have become quite popular around the globe. In June 2022, Singapore launched its Digital Trust Centre (DTC) for accelerating PETs development and also signed a Memorandum of Understanding with the International Centre of Expertise of Montreal for the Advancement of Artificial Intelligence (CEIMIA) to collaborate on PETs.[12] On September 7th, 2022, the UK Information Commissioners’ Office (ICO) published draft guidance on PETs.[13] Moreover, the U.K. and U.S. governments are collaborating on PETs prize challenges, announcing the first phase winners on November 10th, 2022.[14] We could reasonably predict that more PETs-related policies would emerge in the coming year. [1] Yan Carrière-Swallow and Vikram Haksar, The Economics of Data, IMFBlog (Sept. 23, 2019), https://blogs.imf.org/2019/09/23/the-economics-of-data/#:~:text=Data%20has%20become%20a%20key,including%20oil%2C%20in%20important%20ways (last visited July 22, 2022). [2] Frontier Economics, Increasing access to data across the economy: Report prepared for the Department for Digital, Culture, Media, and Sport (2021), https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/974532/Frontier-access_to_data_report-26-03-2021.pdf (last visited July 22, 2022). [3] The Centre for Data Ethics and Innovation (CDEI), Unlocking the value of data: Exploring the role of data intermediaries (2021), https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/1004925/Data_intermediaries_-_accessible_version.pdf (last visited June 17, 2022). [4] Please refer to the guidelines for the selection of sponsors of the 2022 Social Innovation Summit: https://www.gov.uk/government/publications/uk-national-data-strategy/national-data-strategy(last visited June 17, 2022). [5] Regulation of the European Parliament and of the Council on European data governance and amending Regulation (EU) 2018/1724 (Data Governance Act), 2020/0340 (COD) final (May 4, 2022). [6] Communication from the Commission to the European Parliament, the Council, the European Economic and Social Committee and The Committee of the Regions— A European strategy for data, COM/2020/66 final (Feb 19, 2020). [7] Proposal for a Regulation on European Data Governance, European Parliament Legislative Train Schedule, https://www.europarl.europa.eu/legislative-train/theme-a-europe-fit-for-the-digital-age/file-data-governance-act(last visited Aug 17, 2022). [8] 周晨蕙，〈日本資訊信託功能認定指引第二版〉，科技法律研究所，https://stli.iii.org.tw/article-detail.aspx?no=67&tp=5&d=8422（最後瀏覽日期︰2022/05/30）。 [9] CDEI, supra note 3. [10] Ada Lovelace Institute, Exploring legal mechanisms for data stewardship (2021), 30~31,https://www.adalovelaceinstitute.org/wp-content/uploads/2021/03/Legal-mechanisms-for-data-stewardship_report_Ada_AI-Council-2.pdf (last visited Aug 17, 2022). [11] George A. Akerlof, The Market for "Lemons": Quality Uncertainty and the Market Mechanism, THE QUARTERLY JOURNAL OF ECONOMICS, 84(3), 488-500 (1970). [12] IMDA, MOU Signing Between IMDA and CEIMIA is a Step Forward in Cross-border Collaboration on Privacy Enhancing Technology (PET) (2022),https://www.imda.gov.sg/-/media/Imda/Files/News-and-Events/Media-Room/Media-Releases/2022/06/MOU-bet-IMDA-and-CEIMIA---ATxSG-1-Jun-2022.pdf (last visited Nov. 28, 2022). [13] ICO publishes guidance on privacy enhancing technologies, ICO, https://ico.org.uk/about-the-ico/media-centre/news-and-blogs/2022/09/ico-publishes-guidance-on-privacy-enhancing-technologies/ (last visited Nov. 27, 2022). [14] U.K. and U.S. governments collaborate on prize challenges to accelerate development and adoption of privacy-enhancing technologies, GOV.UK, https://www.gov.uk/government/news/uk-and-us-governments-collaborate-on-prize-challenges-to-accelerate-development-and-adoption-of-privacy-enhancing-technologies (last visited Nov. 28, 2022); Winners Announced in First Phase of UK-US Privacy-Enhancing Technologies Prize Challenges, NIST, https://www.nist.gov/news-events/news/2022/11/winners-announced-first-phase-uk-us-privacy-enhancing-technologies-prize (last visited Nov. 28, 2022).

