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This response to “The Current State of Research Data Management in Canada: A Report by the Digital Research Alliance of Canada” was written by Deb Verhoeven.

Data, famously, just wants to be free. But it might also be said that data just wants to dance. Digital data is notably social at heart. Its binary form enables it to mingle easily with other digital data. Machine reading technologies mean that data can communicate directly with other data, bypassing human mediation. This potential for social capability has given rise to data management techniques that favour comparison, correlation and conformity and are built on value systems that prioritise precision, simplification and efficiency.

A recent significant report reiterates this emphasis on the benefits of integration as a simultaneously technical and systemic objective. In its recent position paper on The Current State of Research Data Management in Canada, The Digital Research Alliance of Canada (formerly the New Digital Research Infrastructure Organisation) tautologically explains interoperability by focussing on the establishment of common research procedures sustained by pre-defined relationships, cohesive infrastructure, and an operating framework that actively inhibits innovation:

Achieving interoperability between components of the RDM ecosystem relies on common schemas, standards, and protocols for collecting, organizing and describing research data and supporting infrastructure. In order to maximize the potential of research data, it must be able to be exchanged securely and integrated between different systems, while being interpreted correctly and appropriately by different users. To support both semantic and technical interoperability, operating frameworks are required that define the procedures, terms, and relationships necessary to allow data to be exchanged unencumbered between digital research infrastructures. These provide an architecture to the ecosystem, which allows new data, software, and infrastructure to be developed and integrated by conforming to these existing frameworks. (p. 5)

If data is to dance then we must build a ballroom to a standard size, play a pre-recorded unvarying duple rhythm and only admit data that already knows how to tango.

But what if we evaluated data’s desire to dance in terms of improvisation, flexibility and interpretation rather than as the correct execution of a tightly synchronized choreography? What if we started from the premise that the relational capacity of data might also play a role in understanding and enabling social change rather than just reiterating procedural conformity? How might a perspective derived from the humanities, with a focus on creativity, co-operation, complexity and contestation, and equally with a sensitivity to the ways data and power are mutually implicated, alter the ways to manage data integration, exchange and interoperation? How do we reconcile the social ambitions of data interoperation with the possibility that neither humans, nor data, dance to the same beat nor with the same ability and flair?

Data just wants to be free-size? Beyond a stretch fabric approach to Data Management

The limitations of standardization are well rehearsed in many fields. Clothing sizes are a great example of the way politically deduced, selective, historically specific “averages” were (and continue to be) deployed to promote normalized systems for categorizing the human body. These uncomfortable categories have the entirely detrimental effect of demarcating precisely who is not a good “fit”. And it’s not just about the cut of the cloth. It’s the materials and fasteners themselves, and it’s also the assumption that all wearers have the same needs, mobility and bodies all the time. Data systems designed around the value of conformity similarly relegate ill-fitting data and those it represents to the cutting room floor.

The response to these evident systemic shortcomings, however, is not to fabricate “one-size fits all” or even “one size fits most” solutions. I’m not trying to suggest that data wants to be “free-size” or even “unsized”. I’m certainly not proposing the adoption of a stretch fabric approach to information management. But we might look to the adaptive clothing movement for inspiration with its use of innovative materials ( and an entire ethic based on inclusive manufacturing and design ( Adaptive clothing is intended from the outset to be adjustable to a variety of uses and users.

I want RDM that sets a precedent for diversity and inclusion by thinking of information design and management systems as the digital information version of “adaptivewear”. In other words, I want Canada’s future research data ecology to focus first and foremost on information management in terms of problem-solving, innovation, intersectionality and empathy rather than accentuating its benefits solely in terms of productivity, regulation, consistency and control. I want data that dances to different beats. And without the need to ever wear Lycra.

Deb Verhoeven is Canada 150 Research Chair in Gender and Cultural Informatics at the University of Alberta. She served on the inaugural board of NDRIO until July 2021 and was not involved in the preparation or oversight of the report The Current State of Research Data Management in Canada.