Data ownership: How to define and enforce data ownership rights and obligations

1. Understanding Data Ownership

Data ownership is a complex and multifaceted concept that encompasses the rights and responsibilities associated with the control and use of data. It is crucial to understand the various perspectives surrounding data ownership to navigate the evolving landscape of data governance.

1. Legal Perspective:

From a legal standpoint, data ownership refers to the legal rights and control that individuals or entities have over the data they generate or collect. These rights are typically established through intellectual property laws, contracts, or privacy regulations. For example, a company may own the data it collects from its customers based on the terms outlined in its privacy policy.

2. Ethical Considerations:

Ethics play a significant role in data ownership discussions. Questions arise regarding the ethical use of data, consent, and the potential impact on individuals and society. Organizations must consider the ethical implications of data ownership and ensure responsible data practices to protect privacy and prevent misuse.

3. Organizational Ownership:

Within organizations, data ownership often involves determining who has the authority to access, manage, and make decisions based on the data. This can vary depending on the data's source, purpose, and the roles and responsibilities of individuals within the organization. For instance, a data scientist may have ownership rights over the data they analyze and derive insights from.

4. User Ownership:

In some cases, individuals may argue for ownership rights over their personal data. This perspective emphasizes individuals' control and consent regarding the collection, use, and sharing of their data. It aligns with the principles of data privacy and empowers individuals to exercise their rights over their personal information.

5. data Ownership challenges:

Data ownership is not without its challenges. Issues such as data aggregation, data sharing, and data portability can complicate the determination of ownership. Additionally, the emergence of emerging technologies like artificial intelligence and machine learning raises questions about ownership when data is used to train models.

6. Examples:

To illustrate the complexities of data ownership, consider a social media platform that collects user data. The platform may claim ownership over the data generated by its users, allowing them to analyze it for targeted advertising. However, users may argue that they retain ownership rights over their personal posts and information.

In summary, understanding data ownership requires considering legal, ethical, organizational, and user perspectives. It involves navigating challenges and balancing the rights and responsibilities associated with data control. By comprehending these aspects, individuals and organizations can establish robust data governance frameworks that respect privacy, promote responsible data practices, and foster trust in the digital ecosystem.

2. Defining Data Ownership Rights

One of the most challenging aspects of data ownership is defining and enforcing the rights and obligations of the parties involved in the creation, collection, processing, and sharing of data. Data ownership rights refer to the legal entitlements and responsibilities that govern the access, use, and control of data. Data ownership obligations refer to the duties and liabilities that arise from the possession, transfer, and disclosure of data. In this section, we will explore the legal framework that shapes the data ownership landscape, and examine the different perspectives and approaches that various stakeholders have adopted. We will also discuss some of the key issues and challenges that data owners and users face in the current data ecosystem.

Some of the topics that we will cover in this section are:

- The sources and types of data ownership rights and obligations. We will look at how different legal regimes, such as intellectual property law, contract law, privacy law, and data protection law, confer or limit data ownership rights and obligations. We will also distinguish between different types of data, such as personal data, non-personal data, anonymized data, and aggregated data, and how they affect the scope and nature of data ownership rights and obligations.

- The perspectives and interests of different data stakeholders. We will analyze how different data stakeholders, such as data subjects, data controllers, data processors, data brokers, data custodians, and data beneficiaries, view and assert their data ownership rights and obligations. We will also consider how these stakeholders balance their own interests with the interests of other parties and the public good.

- The challenges and opportunities of data ownership in the digital age. We will address some of the emerging and unresolved issues and dilemmas that data ownership poses in the context of the digital economy and society. For example, how to deal with the complexity and uncertainty of data ownership in a data-driven world, how to ensure the accountability and transparency of data ownership practices, how to foster the innovation and competition of data markets, and how to protect the rights and interests of data subjects and data users.

3. Rights and Obligations

data ownership in business refers to the rights and obligations of both data providers and data consumers regarding the collection, use, storage, and disposal of data. Data ownership is a complex and evolving issue that involves legal, ethical, and technical aspects. Data ownership can affect the value, quality, and security of data, as well as the privacy and trust of the data subjects. Therefore, it is important for businesses to define and enforce clear and consistent data ownership policies and practices that align with their goals and values, as well as the expectations and rights of their stakeholders. In this section, we will explore some of the key aspects of data ownership in business from different perspectives, such as:

1. Data providers: Data providers are the entities that generate, collect, or provide data to others. Data providers can be individuals, organizations, or third parties. Data providers have certain rights and obligations regarding their data, such as:

- The right to decide who can access, use, and share their data, and for what purposes.

