Open Access Policy

For the principles of Open Data Ethics, please see “Open Data Ethics”, Appendix 5 of Central’s Open Access Policy.

Frequently Asked Questions

1. What is data in a performing arts context?
2. How do I decide what sort of data I need to collect for my research?
3. How do I manage data in a way that protects participants?
4. How and why would I share my research data?
5. What constitutes a reasonable Data Management Plan?
6. How might I contextualise my data?
7. What do I need to think about when storing my data?
8. What is metadata? What are metadata standards?

9. What could a Data Access or Data Availability Statement look like? 

10. Where can I find training and support?

1. What is data in a performing arts context?

In the arts and humanities, researchers are often more inclined to think of having “research materials” than of having “data.” However, there is a lot of overlap. The current push toward open data challenges researchers to consider how to curate and cultivate materials generated in the process of research in a manner that makes them more reusable by others.

Understanding “data” (and what “data” is for any research project) is a useful way of deepening understanding about the research itself, including its aims and objectives. The Concordat on Open Research Data (2016) defines “data” as follows:

Research data are the evidence that underpins the answer to the research question, and can be used to validate findings regardless of its form (e.g. print, digital, or physical). These might be quantitative information or qualitative statements collected by researchers in the course of their work by experimentation, observation, modelling, interview or other methods, or information derived from existing evidence. Data may be raw or primary (e.g. direct from measurement or collection) or derived from primary data for subsequent analysis or interpretation (e.g. cleaned up or as an extract from a larger data set), or derived from existing sources where the rights may be held by others. Data may be defined as ‘relational’ or ‘functional’ components of research, thus signaling that their identification and value lies in whether and how researchers use them as evidence for claims.

They may include, for example, statistics, collections of digital images, sound recordings, transcripts of interviews, survey data and fieldwork observations with appropriate annotations, an interpretation, an artwork, archives, found objects, published texts or a manuscript.

In the performing arts, research data might include curated historical datasets, surveys collected during applied theatre projects, and process notebooks for practice research or making a performance. It might include the feelings experienced when watching a performance noted down during or after, the embodied experience of making or watching a piece of work, or any number of ephemera that we encounter in this field.

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2. How do I decide what sort of data I need to collect for my research?

Researchers sometimes want to collect as much data as possible just in case, so that they can decide what to do with it later. However, it is increasingly important to be specific about what data is being collected and why. For example, when conducting a survey or interviews, is knowing the gender of the respondents necessary? If the research is about gender, then yes. If it is not, it is important to ask why that data is being collected and how it will be useful for the research.

In more complex circumstances, where data is not as clear cut as information provided directly from participants, for example, where observing rehearsals and taking notes or using feelings and responses to performance, then returning to the research questions is important. Clear research questions can ensure the data collected is both useful for the research and specific.

When working with others, it is important they know what data is being collected. For example, when researching a production and observing a rehearsal, the actors or participants should have a clear sense of the limits of what is being attended to, not just in terms of their personal characteristics, but also about actions and behaviours.

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3. How do I manage data in a way that protects participants?

The multiple stakeholders of data – such as participants and contributors, recipients and beneficiaries, funders and repositories, and researchers themselves – may present different needs and agendas to be negotiated in data collection and management. Collecting data ‘care-fully’ involves balancing the need for attribution and recognition of participants with the ethical imperative to avoid harm. Anonymisation and pseudonymisation, for example, can be used to mitigate the risks of exposure for participants. However, anonymisation is not always appropriate – for example, when acknowledging participants’ creative or authorial work, or when participants feel that research holds the potential to amplify their voices in specific ways that are not compatible with anonymisation. Researchers should always be transparent with participants about how their data is managed, shared and protected, and this should be discussed in establishing informed consent. Where justifiable, data access can be restricted, with those restrictions documented, revisited and reviewed.

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4. How and why would I share my research data?

UK Research and Innovation state that: “Making your data as open as possible means that publicly funded research is more: transparent and easily scrutinised, helping to increase public trust; easy to re-use and build upon; collaborative and efficient” (UKRI, 2022). 

Whilst there may be circumstances where due to security, confidentiality or commercial reasons it is important to restrict data, funders increasingly expect research data to be as open as possible. Furthermore, making research data open can be particularly important when working with data that might have long-term value — such as research with and about marginalised communities or groups.

Think of a curated and cultivated approach to open data as a way to fill out beyond what you might have published via other means. Sometimes when writing up research, there are key bits of information (responses from participants, images of performances, notes from rehearsals and so on) that we are excited by or we think should be shared widely, but are not within the scope of the particular research output we are working on. Sharing your data and making it accessible is a useful way of ensuring these research findings are available, shareable and reusable even when they do not make it into the particularly research outputs of any given bit of research.

There is no singular way to share research data, as each bit of research will have different forms of data which may be collected and stored in ways unique to that research project. However, researchers can be supported in scoping out and designing the most appropriate ways to disseminate research data (which can – and indeed should, where possible – be connected to how this data is collected). Rather than a one-size-fits-all approach, researchers are encouraged to explore the most appropriate ways of sharing their data to support their research from the start of the project. The more complex the project, the more likely a custom approach is needed.

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5. What constitutes a reasonable Data Management Plan?

