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MUSEUM EXAMPLES
The SEATTLE ART MUSEUM’s installation
Mirror, by Doug Aitken, uses responsive
editing software that tracks weather, traffic
and atmospheric conditions and renders
them as images projected onto 12 stories of
the museum’s façade, pulling from hundreds
of hours of footage Aiken filmed around the
museum, city and state. The pixels in the logo
on the webpage of the NEVADA MUSEUM
OF ART change color throughout the day and
the seasons, taking on hues determined by
the previous hour’s temperature information
in Reno. This dynamic image, driven by environmental
monitoring, gives form to data that
pertains to the museum’s Art + Environmentoriented
identity.
Some museums are already using data
analytics to hone their operations. HISTORY
COLORADO and the POINT DEFIANCE
ZOO & AQUARIUM are both working
with IBM partner organization Bright Star
Partners to capture visitor-related data from
point-of-sale systems (admissions, store,
food service) and analyze it in real time.
This data enables the organizations to make
efficient decisions about staffing and use of
space, and tailor their membership programs,
pricing and communications to the demographics
and behavior of their audience. In
the near future, the zoo intends to enlist the
Near Field Communication capabilities of
smartphones to encourage visitors to “check
in” as they move through the grounds, which
will help managers assess the popularity and
dwell time of particular exhibits. The DALLAS
MUSEUM OF ART uses Chartio for real-time
analytics of patterns of membership sign-up
and visitor use of the museum.
As data becomes more valuable, it becomes,
in effect, a kind of currency. Even museums
have cottoned on to this: early last year the
DALLAS MUSEUM OF ART introduced a
membership model that invites visitors to trade
personal data for a “free” basic membership.
The DMA’s membership structure is designed
to capture as many people and as much data as
possible. The information they collect includes
Zip-plus-four, which they can cross-reference
Museums Might Want to…
Assess the analytic potential of the data sets
we are making freely accessible over the Web.
What can museums do with digital data that we
can’t do with the objects the data represents?
What value can be created using large-scale
analytics, and how do we encourage researchers
to ask interesting and appropriate questions
that can be answered with our data sets? We are
just beginning to explore the value of big data
in the humanities. If museums don’t start
data mining to extract the value of their own
resources, other more tech-savvy organizations
will.
Join the growing number of organizations that
are cooperatively pooling large data sets, allowing
cross mining—a form of sharing sometimes
called “data philanthropy.” Esri, for example,
has launched ArcGIS, a “social networking hub
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