- The right to be informed and consent to the data collection and processing practices of the data consumers.

- The right to access, correct, and delete their data, or withdraw their consent at any time.

- The obligation to ensure the accuracy, quality, and relevance of their data.

- The obligation to respect the privacy and confidentiality of the data subjects and the data consumers.

- The obligation to comply with the applicable laws and regulations regarding data protection and ownership.

- For example, a customer who provides personal and transactional data to an online retailer has the right to know how the retailer uses and protects their data, and the obligation to provide accurate and truthful information.

2. Data consumers: Data consumers are the entities that access, use, or share data from others. Data consumers can be individuals, organizations, or third parties. Data consumers have certain rights and obligations regarding the data they consume, such as:

- The right to access, use, and share data that is relevant, accurate, and timely for their purposes.

- The right to benefit from the value and insights derived from the data.

- The right to be protected from unauthorized or malicious use of the data.

- The obligation to respect the rights and preferences of the data providers and the data subjects.

- The obligation to ensure the security, integrity, and quality of the data.

- The obligation to comply with the applicable laws and regulations regarding data protection and ownership.

- For example, a marketing analyst who uses customer data from an online retailer has the right to use the data for analytical and promotional purposes, and the obligation to protect the data from unauthorized access or disclosure.

3. Data subjects: Data subjects are the individuals whose personal or sensitive data is collected, used, or shared by others. data subjects can be customers, employees, partners, or other stakeholders. data subjects have certain rights and obligations regarding their data, such as:

- The right to be informed and consent to the data collection and processing practices of the data providers and the data consumers.

- The right to access, correct, and delete their data, or withdraw their consent at any time.

- The right to be protected from harm, discrimination, or exploitation resulting from the use of their data.

- The obligation to provide accurate and truthful information to the data providers and the data consumers.

- The obligation to respect the rights and interests of other data subjects and data stakeholders.

- The obligation to comply with the applicable laws and regulations regarding data protection and ownership.

- For example, an employee who provides personal and professional data to their employer has the right to know how the employer uses and protects their data, and the obligation to provide relevant and updated information.

4. Privacy and Consent

One of the most challenging aspects of data ownership is how to handle personal data, which is any information that can identify or relate to a specific individual. Personal data can include names, addresses, phone numbers, email addresses, biometric data, health records, financial transactions, online behavior, and more. Personal data is valuable for many purposes, such as marketing, research, security, and innovation. However, personal data also raises serious concerns about privacy and consent. Who owns the personal data of an individual? How can the individual control how their data is collected, used, shared, and deleted? What are the rights and obligations of the data collectors, processors, and users? How can the individual protect their data from unauthorized access, misuse, or breach? These are some of the questions that this section will explore from different perspectives.

Some of the possible perspectives on data ownership in personal context are:

1. The individual perspective: This perspective views personal data as an extension of the individual's identity, autonomy, and dignity. The individual has the right to own, access, and manage their own data, and to decide who can use it and for what purposes. The individual also has the right to be informed, to give or withdraw consent, to request correction or deletion, and to seek redress in case of violation. The individual should be able to exercise these rights easily and effectively, without being coerced, manipulated, or exploited by the data collectors or users. The individual should also be aware of the risks and benefits of sharing their data, and take responsibility for their choices and actions.

2. The social perspective: This perspective views personal data as a social good, which can benefit the society as a whole. The society has an interest in collecting, processing, and using personal data for various public purposes, such as improving public health, education, security, and welfare. The society also has a duty to protect the privacy and rights of the individuals, and to ensure that the data is used in a fair, transparent, and accountable manner. The society should balance the individual and collective interests, and establish clear and consistent rules and norms for data governance. The society should also foster a culture of trust and cooperation among the data stakeholders, and promote the values of democracy, human rights, and social justice.

