Big Data and Museums

Big Data: it’s a term that conveys power, generates suspicion and even scares some of us. But what role does big data have to play in the future of museums?

Technology has all but taken over the modern world, and a big part of this digital revolution is data collection. Businesses, brands, organisations and communities alike are using Big Data to provide value, deliver services and understand trends. And museums are no exception.

In a presentation in 2017, Brendan Ciecko, the CEO of museum technology start-up Cuseum explored the role of AI and machine learning in helping museums to collect data.

“Machine learning is a method of data analysis that automates analytical model building using algorithms that iteratively learn from data. [It] allows machines to find hidden insights without being explicitly programmed to look for.”

Or, to put it more simply, a machine can look for patterns in data that it wasn’t specifically programmed to find.

“It’s no surprise that museums have tremendous amounts of data,” says Ciecko, “and strides have been made over the past decade towards structuring collections data and making it available for the public to access and experiment with.”

Ciecko continues: “This valuable metadata holds power and yields interesting ways to analyse museums, collections, objects and creators in new ways.”

But, in order to carry out such analysis successfully, “lots of resources, tools, times and expertise” are necessary.

Big Data at The British Museum

As the UK’s biggest visitor attraction and the second-most visited museum in the world, the British Museum welcomes around 6.5 million visitors every year. Yet, until recently, the museum had no easy way of finding out how people experience its exhibitions: what routes they take; what they engage with; how many minutes they take at each installation; which pieces they choose to ignore. This is where Big Data comes in.

By partnering with Microsoft, the British Museum has been able to analyse the way visitors interact with the 800,000 feet of gallery space.

Although the museum has tracked visitor information with consent for years – via audio guides and interactive exhibits – Big Data allows them to do so holistically, getting the bigger picture on what’s working and what isn’t. This has helped the institution gather more information on the average visitor journey.

Siorna Ashby, Senior Project Manager at the museum, said the team had “asked where most people start their journey. We assumed it was the Rosetta Stone on the ground floor, but we also saw people start on the second and third floor.”

Technical Evangelist at Microsoft, Andrew Fryer, also shared his thoughts, saying: “The British Museum did all of that work themselves. We just showed them the art of the possible.”

The Big Data Pyramid

The British Museum’s use of Big Data is not unique. Many cultural institutions around the world are starting to incorporate machine learning into their procedures in order to gain a clearer understanding of how their museum is being used.

This is the central benefit of Big Data, highlighted by the famous DIKW Hierarchy. This pyramid illustrates how Data becomes Information, which then becomes Knowledge and finally – at the top of the pyramid — sits Wisdom. Data can provide valuable information in large quantities, which curators and organisers can then use to inform museum decisions going forward.

GVAM – a Spanish organisation behind mobile museum guides – describes the five key dimensions of Big Data in museums:

–        Volume (the ability to gather lots of information)

–        Velocity (the ability to gather information quickly)

–        Variety or Complexity (the ability to gather information from a wide range of sources)

–        Veracity (the ability to convert data into quantitative information generated from the interaction of the visitor)

–        Valor (the value that Big Data can provide for distinct areas and departments within the museum)

In this way, Big Data can be seen to deliver in terms of both quantity of information and quality.

How big does Big Data need to be?

Big Data is flexible, which is important as not every museum or cultural organisation requires the same breadth of analysis.

For the very biggest museums, lots of data must be collected to understand visitor habits in their entirety. But for most museums, a smaller data pool can still attract significant findings about the way your institution is used and enjoyed.

Data quantity and data quality go hand in hand. The more data you can gather, the more accurate your holistic picture becomes.

Big Data can help museums overcome challenges

New Zealand technology entrepreneur Angie Judge specialises in museum culture, and describes how, until surprisingly recently, arts and culture were primarily a “sport of the rich and powerful.”

Judge argues that Big Data is changing that. She acknowledges the dilemma of not treating museum “visitors” as “customers”, addressing the argument that “culture should not be commercialised”.

Citing sites like the US 9/11 memorial, Judge explains,

“But, the reality is that museums need money to deliver on their social mission, and perhaps the hidden problem is that our old model of grants and funding doesn’t fit very well into the modern world.” In the USA, where cuts to museum funding are expected to total $500 million this is a pressing problem.

In answer to the growing finance challenges faced by museums, Judge has founded her own company – Dexibit – dedicated to advancing Big Data technologies in the cultural sector. The company specialises in using a range of technologies to pull together holistic data about the visitor experience, providing museums with the tools they need to better serve their audiences.

The Museums and AI Network

Not only can Big Data provide insight between museums and visitors, but it can also help bring institutions together from across the industry.

Nowhere are these factors more clearly presented than with the Museums and AI Network, formed in 2019 by Dr Oonagh Murphy, Goldsmiths, University of London and Dr Elena Villaespesa, School of Information, Pratt Institute.

The network is funded through the AHRC Research Networking Scheme, and has already brought together over 50 leading academics and museum professionals to examine current practice, challenges and near future AI technologies – both in the United Kingdom and in the United States.

The network has also engaged with more than 200 members of the public through high profile events, workshops and conversations. The toolkit created by the network aims to support museum curators and attendees alike in understanding the possibility of Big Data and AI technologies, empowering a wide range of museum professionals to develop robust project plans.

Describing the intent behind the network, Dr Oonagh Murphy says: “The network came together to develop a series of small working groups that provide the platform for museum professionals to get together and talk about the challenges they’re facing when it comes to using AI, but also to share some examples of good practice.

“Museums are really interested in AI for two main reasons,” Murphy explains. “AI allows museums to better understand their visitors and creates new opportunities to develop programmes that are more in tune to what visitors want.”

What are the concerns when it comes to Big Data?

We’ve mentioned how useful Big Data can be in museum spaces, but it’s important to remember that Big Data is just that: data. How this data is interpreted and what actions are taken as a result of this data is left up to the museum.

Museum Website Design and Development experts, Cuberis, explore the limitations of Big Data more thoroughly, describing how “there is a certain threshold of quantity of data before you can expect to get accurate results.

“And even if you do have a statistically relevant sample, with dependable results, that’s no guarantee that the results will be actionable. If a particular question receives a 55%-45% split, is that enough to take action on?”

Should, for example, an exhibit be cut if it doesn’t meet footfall expectations over the period of a month? Or does this approach breed a culture that is too cut-throat and fails to consider the nuance of “human” interaction?

This highlights how, useful as Big Data might be, it is ultimately a tool. And like any tool, it needs to be utilised properly in order to deliver the most useable results for museums and galleries.

Dr Oonagh Murphy of the Museums and AI Network also addresses the issues surrounding Big Data, commenting: “It’s never going to be as good as a curator. But, it’s faster, it’s quicker and it’s cheaper.

“So one of the conversations we’ve been looking at is this idea of: is it better to have content that’s not quite perfect but adds to the conversation than have no content at all.”

Big Data: a new avenue of communication

What’s clear from the examples and expertise surrounding Big Data is this: technology provides opportunity. When utilised correctly, Big Data can help museums deliver meaningful and engaging exhibitions that speak to their visitors.

This is something touched on by Judge, who describes how, despite having moved on from the days of private collections with exclusive access, museums still struggle with the balance of power. What big data does is give that power back to the public:

“Big data allows museums to listen, rather than just talk,” explains Judge. “And that turns curation into a conversation.”

When we put it into this context, big data can be a very important tool indeed.