Abstract
I. INTRODUCTION
Now, we are gradually entering the era of intelligence powered by big data, driven by cloud computing, and represented by artificial intelligence. The birth of big data is the result of the traditional “data” changing from quantitative to qualitative, creating a new era in which data values have been redefined and explored. 1 Among them, biological big data is a typical type of big data. Everyone's data output reaches 10TB/person. 2 The total amount of biological data generated every year in the world has already reached the level of EB (one of the computer storage units). 3 Moreover, with the rapid development of technologies for the acquisition, storage, distribution, and processing of large-scale biological data, data has become a basic resource for life science research, including disease treatment and prevention. Based on this, biological informatics and systems biology in understanding the basic laws of life, the transformation of life by synthetic biology, and the control and intervention of human diseases by precision medicine, have made rapid progress. 4 For example, systems biology research based on massive biological data is considered to be the only way to obtain a comprehensive understanding of complex life systems, which will play an important role in biomedicine, especially in understanding the risk factors of diseases. It is precisely because of this that “How Will Big Pictures Emerge from a Sea of Biological Data” was listed by Science magazine as one of the 125 most challenging scientific issues in 2005. 5
China has a huge biological big data resource advantage and the world's leading biological big data production capacity. 6 Biological big data and other big data are collectively identified by the state as a national underlying strategic resource. 7 However, the links in the life cycle of China's biological big data have not yet formed an organic system. In addition to strategic deployment, policy guidance, and technical support, it is vitally important to have legal protection. Otherwise, it will inevitably lead to the occurrence and aggravation of problems such as random, scattered, and disordered circulation; black transactions; random abuse; and loss of biological big data storage. In other words, it is necessary, important, and urgent to promote the regulation process of biological big data.
II. THE CONNOTATION, EXTENSION AND PHYSICAL CHARACTERISTICS OF BIOLOGICAL BIG DATA
A. Connotation and extension of biological big data
“Big data” extends traditional biological data to biological big data 8 and gives it new connotations and extensions. This will affect the construction of the legal system for biological big data. The connotation of biological big data is digital life information. In the context of big data, “data” is not only the numbers and values in the traditional sense, it is the general term for all media that can be input, stored, and processed by computer programs. 9 We can treat “data” as a binary structure consisting of data forms and data content, which can be digitized text, letters, numbers, graphics, images, video, audio, and combinations of them. This determines whether “data” can be processed by computers. The content of the data is “information,” which determines the value of the data. 10 Therefore, the connotation of biological big data is digital life information, which is an objective description of life (a system) from different angles and levels. The extension of biological big data is big data related to life. From the perspective of life science research, genomics big data obtained through new technologies, such as sequencing technology, is the most typical type of data.
In addition, from the perspective of medical health, various types of medical big data represented by physiological and pathological big data obtained through various devices which collect and record health or physiological data are most common. From the perspective of medical equipment, various types of “feedback” big data, represented by utility big data obtained through different channels, are the most common.
B. Physical characteristics of biological big data
The objective state of existence of biological big data reflects three main physical characteristics,
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which will directly affect the creation of specific systems for biological big data. Specifically:
Invisible (inorganic). As a digital life information, biological big data is invisible and does not occupy physical space, but is tangible, which is similar to the object of intellectual property—”information” or a “knowledge product.” It can be copied. Biological big data can be copied indefinitely, again making it similar to intellectual property and different from the property objects. Biological big data can be used by multiple subjects. Nonconsumption (permanence). The use of biological big data does not cause physical loss, but rather increases its value: the more users, the more value—another point of similarity to intellectual property and difference from physical property objects.
III. LEGALIZATION OF BIOLOGICAL BIG DATA IN CHINA
China's rule of law in the data field has started from certain cultural presumptions about personal privacy and data security protection, 12 the open sharing of government data, 13 and property rights of data. 14 Experience with big data is gradually being accumulated and consolidated at the institutional level, leading to a process of continuous improvement. From the connotation and physical characteristics of biological big data, it can be determined that the end result of the regulation of biological big data must form an organic legal system involving various kinds of biological big data, as well as codifying the rights, obligations, and responsibilities of various subjects and actors.