3. The economic perspective: This perspective views personal data as a valuable asset, which can generate economic value and competitive advantage. The data collectors, processors, and users have an incentive to acquire, analyze, and monetize personal data, and to create new products, services, and markets based on data insights. The data stakeholders also have an obligation to respect the privacy and rights of the individuals, and to comply with the relevant laws and regulations. The data stakeholders should seek to maximize the efficiency and profitability of data use, while minimizing the costs and risks of data protection. The data stakeholders should also engage in fair and ethical data practices, and avoid data misuse, abuse, or monopoly.

5. Challenges and Solutions

data ownership in the digital age is a complex and contentious issue that involves multiple stakeholders, such as individuals, businesses, governments, and platforms. Data ownership refers to the rights and obligations of data subjects, data controllers, and data processors over the collection, use, storage, and sharing of personal and non-personal data. Data ownership is not only a legal concept, but also a social, economic, and ethical one, as it affects the privacy, security, autonomy, and dignity of data subjects, as well as the innovation, competition, and accountability of data controllers and processors. In this section, we will explore some of the main challenges and solutions for data ownership in the digital age, from different perspectives and domains.

Some of the challenges and solutions for data ownership in the digital age are:

1. Defining and harmonizing data ownership rights and obligations across jurisdictions and sectors. Different countries and regions have different laws and regulations regarding data ownership, such as the general Data Protection regulation (GDPR) in the European Union, the california Consumer Privacy act (CCPA) in the United States, and the personal Data protection Act (PDPA) in Singapore. These laws and regulations may have different definitions, scopes, and standards for data ownership, such as what constitutes personal and non-personal data, who are the data subjects, controllers, and processors, and what are their rights and obligations. Moreover, different sectors and industries may have different norms and practices for data ownership, such as the health, education, finance, and e-commerce sectors. These differences may create inconsistencies, conflicts, and uncertainties for data ownership, especially in cross-border and cross-sector data flows and transactions. Therefore, one of the possible solutions is to develop and adopt common frameworks and principles for data ownership, such as the OECD Privacy Guidelines, the APEC Privacy Framework, and the Global Privacy Assembly (GPA) resolutions, that can facilitate interoperability and cooperation among different jurisdictions and sectors, while respecting their diversity and sovereignty.

2. Empowering and protecting data subjects in the data economy. Data subjects are the individuals whose personal data are collected, used, stored, and shared by data controllers and processors, such as online platforms, apps, and services. Data subjects are often the source and the target of the data economy, as they generate and consume data, and benefit and suffer from data-driven products and services. However, data subjects may not have sufficient control, consent, and transparency over their data, as they may not be aware of, understand, or agree with the data practices of data controllers and processors, such as what data are collected, how they are used, where they are stored, and with whom they are shared. Moreover, data subjects may not have adequate access, portability, and erasure rights over their data, as they may not be able to access, correct, transfer, or delete their data from data controllers and processors, especially when they are locked in or dependent on certain platforms, apps, and services. Furthermore, data subjects may not have effective remedies and redress mechanisms for their data, as they may not be able to prevent, detect, or report data breaches, violations, or abuses, or seek compensation or justice for the harms and damages caused by data controllers and processors. Therefore, one of the possible solutions is to strengthen and enforce the data protection and privacy rights of data subjects, such as the right to be informed, the right to access, the right to rectification, the right to erasure, the right to restrict processing, the right to data portability, the right to object, and the right to not be subject to automated decision-making, as stipulated by the GDPR and other data protection laws and regulations, that can empower and protect data subjects in the data economy.

3. Balancing and aligning the interests and incentives of data controllers and processors in the data ecosystem. Data controllers and processors are the entities that collect, use, store, and share personal and non-personal data of data subjects, such as online platforms, apps, and services. Data controllers and processors are often the drivers and the beneficiaries of the data economy, as they create and offer data-driven products and services, and generate and capture value from data. However, data controllers and processors may not have sufficient accountability, responsibility, and transparency for their data, as they may not comply with, respect, or uphold the data ownership rights and obligations of data subjects, or the data governance rules and standards of data regulators and authorities. Moreover, data controllers and processors may not have adequate competition, innovation, and collaboration for their data, as they may not share, exchange, or integrate their data with other data controllers and processors, especially when they have dominant or monopolistic positions or practices in the data market or industry. Furthermore, data controllers and processors may not have optimal efficiency, quality, and security for their data, as they may not manage, process, or store their data in the most effective, accurate, or safe manner, especially when they have large or complex data sets or systems. Therefore, one of the possible solutions is to foster and promote the data stewardship and trustworthiness of data controllers and processors, such as the principles of lawfulness, fairness, and transparency, purpose limitation, data minimization, accuracy, storage limitation, integrity and confidentiality, and accountability, as advocated by the GDPR and other data governance frameworks and initiatives, that can balance and align the interests and incentives of data controllers and processors in the data ecosystem.

