Jennifer Wexler – Digital Research Project Producer (British Museum), Daniel Pett - Fitzwilliam Museum, and Chiara Bonacchi – Lecturer in Heritage (University of Stirling)
This session will look at how we can use digital technology to democratise access to archaeological and museum collections, as well as increase public awareness and knowledge of these collections using innovative tools such as 3D modelling and AR/VR experiences.
3. Big Question?
How can we use digital technology
to democratise access to
archaeological & museum
collections?
4. What’s the Problem?
Representation in
cultural participation.
Lower income, lower education
and ethnic minority groups in
the UK and US are under-
represented at state-funded
museums and galleries.
Despite policies granting free
entrance to state-funded
museums and galleries in the UK
& an increasingly ethically and
culturally diverse population in
the US. (Neelands et al., 2015;
Blackwood & Purcell, 2014)
5. Measuring cultural participation
But there is a tendency to focus on actual foot-fall at museums, eg.
museum visitation as the only form of active public participation
Hall, 1999; Li et al., 2003; Warde et al., 2003
6. What happens when engagement
with museum and archive
content/materials is conducted in
the private space of the home or
the office, thanks to the digital
applications such as
crowdsourcing, 3D Modelling,
AR/VR/Immersive Experiences?
Does this make participation
more diverse or democratic?
7. It all started with…
Collaboration(s) between citizens ‘inside’ and ‘outside’ heritage institutions to study the
human past. Citizen Archaeology.
10. Transcription of NBAI
National Bronze Age Index (NBAI), an archive of 30,000 object cards of prehistoric metal
objects found in the UK between 1800 and 1983.
Crowdsourcing template for NBAI transcription.
13. Metalwork into meaning: Towards a ‘total’ dataset
Bronze Age Index Card data Portable Antiquities Scheme data
Middle & Late Bronze Age palstave axe data:
14. Developments in Bronze Age Studies
• Integrating: New and old datasets are finally being
combined and providing exciting new avenues for
future research
• Communicating: New ways for museum
professionals to communicate with the public,
breaking down existing barriers
• Building: Macro scales from micro steps; new
digital content from the catalyst of public interest in
new discoveries
17. Public Engagement & Social Media
Part of the appeal (of the transcriptions) for me is seeing how the
original authors put a little bit of themselves into their record
cards, and obviously took pride in analyzing and recording the
artefacts. I'm just completing a card now in which the patina is
described as ‘Beautiful apple green’. (MicroPasts Contributor, MicroPasts
Forum: http://community.micropasts.org/t/just-a-silly-thought/140/5).
18. Motivations
Motivation category Example
Learning about history and
archaeology
An interesting way to learn a bit more about
history & archaeology.
Giving back to / connecting with an
institution
Assisting the British museum as a thank you for
visiting out metal detecting club (Trowbridge)
Interest and curiosity I am a Celtic Artist with a degree in
Anthropology, and I find the work interesting.
Skill building or career development Experience for a future career in Ancient
History and Archaeology, as I am currently
studying a part-time BA (Hons) degree in
Classical Studies. I am also between modules at
the moment, so I have the time to dedicate to
this project.
Enjoyment It’s oddly relaxing
Helping out Helping a project
Contributing to knowledge
production
To help contribute towards greater scientific
knowledge
Identity and self-definition Ancestors were English and Scottish (and
American Indian).
19. Representation
Relatively high levels of formal
education:
• almost all participants have either
a university degree or a post-
graduate degree.
• 88% were either in employment
or retired, with
• 21% composed of students,
unemployed or stay-at-home
participants.
These findings are in line with the
results of cross-sectional evaluations
of other heritage crowdsourcing
projects (Causer and Wallace, 2012;
Eccles and Greg, 2014).
Geographic spread of participants, based on Google Analytics data.