From the data point of view, two of the most important and indispensable goals are the protection and the circulation of data. In this regard, China has already had preliminary legislative practice, mainly in the form of distributed laws and regulations such as the General Principles of Civil Law, the Science and Technology Progress Law, and the Scientific Data Management Measures. The Regulations on the Management of Human Genetic Resources is also directly related to biological big data, but it is still in the legislative process. 15
A. The legalization of biological big data in China
The human body is an important source of biological big data. A large amount of personal information has become biological big data captured in the form of graphics, images, video, and audio through various forms of electronic technology. Such biological big data should be strictly protected by law to prevent excessive collection, loss, leakage, misappropriation, or abuse in order to avoid infringing on people's rights and to prevent damage to national interests and threats to national security. In this regard, on October 1, 2017, the Civil Code of the People's Republic of China Chapter 5, Civil Rights, Article 111, specifically states: “Personal information of natural persons shall be protected by law. Any organization or individual that needs to obtain other people's personal information shall obtain and ensure the information security according to law, and shall not illegally collect, use, process or transmit other people's personal information, nor illegally buy, sell, provide or disclose other people's personal information.” The personal information of a natural person in this article mainly refers to any biological and physical data, documents, archives, and other materials according to which a specific natural person's identity can be identified. It not only protects physical information such as ID card information, household registration information, family composition, occupational status, social interaction, and online transactions, but also includes genetic composition, biology, genetic code, and physiological information of natural persons. Any information relating to a particular natural person that can be thereby specified is personal information. 16
Article 5 of the Scientific Data Management Measures, implemented on March 17, 2018, stipulates: “Any unit or individual engaged in scientific data collection, production, use and management activities shall abide by relevant state laws, regulations and departmental rules, and shall not use scientific data to engage in activities that endanger national security, social public interests, the legitimate rights or the interests of others.” Article 25 states: “Scientific data concerning state secrets, national security, social public interests, trade secrets, and personal privacy may not be open to the public. The purpose of use, user qualification and confidentiality conditions shall be examined and the scope of knowledge shall be strictly controlled if it is really necessary to open to the outside world.” The Human Genetic Resources Management Regulations (Ministry of Science and Technology for review) also specifically responded to the data problems. The human genetic resources referred to in the Regulations also include biological big data. The content of Article 3, paragraph 3, of the Regulations reads: “The human genetic resources mentioned in these regulations refer to the organs, tissues, cells, nucleic acids, nucleic acid products and other resource materials containing human genome, genes and their products, as well as the data and other information materials produced.” Article 5 reads: “Without permission, no unit or individual may carry out such activities as collection, international cooperation, or exit of human genetic resources. The sale of human genetic resources by any unit or individual is prohibited.” These provisions stipulate that China strictly protects biological big data involving personal information.
B. The current situation of regulation of data circulation
Data circulation is realized by new technologies, such as data transmission and network platform technology. The transmission (i.e., circulation) of data is the core link in the life cycle of data, and it is followed in that life cycle by the storage, then application, of data. Increasing circulation of data is the general trend, which maximizes the release of the intrinsic value of data. How to promote the circulation of data while protecting data security is an important issue for the law. This is especially true for bio-big data. Only when biological big data achieves smooth circulation can we truly utilize the discovery of life knowledge to promote the deep development of human health and improvement of human life.
The generalized term used, “data circulation,” covers the collection, provision, sharing, opening, and trading of data. In this regard, Article 65 of the safeguard measures of Chapter VI of the Science and Technology Progress Law, which came into effect on July 1, 2008, stipulates:
The administrative department of science and technology of the State Council shall in conjunction with the relevant competent department of the State Council, … make public the distribution and use of scientific and technological resources in a timely manner. The management unit of scientific and technological resources shall publicize the shared use system and use of the scientific and technological resources managed by the society and arrange the use according to the use system. …
The Scientific Data Management Measures provides detailed regulations on the circulation of biological big data, focusing in Chapter III on collection, remittance, and preservation (Articles 11 to 18) and in Chapter IV (Articles 19 to 24) on the exchange of data, including the conditions, requirements, and procedures for sharing. The Regulations on the Management of Human Genetic Resources (Draft for Science and Technology of the Ministry of Science and Technology) also has a special chapter on “Capture and Collection of Human Genetic Resources” (Chapter 2, Articles 9 to 13) which includes specific conditions, requirements, and procedures for the collection of human genetic resources. These specific provisions have guaranteed, regulated, guided, and encouraged the circulation of biological big data with scientific data characteristics. However, data transactions as a new data circulation model have not yet had a clear legislative response. Although the content of Article 5, paragraph 2, of the Regulations on the Management of Human Genetic Resources (Draft for Science and Technology) calls for “[p]rohibition of any unit or individual from trading human genetic resources,” that doesn't mean that all biological big data can't be traded. On the practical level, the first big data exchange in China, Guiyang Big Data Exchange, including medical big data and health big data in its tradable big data varieties. 17 At the legislative level, Article 127 of Civil Rights in Chapter 5 of the General Principles of Civil Law also leaves room for trading data. The trading of biological big data is a new global subject worthy of further study.
