One of the themes covered in CFM’s TrendsWatch 2014 report is the power of big data and data analytics. The ubiquity of internet-connected sensing devices and our relentless use of social media and online commerce generates 2.8 zettabytes (a zettabyte = 2 to the 70th power) every year. This flood of information is being fed into predictive algorithms that yield results that look nearly magical: forecasting spikes in unemployment, global conflict, disease outbreaks, even local crime. As people are quickly discovering, big data analytics, like any tool, can be misused, but when applied to appropriate problems with sound methodologies, they can transform whole sectors.
Can big data transform museums? Data mining can certainly be useful to individual museums–I’m chairing a session on that topic on Monday, May 19, 1:45 pm at the upcoming Alliance conference in May. Data on a museum’s visitors linked to US Census data via zip code can generate reams of illuminating demographic information. Tracking patrons’ use of museum space and amenities can suggest efficiencies of staffing and services. But I’m even more interested in the potential payoff of big data for the museum field as a whole.
As we’ve explored in TrendsWatch 2013 and on this Blog, we live in a society increasingly focused on concrete measurements of outcomes. This poses the risk that museums, in order to comply with these expectations, may focus on doing small, measurable good, while losing sight of the big, ambitious hard-to-measure good that lies at the heart of our missions. How do you measure the improvement art makes in someone’s life? What metric captures the value of an understanding of history? Largely, in the past, we couldn’t measure things like this, and didn’t try. Even in fields like medicine it is rare to find the kinds of large scale, long-term longitudinal research projects that can tease out small and subtle effects of lifestyle and behavior. Museums have never had the cultural equivalent of the Framingham Heart Study or the Nurses’ Health Study, following thousands of individuals over the course of decades, generating the masses of granular data needed to support such analysis. Instead researchers try to get at these questions in bits and pieces (measuring the effect of field trips, or the personal value of museum engagement), but the results are generally limited and hard to generalize.
Now there is an alternative to traditional longitudinal studies like Framingham. The combination of the Internet of Things (which tracks and measures so much of what we do), the Quantified Self movement (mainstreaming individual collection and analysis of minute details of everyday life), and Big Data Analytics could give us the ability to assess the impact of museum engagement on health, happiness, educational attainment, well-being and other measures of success.
People are already envisioning how big data can transform health care. Doctors and health care advocates envision a future in which the internet-connected things in your life—your fridge, scale, activity monitor band, medicine cabinet—communicate with your health provider to provide seamless integration of care. Besides giving individuals a “big picture” look at how their own behavior, diet and environment affect their personal health, this network would create huge databases, supporting analysis that would greatly increase the speed and power of identifying the overall risks and benefits of specific foods, behaviors or environmental exposure. It took decades to make an overwhelming case for the dangers of cigarette smoking. Despite the huge sums the tobacco lobby is spending to defend the next system for delivering nicotine, it may take far less time to quantify the first and second-hand risks of vaping (inhaling vapor from electronic cigarettes).
Educators, technologists and reformers are already envisioning how big data can transform education. The IBM PETALS project (Personalized Education Through Analytics on Learning Systems) is using machine learning and advanced data analytics to identify the individual learning needs of students and recommend personalized learning pathways. Khan Academy is using data gleaned from its thousands of student learners not only to provide feedback to teachers on specific students, but also to identify patterns in how students learn, and what kinds of pedagogy work best with what kinds of learners. Some researchers, and reformers, want to link children’s health and school records to identify factors that cross the home/school/community boundaries to affect children’s ability to thrive. For example, linking hospital records with education records to assess the correlation between smoking during pregnancy and ADHD, or impact of concussions on educational outcomes, or how children with a diagnosis of autism fare in the special education system.
What if we added cultural engagement to the linked data sets of health and education? If we track how people—children or adults—Interact with museums, historic sites, libraries, performing arts, and put that in the big data mix, we could finally document the effects of, say, family museum visits on kids’ educational attainment, or the impact of engagement with the arts on health and well-being.
The biggest challenge to this “holy grail” of museum metrics isn’t technological—it’s cultural. The kind of blanket surveillance that enables us to collect this level of detail is frankly, freaking people out, and leading to a backlash of concern about personal privacy. Do you really want your toothbrush ratting you out to your dentist? While you may feel better if your mom’s pillbox emails you if she doesn’t take her meds, do you want your pillbox emailing your kids? Do we want our museum logging when we visit, and how long we stay? (Well, maybe with appropriate incentives, we do.)
If we as a society ever do decide the potential benefits arising from mass collection of personal data outweigh our concerns, it may be with regard to our children. We already accept limits to kids privacy and autonomy in the interests of ensuring their health and safety, limits that we would not accept for adults. So I’m waiting for the first city to propose the trifecta of big data on children, merging health, education and cultural data to find out what really fosters happy, healthy, successful kids. Let me know if you see a movement toward this starting in your community…
One thought on “Big Data and the Holy Grail of Museum Metrics”
Great post! Big data can truly disrupt the museum experience. Being aware of the the museum audiences' likes and interests can help a great deal in improving museum layouts and exhibit locations. Based on how much time a visitor spends in front of an art piece, he/she can be sent related text/rich media with more information on the exhibit, similar artefacts in the museum shops etc. Here's a good post on how this can be done: http://bit.ly/1FHBNSH