Is data really that important to a business?
A quick survey of the top companies by market capitalisation readily reveals that data is key.
We use cookies and other similar technology to collect data about you to allow us to deliver our online services, measure our website audience and improve your browsing experience. Full details on the cookies we use are set out in our Cookies policy. Please click OK to signify your consent to our use of cookies.
You can withdraw your consent by clicking “manage cookies” and following the instructions shown.
Global | Publication | February 2021
In many jurisdictions pure information, or data, is not considered to be property.1 This is because a claim to property in intangible information presents obvious definitional difficulties, having regard (at least in common law jurisdictions) to the criteria of “certainty, exclusivity, control and assignability” that normally characterize property rights at common law, distinguishing them from personal rights.2 (The position of cryptoassets may be different, as they are increasingly being regarded as “digital assets” – as opposed to pure information – capable of constituting property in an increasing number of jurisdictions.)3
Accordingly it may not be straightforward for a data-holder to exercise a proprietary claim over pure information or data. In many jurisdictions rights to data / datasets are in practice not exercised by reliance on ownership of title or exclusive possession, but rather, by control to access and use. The equivalent of ownership in relation to data in practice may be better considered as the ability to control.
A data holder might:
The determination of who should have the right to control data may not be obvious. For example:
Some jurisdictions are already considering ways to address usage rights in co-generated data. For example:
A quick survey of the top companies by market capitalisation readily reveals that data is key.
The value that can be gained from data by businesses will inevitably lead to an increase in the use of data to improve daily operations and to develop new products, services and processes.
In many jurisdictions pure information, or data, is not considered to be property. This is because a claim to property in intangible information presents obvious definitional difficulties.
There is a patchwork of different rights, intellectual property rights and contract rights that may apply to data. Understanding the way in which these rights come into play enables a business to understand how its data assets can be protected.
Disruptive technologies, such as AI, IoT, AVs, distributed ledger technology (DLT), cryptocurrencies and smart contracts, generate many different forms of data. What are the particular characteristics of such data, and to what extent can intellectual property rights or other rights protect them?
In this section, we review the EU’s position with regards to industrial and non-personal data and look at whether other jurisdictions have similar initiatives.
Data location laws (in relation to industrial and non-personal data) can be restrictive (as in banking secrecy laws, which may require some types of data to remain onshore or to be “localised”) or liberalising (as in laws that ban the prohibition of export of data from a locality).
In furtherance of the objective of leveraging existing datasets paid for by public funds, a number of jurisdictions have sought to make public sector information (PSI) available to industry.
The exclusive possession or control of data can have antitrust / competition law considerations, giving rise to access disputes.
The uncertain nature of intellectual property rights in data means that “contract is king” in data transactions.
Data is an incredibly valuable resource for businesses, enabling organisations to effectively operate and to make business improvements. In order to exploit this value most effectively, businesses must invest in good data management.
Errors, incompleteness or biases within data may flow through, and be amplified by, data analytics process outputs upon which a business's strategic and investment decisions may depend, potentially causing business losses. In this section we deal with liability arising out of use of data / datasets that are in some respect sub-optimal.