IV. SUGGESTIONS FOR FURTHER PROMOTING THE LEGALIZATION OF BIG DATA IN BIOLOGY IN CHINA
In summary, although the rule of law in China's biological big data has already started, China's current regulation in this field does not leave much room for optimism, and a legal ecological environment with a mature regulatory system and complete coverage has not yet formed. To some extent, this will restrict the development of China's biological big data. In practice, the regulation of biological big data is a huge project and it cannot be done in one day. Therefore, this article tries to put forward a statement from three main aspects of the regulation of big data in biology in China, including main purposes, key principles, and core systems in order to contribute to the further promotion of the regulation of big data in biology in China.
A. To clarify the main purposes of the legalization of big data in China
The main purpose of the legalization of big data of China is to clarify the qualifications, rights, obligations, and responsibilities of the various parties involved in all aspects of the data life cycle at the institutional level and related matters. Regulating and guiding data behavior in the field of biological big data will promote the development of national biological big data and benefit people's health. The whole life cycle of data must be addressed for effective regulation. In the past, the concept of life cycle was used primarily in the management field. Now, however, it has developed into a general concept which often appears in such diverse fields such as politics, economics, environment, technology, society, etc. It can also, as here, be applied to the field of big data. It is generally understood that the term “life cycle” covers a process from cradle to grave.
Based on the characteristics of big data, Chinese scholars divide the life cycle of big data into five stages: production, organization, analysis, application, and destruction. 18 However, the authors believe that the life cycle of big data in real situations may be more helpfully divided into four phases: production phase, circulation phase, application phase, and destruction phase—though because certain biological big data, such as genomics, is permanently preserved for future or ongoing application, the destruction phase is not a necessary or inevitable part of all big data utilization. Data production (or generation) mainly includes data sequencing, acquisition, recording, and other behaviors which capture data through technological means. Data circulation mainly includes data exchange, collection, 19 provision, sharing, openness, and other transactions, such as through online platform technology and other Internet-based or -facilitated technologies. Data application mainly includes data analysis and visualization. Data destruction is relatively simple and straightforward, comprising primarily data deletion.
The Chinese laws and regulations relating to or affecting biological big data are not specifically targeted at biological big data. In other words, the current situation of regulation of biological big data in China still has significant problems, such as lack of legislation, low level of legislation, and lack of specific content. China lacks a general law with clear legislative purposes, basic principles, and specific systems in the field of biological big data to guide and lead the content and revision of relevant laws, administrative regulations, local regulations, departmental regulations, and local government regulations. This will lead to the emergence of contradictory phenomena in the field of biological big data. In terms of the low level of legislation, there is at present no law in China really addressed to biological big data. This low level of legislation is not commensurate with the importance of biological big data. In terms of lack of content, currently, there is no comprehensive and systematic structure to address the whole life cycle of data in China's legislative practice—only laws of more generalized applicability. However, the life cycle of biological big data poses different specific problems, which require targeted legal responses.
In this regard, it is necessary for China to enact special legislation for biological big data, such as a biodata management law. It is important that the key issues in the field of biological big data are regulated over the whole life cycle of big data, which is driven by the content of biological big data. Legislation (including laws, administrative regulations, departmental regulations, etc.) must also take cognizance of China's national conditions and future development, and be crafted in light of biological data's characteristics. In addition to new laws, such as the aforementioned biodata management law, existing laws touching on biological big data must be amended or revised to better address this field. Thus, the legal system for China's biological big data must be constructed to guarantee the overall efficient operation of China's data work in the field of biological big data. Only when the work of formulating the requisite laws and regulations has been accomplished (or at least preliminarily accomplished, since revising the legal structure will be an ongoing effort as technology changes the acquisition, analysis, and application of data) can we truly solve the problem of lack of legislation, low level of legislation, and lapses or gaps in specific content.