6. Considerations and Best Practices

One of the challenges of data ownership in the modern world is the increasing use of cloud computing, which involves storing and processing data on remote servers that are owned and operated by third-party providers. Cloud computing offers many benefits, such as scalability, flexibility, cost-efficiency, and security, but it also raises some issues regarding who owns the data, who can access it, and how it is protected. In this section, we will explore some of the considerations and best practices for data ownership in the cloud, from the perspectives of data owners, data users, and cloud providers. We will also provide some examples of how different organizations and industries deal with data ownership in the cloud.

Some of the considerations and best practices for data ownership in the cloud are:

1. Define data ownership rights and responsibilities clearly and explicitly. Data ownership in the cloud is not always straightforward, as there may be multiple parties involved in the creation, storage, and usage of data, such as data owners, data users, cloud providers, and third-party vendors. Therefore, it is important to establish clear and explicit agreements and contracts that define the rights and responsibilities of each party, such as who owns the data, who can access it, how it can be used, how it can be transferred, and how it can be deleted. These agreements and contracts should also specify the applicable laws and regulations, the dispute resolution mechanisms, and the penalties for breach of contract.

2. Choose a cloud provider that meets your data ownership needs and expectations. Not all cloud providers are the same, and they may have different policies and practices regarding data ownership, access, and protection. Therefore, data owners and data users should carefully evaluate and compare different cloud providers before choosing one that meets their needs and expectations. Some of the factors to consider include the type of cloud service (such as software as a service, platform as a service, or infrastructure as a service), the location of the cloud servers, the security and privacy measures, the data backup and recovery options, the data portability and interoperability features, and the customer support and service level agreements.

3. implement data governance and management policies and procedures. Data governance and management are essential for ensuring the quality, integrity, and security of data in the cloud. Data owners and data users should implement policies and procedures that cover the entire data lifecycle, from data collection and creation, to data storage and processing, to data usage and analysis, to data deletion and disposal. These policies and procedures should also align with the data ownership agreements and contracts, and comply with the relevant laws and regulations. Some of the aspects of data governance and management include data classification, data encryption, data access control, data audit and monitoring, data retention and deletion, and data breach response.

4. Monitor and review data ownership in the cloud regularly. Data ownership in the cloud is not static, but dynamic and evolving, as data, technology, and business needs change over time. Therefore, data owners, data users, and cloud providers should monitor and review data ownership in the cloud regularly, and update the agreements and contracts, policies and procedures, and systems and tools accordingly. This will help to ensure that data ownership in the cloud remains clear, consistent, and compliant, and that data is used and protected in the best possible way.

Some examples of how different organizations and industries deal with data ownership in the cloud are:

- Healthcare: Healthcare data is highly sensitive and regulated, and data ownership in the cloud can be complex and challenging. One example of how healthcare organizations deal with data ownership in the cloud is the Health Insurance Portability and Accountability Act (HIPAA), which is a US law that sets the standards for the protection of health information. HIPAA requires healthcare organizations and their cloud providers to sign a business associate agreement (BAA), which defines the roles and responsibilities of each party regarding the use and disclosure of protected health information (PHI). HIPAA also requires healthcare organizations and their cloud providers to implement administrative, technical, and physical safeguards to ensure the confidentiality, integrity, and availability of PHI.

- Education: education data is also sensitive and regulated, and data ownership in the cloud can be complicated and contentious. One example of how education organizations deal with data ownership in the cloud is the Family Educational Rights and Privacy Act (FERPA), which is a US law that protects the privacy of student education records. FERPA gives students and parents the right to access, amend, and consent to the disclosure of their education records, and limits the access and use of education records by third parties, such as cloud providers. FERPA also requires education organizations and their cloud providers to have written agreements that specify the purpose and scope of the data sharing, the security and privacy measures, and the data retention and deletion policies.