A reasonable Data Management Plan (DMP) should show that the sustainability horizons for all aspects of a project’s research data have been considered. For example, the Feminist Data Manifest-No advocates for refusing “the use of data about people in perpetuity.” At the same time, oral history data can circumvent standard General Data Protection Regulation (GDPR) horizons, because it constitutes “archiving in the public interest.” So, what is reasonable and meaningful to stay around, and what could cause harm? In addition, a DMP should account realistically for the costs, timelines, and technological implications of ongoing preservation. For example, a document or spreadsheet might be stored in a way that is accessible much longer than a web-based experience; you could screen-grab a video of a web-based experience, but video files will still become obsolete without file conversion sooner than some other file types.

With every bit of research, it is important to consider how the data is managed, not just how and where it is stored but how it can be easily accessed and shared. Having a Data Management Plan is something which is increasingly important to funders, including UK Research and Innovation (UKRI) and specific bodies within UKRI such as the Arts and Humanities Research Council (AHRC). A DMP should help researchers to consider all the important aspects of their research in relation to data – from what the data is, to how it will be collected and stored, to how the data will be cared for and curated before it is disseminated.

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6. How might I contextualise my data?

Data contextualisation includes user guides, data biographies or other framing explanations of where the data comes from and how researchers envision it might be used. A key aspect of countering the supposed neutrality of data and ensuring proper reuse is to provide context about the process of collection and curation. As the Feminist Data Manifest-No puts it: “We refuse to consider data as raw and only an end product without context and values and to ignore that data has an origin story, and a creator or creators whose legacy must be understood in order to understand the data itself.”

So, what does a particular parameter really mean? Who or what was included or not? Who or what do the researchers know was not included? Two ways to push future users beyond taking research data at face value are to produce a data biography and/or a user guide. A simple data biography tells the story of the data, by providing information about who created this data, and how, where, when, and why it was collected. The resources below also link to a more complex data biography builder that focuses specifically on equity. A user guide provides a broader range of study-level documentation, from the contexts and methods employed in data collection to the assumptions underlying each datapoint.

Further, contextualization might include information on the structure of the data itself, and any conditions on future usage. For further information on data curation for reuse and on “justified and justifiable” restrictions on data use, see Principle #2 and Principle #7 of the Concordat on Open Research Data.

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7. What do I need to think about when storing my data?

When thinking about data storage, researchers might ask the following questions:

• What’s backed-up? – all, some or just the bits you change?

• Where? – original copy, external local and remote copies?

• What media? – DVD, external hard drive, USB, Cloud?

• How often? - hourly, daily, weekly? Automate the process?

• What method/software? – duplicating, syncing or mirroring?

• For how long is it kept? – are there data retention policies that might apply?

• When is it destroyed – is there a schedule for this? The only sure way to ensure data is irretrievable
is to physically destroy the drive (using an approved secure destruction facility).

Data management plans should include a suitable backup to alleviate the risk of the loss of data through damage/accident, or criminal infiltration. At the same time, the more places data is stored, the more researchers need to think about securing it. When dealing with data of a sensitive or confidential nature, it is particularly important to ensure that the storage of such information is suitably protected/encrypted.  If a research project uses cloud servers, some funders may require them to be located on servers within the UK and EU. The UK Data Service recommends Pretty Good Privacy (PGP), which is more complicated than just a password, but much more secure, and involves use of multiple public and private keys. Researchers may want to keep passwords and keys on paper (2 copies) and in a PGP (pretty good privacy) encrypted digital file.

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8. What is metadata? What are metadata standards?

Metadata is data about data – or asset of data that describes of gives information about other data. Metadata is used to give clearer understandings of data and datasets for those who might use them, helping them find relevant information or more easily discover resources. Adhering to pre-existing metadata standards can help to describe data in a consistent manner to ensure the usability of the metadata; however, findability and usability may differ for different contexts, so consider the knowledge structures to which the standard or standards you choose belong and the worldviews that they promote. Metadata can include descriptive information, as well as further details about provenance and access to and future use of data.

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9: What could a Data Access or Data Availability Statement look like? 

Your data access statement is included in the publication itself, and tells readers where they might be able to find supplemental materials, including underlying data and/or evidence to support your claims, or why none are available. An aspect of this is already covered by standard citational practices in our field of referencing primary and secondary sources in a manner that future researchers can find them again. In addition, there may be materials that you specifically gathered and collated, such as audience surveys or interviews, that may be useful to future researchers. If those materials have been held on a publisher’s website or in a data repository, then your data access statement might say something like “the research materials described have been deposited with … .”

Or alternately, they might be “available upon request from the author(s).” If there are restrictions or embargoes on the use of those materials, then there should be an explanation of why these are restricted and the terms under which they might be accessed. If the underlying data is completely unavailable, a data access statement needs to explain the rationale. Cambridge UP has a useful table of data availability statement templates under various conditions, ranging from “Data openly available in a public repository, with a permanent identifier” to “Data available on request due to privacy/ethical restrictions.” 

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10. Where can I find training and support?

Vitae is a globally recognised organisation that works to support the professional development of researchers. They offer training and it is free to register and access all sorts of resources. Jisc (another organisation that supports UK research and education) offers a thorough, step by step, Research Data Management Tool Kit. Another place for advice and practical help with research data management is the Digital Curation Centre.

Some individuals at Central who might be able to support researchers in thinking about sharing research data from as early as possible are Research Advisors, the Chair of the Research Ethics and Integrity Sub-Committee, the Open Data Ethics Working Party, and the Head of Digital Research. Please email the ethics team at Central with any questions.

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