The development of general laws in the field of biological big data is of great significance to provide guidance and an overall structure. Based on the current status of regulation of China's biological big data, we believe that developing the law for regulating biological big data can be divided into three stages.
The first stage will take the form of “departmental regulations,” such as Biodata Management Measures. Although its legal effect is low and its scope of action is limited, it can accumulate experience for higher-level legislation in the future.
The second stage would be “administrative regulations” issued by the State Council. These more comprehensive regulations are necessary because many problems involved in biological big data cannot be solved by any one department. After being upgraded from “departmental regulations” to “administrative regulations,” the regulations' scope of application will be more extensive, more authoritative, and their enforcement will be greatly enhanced. On the basis of the Biodata Management Measures, it can be revised to Biological Big Data Management Regulations.
The third stage would be in the form of “laws” formulated by the National People's Congress or its standing committee. Since biological big data is related to people's lives and health, it is not enough to regulate them only in the form of “administrative regulations”; rather, the regulatory structure needs to be upgraded to the “legal” level.
Here, it should be emphasized that while the legal system of China's biological big data is gradually being built, the “standards” system of China's biological big data should be constructed simultaneously. Because standards supplement the law, they can improve the operability of the law. Laws generally address broader concerns: it is impossible to specify every problem and every situation in detail in advance, especially in some professional fields, but more specific situations can be addressed through the promulgation of standards. In addition, the law, due to the process of enacting it, has a certain stability and it can be difficult to readily change it, but standards can be modified more readily in response to social or technological development. Therefore, standards can be a useful complement to legal norms. Standards can be formulated in a timely manner according to the developing needs of society while reflecting content that is not stipulated in the law. The broad principles and inherent stability of the law are actually in tension with the specificity and variability of developments in the data field, but the detail and ready revisability of standards can provide an effective means to implement the law.
B. To establish the key principles for the regulation of Chinese biological big data
The basic principles of law are indispensable for the formulation and operation of the specific system of law and are the basic truths and principles of law. As Gustav Radbruch said: “There are certain principles of law which are more effectual than other rules of law, so that whatever law contradicts them, it loses its validity, and these principles of law are called natural law or rational law.” 20 In addition, the basic principles of law reflect value judgment attributes and provide stability, can coordinate conflicts between rules, make up for any deficiencies of statutory law, provide guidance for judges and limit the abuse of judges' discretion, and guide the specific system of law. Broad legal principles provide the basic norm(s) that must be followed to guide the creation, implementation, and revision of the legal system for biological big data rule of law and are the building principles of the legal system. The legalization of biological big data must first establish clear key principles, and on this basis, design a sound system. In this regard, we believe that the three most critical principles are the principle of data security, the principle of data circulation, and the principle of balance of interests.
1. Legalization
The principle of data security refers to ensuring the security of data through legal mechanisms to avoid problems such as loss, leakage, theft, abuse, and destruction of individual data, as well as to avoid any resulting security risks. In the context of big data, security issues are unavoidable. For biological big data, because it mainly comes from the human body, it is closely related to a country's biological resources, the life and health of the population, medical treatment, environment, agriculture, and many other critical aspects of national life, making the security issue particularly important. It can be seen that security should be the driving force for the law as it pertains to biological big data. From the perspective of promoting the legalization of China's biological big data and the “legal ecological” environment of biological big data, it is appropriate to adopt the concept of data security in a broad sense, which should contain two meanings. The first layer of meaning is the security of the data itself, including national data security, personal data security, enterprise data security, and the data security of other entities such as social groups. From a cycle perspective, data security includes security during the data generation phase, security during the data circulation phase, security during the data application phase, and security during the data destruction phase. The second meaning is the security risk of data application, that is, biological big data should not be used to engage in activities that endanger national security, personal security, corporate security, and the security of other entities, such as social groups, or to cause potential harm to these entities.