- Finance: Finance data is also sensitive and regulated, and data ownership in the cloud can be risky and costly. One example of how finance organizations deal with data ownership in the cloud is the payment Card industry data Security standard (PCI DSS), which is a global standard that applies to any organization that processes, stores, or transmits payment card data. PCI DSS requires finance organizations and their cloud providers to comply with a set of requirements that cover the security of payment card data, such as data encryption, data access control, data audit and monitoring, data breach response, and data security testing. PCI DSS also requires finance organizations and their cloud providers to have a formal agreement that defines the roles and responsibilities of each party regarding the protection of payment card data.

7. Jurisdictional Issues

One of the most challenging aspects of data ownership is how to deal with cross-border transactions involving data. Data is often stored, processed, and transferred across different jurisdictions, each with its own legal framework and regulations. This raises a number of questions, such as: Who owns the data? What rights and obligations do the data owners and users have? How can data ownership be enforced across borders? How can data protection and privacy be ensured in different jurisdictions? How can data-related disputes be resolved? These are some of the jurisdictional issues that data owners and users need to consider when engaging in cross-border transactions involving data.

In this section, we will explore some of the main jurisdictional issues related to data ownership in cross-border transactions, and provide some insights from different perspectives. We will cover the following topics:

1. The concept of data ownership and its legal implications. Data ownership is not a well-defined concept in most jurisdictions, and it may vary depending on the type, source, and nature of the data. Data ownership may also depend on the contractual agreements between the parties involved in the data transaction. Data ownership may entail different rights and obligations, such as the right to access, use, modify, share, delete, or monetize the data, and the obligation to protect, secure, or anonymize the data. Data ownership may also affect the liability and responsibility of the data owners and users in case of data breaches, misuse, or infringement.

2. The choice of law and jurisdiction in data transactions. When data is transferred across borders, the parties involved in the data transaction need to agree on which law and jurisdiction will apply to the data and the transaction. This may be done through explicit clauses in the contract, or through implicit rules based on the location, nationality, or domicile of the parties. The choice of law and jurisdiction may have significant implications for the data ownership rights and obligations, as well as the data protection and privacy standards. For example, some jurisdictions may have more stringent or lenient data protection laws than others, or may have different approaches to data ownership, such as recognizing data as a property right, a personal right, or a public good.

3. The enforcement of data ownership rights and obligations across borders. Another challenge of data ownership in cross-border transactions is how to enforce the data ownership rights and obligations across different jurisdictions. This may involve different mechanisms, such as contractual clauses, arbitration, litigation, or regulatory intervention. The enforcement of data ownership may face various obstacles, such as the lack of harmonization or cooperation between different legal systems, the difficulty of identifying or locating the data owners or users, the complexity of proving or quantifying the data-related damages, or the risk of conflicting or overlapping claims or remedies.

4. The resolution of data-related disputes across borders. Finally, data ownership in cross-border transactions may also give rise to data-related disputes between the data owners and users, or between the data owners or users and third parties, such as governments, regulators, competitors, or consumers. These disputes may involve various issues, such as the validity, interpretation, or performance of the data contract, the infringement or violation of the data ownership rights or obligations, the breach or compromise of the data protection or privacy, or the compensation or restitution of the data-related losses or harms. These disputes may be resolved through different methods, such as negotiation, mediation, arbitration, or litigation, depending on the preferences and agreements of the parties, or the availability and suitability of the dispute resolution mechanisms.

These are some of the main jurisdictional issues that data owners and users need to be aware of when engaging in cross-border transactions involving data. Data ownership is a complex and evolving concept that requires careful consideration and negotiation of the data ownership rights and obligations, as well as the choice of law and jurisdiction, the enforcement mechanisms, and the dispute resolution methods. By understanding and addressing these issues, data owners and users can ensure a more efficient, secure, and fair data transaction across borders.

8. Legal Remedies and Protection Measures

One of the most challenging aspects of data ownership is how to enforce it in practice. Data owners may face various threats and violations of their rights, such as unauthorized access, use, disclosure, modification, or deletion of their data. Moreover, data owners may have different interests and preferences regarding how their data should be handled, shared, or monetized. Therefore, data owners need effective legal remedies and protection measures to safeguard their data and assert their ownership rights. In this section, we will explore some of the possible ways to enforce data ownership, from both the data owner's and the data user's perspectives. We will also discuss some of the benefits and challenges of each approach, as well as some examples of how they are implemented in different contexts.

