Examples of ownership issues across different research data types

Different types of research data present unique challenges regarding ownership, intellectual property rights, and data management. In collaborative research, data is often created, collected, or processed by multiple individuals or organisations, resulting in shared ownership and legal or ethical obligations. Understanding these ownership arrangements is essential to ensure that data is used, stored, shared, and published in accordance with contractual agreements, copyright law, licensing requirements, and participant rights. The following examples illustrate how ownership issues can arise across different types of research data.

Tabular data: A researcher at a university analyses a dataset combining survey responses they collected with administrative data provided by a government agency. The university may own the survey data, while the government retains ownership of the administrative data, resulting in joint or shared ownership and restrictions on how the combined dataset can be shared.

Text data: A research project involves interviews conducted by a research team and later transcribed by an external transcription service. The participants contribute the content, the researchers design and collect the data, and the transcription company may hold rights over the transcript format. This creates a situation of multiple stakeholders with potential claims over the data.

Image, audio and video data: A documentary-style research project records video interviews with participants using a freelance videographer. The videographer may hold copyright over the recordings, while the research institution controls how the data is used, and participants have rights related to their image and voice. This results in joint ownership and layered rights.

Spatial data: A research team creates maps using geographic data sourced from a national mapping agency and combines it with their own field observations. The mapping agency retains rights over the base data, while the researchers own the newly created dataset, leading to shared ownership with licensing restrictions.

Relational data: A collaborative project between multiple universities produces a network dataset showing collaborations between organisations. Each institution contributes part of the data, meaning ownership is joint across partners, and any data sharing requires agreement from all parties involved.

These scenarios highlight that ownership of research data is often not straightforward, particularly when multiple contributors, institutions, or third-party data sources are involved.

Researchers should carefully consider ownership and copyright issues when preparing data for research, sharing, or publication. This includes assessing whether any rights need to be granted, restricted, or waived, particularly when multiple stakeholders or third-party materials are involved. Clear agreements at an early stage can help avoid limitations on how data can be reused or disseminated.

Where there is uncertainty, researchers are advised to consult with relevant institutional support, such as Ethics Committees and Research Offices, to ensure compliance with legal and ethical requirements. In more complex situations, particularly those involving contractual or intellectual property issues, it may also be appropriate to seek legal advice.

It is also important to note that copyright can be transferred from the original owner to another party, but this must be done formally in writing through a legal document known as an assignment. Without such a written agreement, copyright remains with the original creator.