This year MCN will focus on how museums can use technology to innovate and emphasize transparency, individual action, and institutional bravery. (from the MCN2017 call for proposals)
Get your hands on datasets, text-mining, data-mining, dataviz tools and tricks. A #MCN50/#MCN2017 data hackathon for museum technologists @MuseumCN.
- a half-day hackathon before the conference
- a follow-up session during the conference to present the results
in others category
This is a hands-on data crunching session.
This isn't a workshop (there isn't one workshop leader, each participant is bringing and learning something) but it rather takes the shape of a hackathon where all participants share tips and techniques and produce a few stunning presentations by the end of the day.
Some results will be presented in a session during the conference.
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Evaluation => What can your data tell you about your visitors and your collection? How can this feed your digital strategy?
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Data-led storytelling => Can data help you decide where to focus your interpretation efforts?
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Data-backed storytelling => How can data not lead but strengthen and support your narratives?
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Accessibility => How can you increase accessibility with big data and machine learning? (eg. reducing costs of translations)
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Strategy/etc => What do you get from "opening" your collection? Feedback from institutions that have just done it.
One of the principles of data science is that it has to be reproducible. So, one outcome could be to share a repository of tools on GitHub. A data toolkit that can be applied to "any" museum dataset.
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Hackathon from 1:00 PM to 5:00 PM Tuesday, November 07, 2017, at CMP_studio IMPORTANT : as the Carnegie Museums of Art and Natural History are closed on Tuesdays, please confirm to get access to CMP Studio
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Presentation of the results from 11:30 AM to 12:30 PM Friday, November 10, 2017 at #MCN2017.
- a series of short lightning talks where participants present tools or techniques they use, and how they use them, to feed the discussion
- participants/groups choose to apply some of these tools and techniques to a dataset
2 profiles:
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people at ease with programming and hacking code, be it with Java, Python, R, and/or dataviz techniques
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people who can bring a large dataset and are curious to explore it in a different way (eg. a collection of publications, labels, audio guide scripts etc.)
- Seema Rao : on setting goals when working with data
- Christophe Buffet : on using Java or R for text-mining
- Jeff Steward : on Harvard Art Museums’ statistical landscapes (see Suns Explorer, Collection Activity, Collection Terrains)
- Chad Weinard : on releasing The Williams College Museum of Art collection data (see New Dimensions for Collections at WCMA)
- Jeffrey Inscho and the CMP_studio space/team
- Elena Villaespesa : on the evaluation of open access at the Met
- MCN’s Data and Insights SIG
- many more people from the MCN community and outsiders
- CMOA
- WCMA
- The Met
- Cooper-Hewitt
- MoMA
- MoMA's exhibition and staff histories
- Tate
- ACMI
- ACMI Historic Film Screening Data
- Yale Center for British Art IIIF top-level collection
- Museum für Kunst und Gewerbe Hamburg
- others can be added to this list, cf. gitMuseum
- API Harvard Art Museums
- API Collection of Cooper Hewitt, Smithsonian Design Museum
- Brooklyn Museum Opencollection API
- Collection API - Science Museum Group
- Rijksmuseum API
- Walters Art Museum Collections API
- Statens Museum for Kunst
- Europeana APIs (Europeana currently offers four APIs)
- and many more
- CHECK if there is a collection API for the Barnes? Barnes Foundation
- MCN-L archive
- twitter hashtags such as #musetech, #mtogo, #MCN2017
- twitter handles such as @MuseumCN
- papers eg. MW papers
- conference programs
- conference participants lists
- conference presentations slides or transcriptions
- websites eg. MCN
- emails
- etc.
- Cool stuff made with cultural heritage APIs - A very big list of projects using using open data and cultural heritage APIs
- FiveThirtyEight's view on The Met's collection: An Excavation Of One Of The World’s Greatest Art Collections by Oliver Roeder
- FiveThirtyEight's view on MoMA's collection: A Nerd’s Guide To The 2,229 Paintings At MoMA by Oliver Roeder
- 120kMoMA - A data visualization study of The Museum of Modern Art collection dataset of 123,919 records by Helen D. Wall
- 120kMoMA peak years — A data visualization study of years information in The Museum of Modern Art Collection dataset by Helen D. Wall
- TateData peak years — A data visualization study of years information in The Tate Collection dataset and a comparison with the MoMA Collection by Helen D. Wall
- MoMA Exhibition Spelunker by Good, Form & Spectacle
- about Jeff Steward’s “Suns Explorer” for Harvard Art Museums: When big data meets art appreciation
- Data Visualization Workshop Series at NCSU Libraries
- Dear Data
- Merete Sanderhoff — Open access can never be bad news
- Merete Sanderhoff — Your imagination is the only limit
- George Oates — on the MoMA Exhibition Spelunker
- Giorgia Lupi — Dear Data has been acquired by MoMA, but this isn’t what we are most excited about.
- Elina Sairanen — What Does Data Have to Do with It?
- Keir Winesmith and Anna Carey — Why Build an API for a Museum Collection?
- Chad Weinard — New Dimensions for Collections at WCMA
- Shelley Bernstein - Open Access at the Barnes