Experiences about opening data in private sector

Experiences about opening data in private sector Ⅰ. Introduction 　　Open data is the idea that data should be available freely for everyone to use and republish without restrictions from copyright, patents or other mechanisms of control. The concept of open data is not new; but a formalized definition is relatively new, and The Open Definition gives full details on the requirements for open data and content as follows: 　　Availability and access: the data must be available as a whole with no more than a reasonable reproduction cost, preferably by downloading over the internet. The data must also be available in a convenient and modifiable form. 　　Reuse and redistribution: the data must be provided under terms that permit reuse and redistribution including the intermixing with other datasets. The data shall be machine-readable. 　　Universal participation: everyone must be able to use, reuse and redistribute the data— which by means there should be no discrimination against fields of endeavor or against persons or groups. For example, “non-commercial” restrictions that would prevent “commercial” use, or restrictions of use for certain purposes are not allowed. 　　In order to be in tune with international developmental trends, Taiwan passed an executive resolution in favor of promoting Open Government Data in November 2012. Through the release of government data, open data has grown significantly in Taiwan and Taiwan has come out on top among 122 countries and areas in the 2015 and 2016 Global Open Data Index[1]. 　　The result represented a major leap for Taiwan, however, progress is still to be made as most of the data are from the Government, and data from other territories, especially from private sector can rarely be seen. It is a pity that data from private sector has not being properly utilized and true value of such data still need to be revealed. The following research will place emphasis to enhance the value of private data and the strategies of boosting private sector to open their own data. Ⅱ. Why open private data 　　With the trend of Open Government Data recent years, countries are now starting to realize that Open Government Data is improving transparency, creating opportunities for social and commercial innovation, and opening the door to better engagement with citizens. But open data is not limited to Open Government Data. In fact, the private sector not only interacts with government data, but also produces a massive amount of data, much of which in need of utilized. 　　According to the G20 open data policy agenda made in 2014, the potential economic value of open data for Australia is up to AUD 64 billion per annum, and the potential value of open data from private sector is around AUD 34 billion per annum. Figure 1 Value of open data for Australia (AUD billion per annum) Source: McKinsey Global Institute 　　The purpose for opening data held by private entities and corporations is rooted in a broad recognition that private data has the potential to foster much public good. Openness of data for companies can translate into more efficient internal governance frameworks, enhanced feedback from workers and employees, improved traceability of supply chains, accountability to end consumers, and with better service and product delivery. Open Private Data is thus a true win-win for all with benefiting not only the governance but environmental and social gains. 　　At the same time, a variety of constraints, notably privacy and security, but also proprietary interests and data protectionism on the part of some companies—hold back this potential. Ⅲ. The cases of Open Private Data 　　Syngenta AG, a global Swiss agribusiness that produces agrochemicals and seeds, has established a solid foundation for reporting on progress that relies on independent data collection and validation, assurance by 3rd party assurance providers, and endorsement from its implementing partners. Through the website, Syngenta AG has shared their datasets for agricultural with efficiency indicators for 3600 farms for selected agro-ecological zones and market segments in 42 countries in Europe, Africa, Latin America, North America and Asia. Such datasets are precious but Syngenta AG share them for free only with a Non-Commercial license which means users may copy and redistribute the material in any medium or format freely but may not use the material for commercial purposes. Figure 2 Description and License for Open data of Syngenta AG Source: http://www.syngenta.com 　　Tokyo Metro is a rapid transit system in Tokyo, Japan has released information such as train location and delay times for all lines as open data. The company held an Open Data Utilization Competition from 12 September to 17 November, 2014 to promote development of an app using this data and continues to provide the data even after the competition ended. However, many restrictions such as non-commercial use, or app can only be used for Tokyo Metro lines has weakened the efficiency of open data, it is still valued as an initial step of open private data. Figure 3 DM of Tokyo Metro Open data Contest Source: https://developer.tokyometroapp.jp/ Ⅳ. How to enhance Open Private Data 　　Open Private Data is totally different from Open Government Data since “motivation” is vital for private institutions to release their own data. Unlike the government data can be disclosed and free to use via administrative order or legislation, all of the data controlled by private institutions can only be opened under their own will. The initiative for open data therefore shall focus on how to motivate private sectors releasing their own data-by ensuring profit and minimizing risks. 　　