Making space for diverse ways of knowing in museum collections information systems – Erin Canning (August 2020)

In light of ICOM’s dedication of International Museum Day 2020 to the theme of “Museums and Equality: Diversity and Inclusion”, it is worth looking at how documentation practices, policies, and infrastructures – technical and otherwise – can fit into these broader institutional goals. Committing to diversity, equity, and inclusion involves ensuring that our institutions are open to new ways of thought and practice by critically examining existing systems no matter how long they have been in place. Collections information systems should be included within the scope of such a review, as the way that data is structured within them and the kinds of knowledge that they accommodate can uphold entrenched power relations.


This argument is based on two foundational statements:

  1. That information systems – such as collections management systems – are artifacts of systems of power, and like any other system or infrastructure, they enact the power relations of those who originally designed and created the systems to the detriment of those upon whom power is enacted; and
  2. That there are many different kinds of knowledges and ways to come to know things, and these should all be considered as legitimate object knowledge.

ICOM International Museum Day 2020 – Museums for Equality: Diversity and Inclusion


The way that our collections information management systems are designed, and the kinds of information that they afford space for, deeply influences what we view as legitimate knowledge or way of knowing: if there is no way to hold a kind of knowledge or type of information in a collections management system, then it is relegated to a space outside of the official, institutional, source of knowledge about an object. This is one of the consequences of the design of these systems that we use to document objects and collections. How does a knowledge seeker (system user) know that they are only seeing a part of the picture if the information system they are using does not acknowledge diverse ways of knowing? If the problem is not that there is an empty data field, but no field at all to hold a different kind of information, then it is as if that data does not exist, is not of value. As such, collections information management systems impose constrained notions of what is object information, and therefore, what is an object – and what is object knowledge. This is a system of belief that has been encoded into collections management systems.

Furthermore, object information is contextually based: it is not simply what is known about an object, but what is known at particular points in time, based on what has been conveyed by the individuals who have made, discovered, collected, or researched an object, and the individuals who then inserted that information into a museum documentation system. These are incredibly powerful acts, with political and ethical implications.

Traditionally, collections information management systems have been focused on the management of collections as physical assets rather than the information embodied by the objects in museum collections (Peacock, Ellis, & Doolan, 2004). While they started out as digitized forms of catalogue cards and ledgers, database technologies are now fully capable of supporting the inclusion of multiple forms of knowledge. This would, however, require a revisiting of the existing standards off of which collections software is based, in order to accommodate new kinds of information as well as types of knowledges and expertise.

Groupings of cognitive biases into four main categories
(categories by Buster Benson, visualization by John Manoogian III) 


Feminist theory and queer theory can help guide such a review, as they are both focused on interrogations of systems and relations of power and therefore are lenses through which we can approach an analysis of museum collection information systems – especially when we have goals of diversity, equity, and inclusion in mind. Ultimately, this is an analysis of those systems of power and the ways that they are built into our systems and processes, and then hides there: once a system is in place, it becomes naturalized, “just the way things are”. This means we do not question how our systems are constructed, what values or judgments might be encoded into them, or why they were thought up in the first place.

Both feminist and queer digital humanities scholarship argue that technology can be used to bring to light and critique dominant norms. Hiding within classification systems – such as collections information management systems – are encoded biases, false binaries, and implied hierarchies. Feminist thinking teaches us to question why such distinctions have come about and what values they reflect – not just the categories, but the structure of the system itself.

The Feminist Data Manifesto-No is a series of commitments and refusals based on the principles of feminist data practices

In entering an analysis of museum collections information systems using feminist and queer theories, I propose a series of guiding questions, provocations, and arguments to consider:

3 questions from feminist theory:

1. What would collections information management systems look like if they emerged from the concerns of feminist theory?

This would mean not augmenting or adapting existing problematic infrastructure, but to build something entirely new.

2. What would collections information management systems look like if they were built to show data as the products of sets of relationships of power, experiences as they have been lived?

Feminist theory encourages us to start understanding data not as givens but as constructions that are actively created by people at times and in places – contextual in nature, and event-centric in their creation.

3. What would collections information management systems look like if they did not prioritize only information based on physical and visual analysis, rooted in western pedagogical theory, but also made space for information that comes from engaging all of the body’s senses and ways of understanding the worldin the pursuit of knowledge?

Feminist theory urges us to prioritize those things coded as “feminine” and value the ways of knowing that have been “othered”. Feminist theory argues that emotion and other forms of subjective experiences are legitimate sources of knowledge.

2 provocations from queer theory:

  1. Everything is subjective and contextual:

Rather than taking categories as stable and fixed, queer theory sees these them as shifting and contextual; there is no such thing as universal and unchanging information. There is no way to separate categories from the context in which they were first proposed and implemented.

  1. Nothing is ever complete:

Queer theory rejects the notion that knowledge is ever complete or even finalizable. As such, queer thinking must be applied to the conceptual models to show this, not just to add new metadata.


Excerpt from “7 Ways to Visualize Gender”




1 argument for event-centric collections information data models:

Rather than flattening data into binaries to fit object-centric data models, we should seek to show uncertainty, contextuality, variation, instability, and multidimensionality. Event-centric data models, such as that which CIDOC-CRM takes as its base, offer a way to do this as they permit for greater flexibility and model network relationships not set hierarchies.

Although there are specific aspects and nuances to feminist theory and queer theory, a common thread runs through them both: the relational and contextual nature of object information and meaning. Through this lens, it is clear that museum information systems must address the need to provide for different kinds of complexity of museum object information, and also integrate various sources of object information and ways of knowing.

Illustration of linked data structure by Elco van Staveren



Museums must look to information systems that are based on event-centric data models and capable of including shifting, variable, and contextually known information in order to begin to address these concerns concern – such as the CIDOC-CRM. As an event-centric data model, the CIDOC-CRM provides a unique structure that is different from collections management systems software environments, which are built on object-centric information models. This is an important distinction because the CIDOC-CRM says that all information is the result of an event, which allows us to show that information is not intrinsic or static, but always the result of one or more persons encountering one or more things at a certain moment in time – and it is this meeting that results in the creation of a piece of data. Data is never inherent to something; it is only ever made by people at moments in time and space.

Designing information systems that work towards diversity, equity, and inclusion requires new tools in our collective toolbox. We need expertise in the practical application of theory work focused on interrogations of structures of power in addition to technical and subject matter expertise. In order to begin to achieve these goals, collections information management system schemas must be based on data models that are aligned with these concerns. Two key components of this reconceptualization – both in the end product and the work involved to get there – are the development and use of event-centric information systems such as the CIDOC-CRM, and the true valuing of different knowledges and different ways of knowing.


Bio: Erin Canning is the Ontology Systems Analyst for LINCS, a 3-year project funded by the Canada Foundation for Innovation that seeks to convert large humanities datasets into an organized, interconnected, machine-processable set of resources for Canadian cultural research. Erin is interested in the possibilities that semantic data modelling offers for museum collections data in more holistic and inclusive ways, as well as feminist and queer approaches to museum data practices. Erin holds Masters degrees in Information (MI) and Museum Studies (MMst) from the University of Toronto (2018).  Erin tweets at @eecanning



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