2. Data circulation principles
The principle of data circulation refers to the diversification of data circulation through various mechanisms so as to maximize the release of the value of data. 21 This is mainly due to two considerations. The first is that the professional division of work in the field of big data necessarily makes data circulate between data collection, storage, and the analysis and mining. The data itself is only an objective description and expression, and cannot be directly generated or transformed into new knowledge. Only effective data processing, analysis, and mining can develop the value of the data. 22 Nowadays, the cost of obtaining data is getting lower and lower, and there is more and more space to store it. This turn makes requires increasing effort and more powerful tools to analyze and mine data. This will gradually promote the division of professional labor, with some specializing in data collection and storage, others in data analysis and mining.
For example, with the increasing popularity of big data technology in the medical field, hospitals have accumulated a large amount of medical big data, such as physiological and pathological data, in their daily medical practice. 23 They possess a vast wealth of data which contains a huge amount of information with intrinsic value. However, doctors usually do not have enough professional ability in analysis and mining to directly make use of this data. If they want to draw out deeper information, the data needs to be analyzed and mined by institutions or personnel specialized in medical big data analysis and mining. This necessarily requires the circulation of data, from hospitals to technical institutions specializing in medical big data analysis and mining, so as to obtain useful results. This circulation must be done, however, under the premise of ensuring data security. With each order-of magnitude-increase in the amount of biological big data collected and stored, more and more information can be analyzed and mined, and the value of such information has overflow characteristics. It can be used not only by the subject of data collection and storage, but also by other subjects. Taking the medical field as an example, hospital medical big data can be widely applied to different contexts through different analysis software and mining algorithms. That is to say, the same medical big data may have applicability to basic research, drug development, clinical diagnosis and treatment, health management, and even extend to seemingly unrelated fields outside the field of medical health, such as furniture design, urban planning and so on. This also requires the circulation of data, which is circulated by the hospital to other entities who need such data, in order to avoid the formation of data islands and data barriers while maximizing the release of data value and promoting comprehensive development—all while maintaining data security.
The second aspect of data circulation includes several main modes of data collection, interchange, provision, sharing, openness, publicity, and transaction. The legal system must lay a solid foundation for data circulation and open up a smooth path.
3. The principle of balance of interests
The principle of balance of interests refers to balancing the interests of the various entities involved in the data life cycle through legal mechanisms, respecting their legal rights, and protecting their legitimate rights and interests so as to avoid conflicts. From the perspective of the sociology of law, interest conflict is “the interest dispute and the interest competition which the interest subject produces based on the interest difference and the interest contradiction.” 24 In the whole data life cycle, especially in the data circulation phase, biological big data will involve a variety of different subjects. At the same time, according to the content of the data itself, it will involve the public interests of the state and society, and the private interests of enterprises and individuals. This will inevitably lead to interest imbalance or even conflicts of interest. Therefore, the balance of the law is particularly important. Of course, the interests are divided into different priorities and order. When there is a conflict of interest, the public interest should be protected against private interests. The interests protected by law can be divided into different levels and ranked. Compared with private interests, public interests with the characteristics of shareability and universality of beneficiaries should be properly protected. 25 For biological big data required for government decision-making, public safety, environmental protection, or medical or public welfare research, the norm should be free and open sharing, with paid or restricted access as the exception.
C. To create a core system in the legalization of China's biological big data
The ultimate goal of the regulation of China's biological big data is to build a scientific and operational legal system. In this regard, based on the above three key principles, in the process of the legalization of biological big data in China, the core systems we should create mainly include a security system, a data circulation system, and a supervision and evaluation system.
1. Biological big data security system
In the “Promoting the Big Data Development Action Plan,” 26 it is clearly required to improve the regulatory system and standards system, scientifically regulate the use of big data, and effectively protect data security. Admittedly, non-circulation is the greatest guarantee of data security, but this will result in a huge waste of data resources, while unrestricted circulation will bring unpredictable security risks. Therefore, to ensure data security as a prerequisite for data circulation, it is necessary to achieve a balance between the two through a specific legal system. In this regard, we believe that the biological data security system must incorporate both physical and procedural aspects. It must cover all stages of the whole life cycle of biological big data, and clarify the qualifications, rights, obligations and responsibilities of each subject involved. Specifically, the biological big data security system in the data generation phase generally should include the content of the data and proper subjects for collection, procedures for data acquisition, and agent qualification, rights, obligations, and responsibilities; it needs to address different data activities related to safety procedures, such as recording data, approval procedures, collecting data, storing data relating to emergency response procedures, and so on. The data security system in the circulation stage of data should include procedures for controlling the circulation of data, for verifying who may access which data, and relating to the qualifications, rights, obligations, and responsibilities of any third-party platforms involved in the sharing or circulation of data. The security system in the application stage should include the qualifications, rights, obligations and responsibilities of those analyzing or mining data, as well as security certification procedures for data products. The security system in the data destruction stage needs to address the qualifications, rights, obligations, and responsibilities of the persons or entities responsible for data destruction, ensuring the correct data is destroyed or delated, and verifying its destruction.