Originally, open data shall be available freely for everyone to use without any restrictions, and data owners may profit indirectly as users utilizing their data creating apps, etc. but not profit from open data itself. The income is unsteady and data owners therefore lose their interest to open data. As a countermeasure, it is suggested to make data chargeable though this may contradict to the definition of open data. When data owners can charge by usage or by time, the motivation of open data would arise when open data is directly profitable. 　　Data owners may also worry about many legal issues when releasing their own data. They may not care about whether profitable or not but afraid of being involved into litigation disputes such as intellectual property infringement, unfair competition, etc. It is very important for data owners to have a well protected authorization agreement when releasing data, but not all of them is able to afford the cost of making agreement for each data sharing. Therefore, a standard sample of contract that can be widely adopted plays a very important role for open private data. 　　A data sharing platform would be a solution to help data owners sharing their own data. It can not only provide a convenient way to collect profit from data sharing but help data owners avoiding legal risks with the platform’s standard agreement. All the data owners have to do is just to transfer their own data to the platform without concern since the platform would handle other affairs. Ⅴ. Conclusion 　　Actively engaging the private sector in the open data value-chain is considered an innovation imperative as it is highly related to the development of information economy. Although many works still need to be done such as identifying mechanisms for catalyzing private sector engagement, these works can be done by organizations such as the World Bank and the Centre for Open Data Enterprise. Private-public collaboration is also important when it comes to strengthening the global data infrastructure, and the benefits of open data are diverse and range from improved efficiency of public administrations to economic growth in the private sector. However, open private data is not the goal but merely a start for open data revolution. It is to add variation for other organizations and individuals to analyze to create innovations while individuals, private sectors, or government will benefit from that innovation and being encouraged to release much more data to strengthen this data circulation. [1] Global Open Data Index, https://index.okfn.org/place/（Last visited: May 15, 2017）

Observing Recent Foreign Developments upon Bio-medicine、 Marketing Medical Devices、Technology Development Project and the Newest Litigation Trend Concerning the Joint Infringement of Method/Process Patents

1、Chinese REACH has put into shape, how about Taiwan REACH? - A Perspective of Chinese Measures on Environmental Management of New Chemical Substances Taiwan food industry has been struck by the government agency's disclosure that certain unfaithful manufacturers have mixed toxic chemicals into the food additives for the past 30 years, and the chemicals may seriously threaten public health. This event has not only shocked the confidence of the customers to the industry, but also drew public attention on the well-management and the safe use of chemicals. In order to manage the fast advancing and widely applicable chemical substance appropriately, the laws and regulations among the international jurisprudences in recent years tend to regulate unfamiliar chemicals as “new chemical substances” and leverage registration systems to follow their use and import. REACH is one the most successful models which has been implemented by European Union since 2006. China, one of our most important business partners, has also learned from the EU experience and implemented its amended " Measures on Environmental Management of New Chemical Substances" (also known as "Chinese REACH") last year. It is not only a necessity for our industry which has invested or is running a business in China to realize how this new regulation may influence their business as differently , but also for our authority concerned to observe how can our domestic law and regulation may connect to this international trend. Therefore, except for briefing the content of Chinese REACH, this article may also review those existing law and regulations in Taiwan and observe the law making movement taken by our authority. We expect that the comparison and observation in this article may be a reference for our authorities concerned to map out a better environment for new chemical management. 2、The study on Taiwanese businessmen Join the Bid Invitation and Bidding of Science and Technology Project China government invests great funds in their Science and Technology Project management system, containing most of innovated technology. It also creates the great business opportunity for domestic industry. China government builds up a Bid Invitation and Bidding Procedure in the original Science and Technology Project Regime recent years, in order to make the regime become more open and full of transparency. It also improves Regime to become more fairness and efficiency. Taiwan industry may try to apply for those Science and Technology Project, due to this attractive opportunity, but they should understand china's legal system before they really do that. This Article will introduce the "Bid Invitation and Bidding Law of the Peoples Republic of China", and the "Provisional Regulation on Bid Invitation and Bidding of Science and Technology Project", then clarify applied relationship between the "Bid Invitation and Bidding Law of the Peoples Republic of China", and "Government Procurement Law of the Peoples Republic of China". It also analyzes "Bid Invitation and Bidding Procedure", "Administration of Contract Performance Procedure", "Inspection and Acceptance Procedure", and "Protest and Complaint Procedure, providing complete legal observation and opinion for Taiwan industry finally. Keyword Bid Invitation and Bidding Law of the Peoples Republic of China; Government Procurement Law of the Peoples Republic of China; Provisional Regulation on Bid Invitation and Bidding of Science and Technology Project; Applying for Science and Technology Project Regime; Bid Invitation and Bidding Procedure; Administration of Contract Performance Procedure; Inspection and Acceptance Procedure; Protest and Complaint Procedure. 