Some of the possible ways to enforce data ownership are:

1. Contracts and agreements: Data owners and data users can enter into contracts or agreements that specify the terms and conditions of data ownership, such as the scope, purpose, duration, and compensation of data use. Contracts and agreements can also include clauses that define the responsibilities and liabilities of each party, as well as the dispute resolution mechanisms and remedies in case of breach. Contracts and agreements can be formal or informal, written or verbal, depending on the nature and context of the data transaction. For example, data owners can sign a data license agreement with a data user that grants them a limited, non-exclusive, and revocable right to use their data for a specific purpose and period of time, in exchange for a fee or other benefits. Alternatively, data owners can agree to a data sharing agreement with a data user that allows them to access and use their data for free or for mutual benefit, subject to certain restrictions and obligations.

2. Laws and regulations: Data owners and data users can rely on existing laws and regulations that govern data ownership, such as intellectual property laws, data protection laws, consumer protection laws, and contract laws. Laws and regulations can provide a legal framework and a set of rules and principles that define and protect the rights and interests of data owners and data users, as well as the sanctions and penalties for violations. Laws and regulations can also establish the jurisdiction and authority of courts and regulators to enforce data ownership and resolve disputes. For example, data owners can claim ownership of their data under intellectual property laws, such as copyright, trademark, or patent laws, if their data meets certain criteria of originality, distinctiveness, or inventiveness. Alternatively, data owners can invoke data protection laws, such as the General data Protection regulation (GDPR) in the European Union, or the California consumer Privacy act (CCPA) in the United States, to exercise their rights over their personal data, such as the right to access, rectify, erase, or port their data, or the right to object, restrict, or withdraw their consent to data processing.

3. Technical and organizational measures: Data owners and data users can implement technical and organizational measures that enable and facilitate data ownership, such as encryption, authentication, authorization, auditing, logging, or anonymization of data. Technical and organizational measures can provide a practical and operational means to enforce data ownership, by ensuring the security, privacy, integrity, and quality of data, as well as the accountability and transparency of data use. Technical and organizational measures can also support and complement the contractual and legal mechanisms of data ownership, by providing evidence and verification of data transactions and compliance. For example, data owners can encrypt their data with a unique key that only they possess, to prevent unauthorized access or use of their data by third parties. Alternatively, data owners can use blockchain technology to create a decentralized and distributed ledger of data transactions, to track and trace the provenance and ownership of their data.

9. Evolving Concepts of Data Ownership

1. The shift Towards User-centric Data Ownership:

With the increasing awareness of privacy and data protection, there is a growing emphasis on empowering individuals to have more control over their personal data. Users are demanding greater transparency and consent mechanisms, enabling them to determine how their data is collected, used, and shared.

2. blockchain Technology and decentralized Data Ownership:

blockchain technology has the potential to revolutionize data ownership by providing a decentralized and immutable ledger. It allows individuals to have full control over their data, eliminating the need for intermediaries and enhancing security and privacy. Smart contracts can enable users to define specific conditions for data access and usage.

3. Data Ownership in the age of Artificial intelligence:

As AI technologies advance, questions arise regarding data ownership in AI-generated outputs. Who owns the insights and predictions generated by AI algorithms? Should it be the data provider, the AI system developer, or the AI system itself? These complex issues require careful consideration and legal frameworks to ensure fair and ethical data ownership.

4. Data Cooperatives and Collective Ownership:

Data cooperatives are emerging as a potential solution to democratize data ownership. These cooperatives allow individuals or communities to collectively own and manage their data. By pooling resources and sharing data, participants can negotiate better terms with data consumers and have more control over how their data is utilized.

5. cross-Border data Ownership and Jurisdictional Challenges:

With the global nature of data flows, cross-border data ownership becomes a complex issue. Divergent data protection laws and jurisdictional challenges can create conflicts and uncertainties. International collaborations and harmonization efforts are needed to address these challenges and establish clear guidelines for data ownership in a globalized world.

6. Data ownership and Intellectual Property rights:

The relationship between data ownership and intellectual property rights is evolving. As data becomes a valuable asset, questions arise regarding copyright, patents, and trade secrets associated with data. Legal frameworks need to adapt to ensure adequate protection and incentivize innovation while respecting data ownership rights.

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