Category: data economy

Inheritance of data

A natural extension of the consideration of the legal status of data is the question of whether data can be inherited. This is no longer just a theoretical issue. Data are increasingly valuable, making it vital to answer the question of whether data constitute an asset of the decedent’s estate that can be taken over by the heirs.

According to the Polish Civil Code, the decedent’s property rights and obligations are the subject of succession. But the estate does not include the decedent’s rights and obligations closely linked to his person and rights which, upon death, are transferred to designated persons irrespective of whether they are heirs.

Is it possible to inherit data based on such a definition of inheritance?

First of all, to answer this question, it is necessary to recall the division into different categories of data which, like the issue of classifying certain types of data as property rights, has already been analysed in our data economy series. Indeed, depending on which category of data we are dealing with, the assessment of whether a right or obligation should be included in the estate changes.

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What is the right to personal data?

When seeking inspiration for the future legal status of data, it is worth taking a closer look at how the right to personal data has been shaped. In particular, we could consider whether it is a property right and whether the current legal framework for the right to personal data corresponds to reality and meets our needs.

The attempt to define an absolute right to personal data is mainly driven by Art. 1(2) of the EU’s General Data Protection Regulation, which states that one of the objectives of the regulation is to protect the “right to the protection of personal data.” The right to protection of personal data is also enshrined in the Charter of Fundamental Rights of the European Union and the Treaty on the Functioning of the European Union.

The source of this right is found in European legislation. For this reason, an attempt to determine the substance of the right to data protection is difficult, as we cannot simply and directly refer to structures known from the different legal systems of the member states.

The essence of the right to data protection seems to be indicated in recital 7 of the GDPR preamble, which states, “Natural persons should have control of their own personal data.” Thus, the right to protection of personal data is primarily intended to give data subjects control over their data. The specific content of this right is defined by the protective instruments provided for in the GDPR. Among other things, these instruments consist of a guaranteed right to information about processed data, the right of control, but also the right to object to data processing. Many of these rights are similar to the bundle of rights also found in classical property law structures. However, important differences also exist.

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Data as crypto-assets

At first glance, it may not seem obvious to treat data as crypto-assets. But a closer look shows that the current and planned regulations for this new asset class could serve as a key legal framework for the future data economy.

The data economy and blockchain have a lot in common. Blockchain and data tokenisation are also a theme running through our data economy publications. Blockchain has revived the discussion of data tokenisation, i.e. turning data into an identifiable and tradable digital asset.

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What’s the MyData movement all about?

The contemporary debate about data, including discussions of the legal status of data, are hard to understand without defining the broader context. One element of this context is the demands of the movement referred to collectively as “MyData.”

A European strategy for data,” published by the European Commission in February 2020, alludes to the MyData movement in the context of the challenge presented by inadequate technological support for data subjects in managing their own personal data. On one hand the Commission perceives the potential inherent in personal data, in particular the potential for the data subjects themselves. Appropriately managed personal data can improve the quality of services received by data subjects (e.g. in the area of healthcare) and increase their control over their data. On the other hand, the Commission found that there is a lack of appropriate tools for managing data, and thus the inherent potential of the data is not being exploited to the fullest.

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Data and copyright

Is copyright a path to take to protect data? Can data be regarded as a result of creativity and, consequently, a protected work? Does the protection of a data filing system also include the data collected in it?

Non-personal data, in
particular data collected or generated by machines, has great economic and
scientific value. Increasingly, it is a key business asset, providing the basis
for launching new goods and services. It helps improve methods of detecting and
treating diseases, determine where to set up a wind farm or where to cut down
trees so they do not interfere with power lines, and helps ease traffic congestion
in cities.

Do entities collecting
such data or creating algorithms that harvest data, e.g. from the internet,
have rights to the data? Can such data be freely traded, e.g. sold or licensed?

This issue raises many unanswered questions. This article will address whether data is protected by copyright and, as a result, whether the data “owner” can use the instruments provided by the Polish Copyright Act to protect it against infringement by third parties.

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Different layers of data

The conceptual framework of the data economy also requires an understanding of the division of data into different layers. This may have great legal significance.

From a legal perspective, one of the most important issues of the data economy is undoubtedly the civil-law status of data (as we discussed in another article). However, it crucial to distinguish between different data layers. It turns out that when talking about “data,” we may be referring in practice to different dimensions of data.

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