3、Comparing the Decisions of the United States Supreme Court regarding Preempting Marketing Medical Devices and Drugs from State Tort Litigations with the Decision of a Hypothetical Case in Taiwan The investment costs of complying with pertinent laws and regulations for manufacturing, marketing, and profiting from drugs and medical devices (abbreviated as MD) are far higher than the costs necessary for securing a market permit. The usage of MD products contains the risk of harming their users or the patients, who might sue the manufacturer for damages in the court based on tort law. To help reduce the risk of such litigation, the industry should be aware of the laws governing the state tort litigations and the preemption doctrine of the federal laws of the United States. This article collected four critical decisions by the United States Supreme Court to analyze the requirements of federal preemption from the state tort litigations in these cases. The article also analyzed the issues of preemption in our law system in a hypothetical case. These issues include the competing regulatory requirements of the laws and regulations on the drugs and MDs and the Drug Injury Relief Act versus the Civil Code and the Consumer Protection Law. The article concluded: 1. The pre-market-approval of MD in the United States is exempted from the state tort litigations; 2. Brand-name-drug manufacturers must proactively update the drug label regarding severe risks evidenced by the latest findings; 3. Generic-drug manufacturers are exempted from the product liability litigations and not required to comply with the aforementioned brand-name-drug manufacturers' obligation; 4. No preemption issues are involved in these kinds of product liability litigations in our country; 5. The judge of general court is not bound by the approval of marketing of drug and MD; 6. The judge of general court is not bound by the determination and verdict of the Drug Injury Relief Act. 4、Through Computer-Aided Detection Software, Comparing by Discussing and Analyzing the Regulatory Requirements for Marketing Medical Devices in the United States and in Taiwan Computer-Aided Detection (CADe) software systematically assists medical doctors to detect suspicious diseased site(s) inside patients' bodies, and it would help patients receive proper medical treatments as soon as possible. Only few of this type of medical device (MD) have been legally marketed either in the United States of America (USA) or in Taiwan. This is a novel MD, and the rules regulating it are still under development. Thus, it is valuable to investigate and discuss its regulations. To clarify the requirements of legally marketing the MD, this article not only collects and summarizes the latest draft guidance announced by the USA, but also compares and analyzes the similarities and differences between USA and Taiwan, and further explains the logics that USA applies to clarify and qualify CADe for marketing, so that the Department of Health (DOH) in Taiwan could use them as references. Meanwhile, the article collects the related requirements by the Administrative Procedure Act and by the Freedom of Government Information Law of our nation, and makes the following suggestions on MD regulations to the DOH: creating product code in the system of categorization, providing clearer definition of classification, and actively announcing the (abbreviated) marketing route that secures legal permission for each individual product. 5、A Discussion on the Recent Cases Concerning the Joint Infringement of Method/Process Patents in the U.S. and Japan In the era of internet and mobile communication, practices of a method patent concerning innovative service might often involve several entities, and sometimes the method patent can only be infringed jointly. Joint infringement of method/process patents is an issue needed to be addressed by patent law, since it is assumed that a method patent can only be directly infringed by one entity to perform all the steps disclosed in the patent. In the U.S., CAFC has established the "control or direction" standard to address the issue, but the standard has been criticized and it is under revision now. In Japan, there is no clearly-established standard to address the issue of joint infringement, but it seems that the entity that controls and benefits from the joint infringement might be held liable. Based on its discussion about the recent development in the U.S. and Japan, this article attempts to provide some suggestions for inventors of innovative service models to use patents to protect their inventions properly: they should try to avoid describing their inventions in the way of being practiced by multi-entities, they should try to claim both method and system/apparatus inventions, and they should try to predict the potential infringement of their patents in order to address the problem of how to prove the infringement.

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