2. Data circulation system for biological big data
Under the premise of strengthening the security of biological big data according, it is crucial to guide and guarantee the circulation of biological big data at the legal level. The coverage area of the data circulation system of biological big data is also mainly concentrated in the circulation stage of data. In biological big data, especially the circulation of biological big data with the characteristics of scientific data, the most typical is the big data of various groups of -omics. 27 Specifically, it is data in the field of life science research, generated through basic research, applied research, experimental development, and other means, as well as the data obtained through observation, monitoring, investigation, inspection, and testing, which is used in life science research activities. We believe that the circulation mode of biological big data with the characteristics of scientific data mainly includes interchange, collection, provision, sharing, and openness. In this regard, the main content of the data circulation system for biological big data with the characteristics of scientific data should still be created from the two aspects of entities and procedures, and the qualifications, rights, obligations, and responsibilities related to the interchange, collection, provision, sharing, and openness of each subject involved should be clarified.
For biological big data without the characteristics of scientific data that can be circulated at the same time, we believe that in addition to the above circulation modes, transaction can also be one of its circulation modes. However, in contrast, this kind of circulation mode needs to be embodied and consolidated at the legal level, so it is necessary to overcome many institutional problems. 28 In this regard, we believe that the concept of derived data can be introduced. Derived data is relative to native data. The latter refers to data generated through legal collection, recording, and storage, which can be understood as the most objective description of the real world, while the former refers to data generated after the processing of native data such as by cleaning, desensitization, anonymizing, processing, calculation, and aggregation, such as by using algorithms for specific purposes. Derived data has the characteristics of creativity, intangibility, reproducibility and non-consumability, and possesses property attributes which are consistent with the characteristics of intellectual property objects. However, as derived data cannot be classified into the existing intellectual property object category, it is necessary to legally construct new intellectual property rights including specific rights such as mark, storage, and use rights. And on this basis, we can truly realize the trading and circulation of such biological big data. 29
3. Monitoring and evaluation system for biological big data
Conducting supervision and evaluation can guarantee the quality of work and data. Therefore, the monitoring and evaluation of biological big data needs to be fixed throughout the system. In this regard, a more mature supervision system and evaluation mechanism, namely a comprehensive supervision system with multiple evaluation mechanisms, should be introduced.
Comprehensive supervision system means that, on the basis of self-regulation of data subjects and supervision of relevant government departments on relevant data behaviors, The supervision and evaluation system of biological big data is a system that the whole society can participate in and supervise, so as to realize the whole society co-governance of the whole life cycle of biological big data. Moreover, these supervision subjects can also supervise each other as part of the supervision of biological big data. At the same time, the supervision and evaluation system of biological big data should clearly define the division of labor and coordination of the subjects involved in supervision, which must be structured and organized. In other words, in addition to clarifying the rights and obligations of the relevant government authorities in conducting the supervision of data behavior related to biological big data, it is also necessary to further clarify the rights and obligations of ordinary citizens, social groups, news media, universities, and scientific research institutions in the supervision of data behaviors related to biological big data. The purpose of supervision is to ensure the quality of relevant work.
Multiple evaluation mechanisms means that the supervision and evaluation system of biological big data can reasonably introduce first-party (self-) evaluation, second-party evaluation, and third-party evaluation of products and services into the field of biological big data. For example, the subject generating or collecting data can make a first-party (self-) evaluation on the data; the subject utilizing the data can make a second-party evaluation; and professional data evaluation institutions can make a third-party evaluation while publishing the results of their evaluation so as to disseminate them to interested segments of society. Another example is the news media. As the main information disseminator, the supervision function and role in the field of public sharing of government data should be affirmed by the supervision system of open sharing of government data. At the same time, the news media, universities, scientific research institutions, and other subjects should be encouraged to carry out long-term monitoring, reporting, investigation and evaluation activities on biological big data.