mia ridge

NITLE ‘Crowdsourcing’ seminar

mia — Fri, 03 May 2013 14:00:54 +0000

Discussion Guide for NITLE Crowdsourcing seminar

Wednesday, May 8, 2013, 1-2 pm EDT, online via NITLE’s desktop videoconferencing platform

Slides (8mb PDF).

Discussion Questions

Have you ever participated in a crowdsourced project? What did you enjoy about it? Were you motivated to continue? Why/why not?
How well do the tasks presented in the seminar and represented in the ‘Suggested Projects’ below match your students’ interests, knowledge and skills? Can you find projects that are a closer match?
What else is required for undergraduate participation in crowdsourced projects to help meet liberal education learning outcomes?
If crowdsourced projects are designed to meet intrinsic or altruistic motivations for voluntary participation, what are the ethical and practical implications of asking students to participate?
What are some of the challenges of collaboration, credit and attribution in scholarly crowdsourcing, and how might you start to resolve them in your work with students?

Suggested Projects

Depending on your interests, visit one or more of the following:
- OCR error correction for users of the National Library of Australia’s online newspaper collection, Trove: http://trove.nla.gov.au/
- Citizen science project GalaxyZoo http://www.galaxyzoo.org/ and ZooTeach ‘Where educators can share high quality lesson plans & resources that compliment the Zooniverse citizen science projects’ http://www.zooteach.org/age/16%20to%2019+
- Many other citizen projects are available on the Zooniverse site https://www.zooniverse.org/ or citizen science portals like http://scistarter.com/.
- Art tagging and identification project Your Paintings Tagger http://tagger.thepcf.org.uk/
- Brooklyn Museum’s Tag! You’re It art tagging game http://www.brooklynmuseum.org/opencollection/tag_game/start.php
Review and compare projects for transcribing historic records: OldWeather http://www.oldweather.org/ and What’s on the Menu http://menus.nypl.org/. What differences did you notice, and what impact do they have on you as a potential transcriber?
Try transcribing some records on Herbaria@home http://herbariaunited.org/atHome/ and Notes from Nature http://www.notesfromnature.org/. How easy was it to get started and complete a record in each project? Based on your experience, which types of users are the projects designed for?

Keynote: ‘A Brief History of Open Cultural Data’

mia — Sat, 13 Apr 2013 09:00:46 +0000

I was invited to give a talk (which seemed to turn into a plenary then a keynote along the way) for the GLAM-Wiki 2013 conference. I thought it might be useful to put current discussions around opening cultural data for use on Wikipedia and other projects that require content to be licensed for re-use in context (for the museum, library and archive professionals in the audience) and some of the contradictory instructions issued to institutions with cultural, scientific or historical content (for the Wikipedians in the audience, though of course there was a huge overlap between those groups).

I’ve blogged my talk notes as ‘An (even briefer) history of open cultural data‘ at GLAM-Wiki 2013 at Open Objects or there’s a video of my talk.

Paper: ‘A thousand readers are wanted, and confidently asked for’: public participation as engagement in the arts and humanities

mia — Tue, 09 Apr 2013 13:00:56 +0000

I was invited to give a paper on my research at Digital Impacts: Crowdsourcing in the Arts and Humanities, convened by Kathryn Eccles and the Oxford Internet Institute.

I’ve also posted Notes from ‘Crowdsourcing in the Arts and Humanities’ on Open Objects.

(My title comes from the Oxford English Dictionary’s 1879 call for contributors to help them get through their backlog of words that needed sources and definitions. Yes, I do spend a bit too much time thinking about Victorian precursors to modern crowdsourcing.)

Workshop: Data visualisation as a gateway to programming

mia — Sat, 16 Mar 2013 09:30:37 +0000

I was invited to run a workshop at THATCamp Feminisms West at Scripps College in Claremont, California, and thought ‘Data visualisations as gateway to programming’ would be a good way to provide a gentle introduction to ‘computational thinking’ by working through the effects different data structures have on potential visualisations in ManyEyes, the online visualisation tool. I also prepared some material on basic concepts in programming and put together a page of ‘Inspiring women through history’ mapped across time and space that contained heavily commented code that suggested various things to try to get a sense of how code (in this case, JavaScript, HTML, CSS) works. My slides are below, you can play with content prepared for ManyEyes, or ‘view source’ at the ‘inspiring women’ link above, save the file to your hard drive and have a play.

Data visualisations as a gateway to programming from Mia

Conference paper: New Challenges in Digital History: Sharing Women’s History on Wikipedia

mia — Mon, 11 Mar 2013 13:06:33 +0000

I’ll be presenting ‘New Challenges in Digital History: Sharing Women’s History on Wikipedia’ in the ‘Developments in Digital Women’s History’ strand of the Women’s History in the Digital World conference at The Albert M. Greenfield Digital Center for the History of Women’s Education at Bryn Mawr on March 23, 2013.

Abstract:

In 1908 Ina von Grumbkow undertook an expedition to Iceland. She later made significant contributions to the field of natural history and wrote several books but other than passing references online and a mention on her husband’s Wikipedia page, her story is only available to those with access to sources like the ‘Earth Sciences History’ journal.

Cumulative centuries of archival and theoretical work have been spent recovering women’s histories, yet much of this inspiring scholarship is invisible outside academia. Inspired by research into the use and creation of digital resources and the wider impact of these resources on historians and their scholarship, this paper is a deliberate provocation: if we believe the subjects of our research are important, then we should ensure they are represented on freely available encyclopaedic sites like Wikipedia.

Wikipedia is the fifth most visited website in the world and the first port of call for most students and the public, yet women’s history is poorly represented. This paper discusses how the difficulties of adding women’s histories to Wikipedia exemplify some of the new challenges and opportunities of digital history and the ways in which it blurs the line between public history and purely academic research.

Update: I’ve posted my talk notes at New challenges in digital history: sharing women’s history on Wikipedia – my draft talk notes.

Paper: Where next for open cultural data in museums?

mia — Sat, 02 Mar 2013 15:26:41 +0000

My latest article for Museum Identity magazine, Where next for open cultural data in museums?, is now live online and in the current print issue of Museum-iD 13.

Site abstract: “Museums have increasingly been joining the global movement for open data by opening up their databases, sharing their images and releasing their knowledge. Mia Ridge presents a brief history of open cultural data projects, explores some reasons why some data is relatively under-used and looks to the future of open cultural data”.

Keynote: ‘The gift that gives twice: crowdsourcing as productive engagement with cultural heritage’

mia — Fri, 01 Feb 2013 09:30:18 +0000

I was invited to give a keynote at ‘The Shape of Things: New and emerging technology-enabled models of participation through VGC‘ at the School of Museum Studies, University of Leicester. This was the first event for the AHRC-funded iSay: Visitor-Generated Content in Heritage Institutions project.

My slides are below and I’ve blogged Notes from ‘The Shape of Things: New and emerging technology-enabled models of participation through VGC’. I’ve also saved an archive of isayevent_tweets_2013_02_01 (CSV).

Crowdsourcing as productive engagement with cultural heritage from Mia

Resources for ‘Crowdsourcing in Libraries, Museums and Cultural Heritage Institutions’

mia — Tue, 22 Jan 2013 19:40:57 +0000

A collection of links for further reading for the British Library’s Digital Scholarship course on ‘Crowdsourcing in Libraries, Museums and Cultural Heritage Institutions’.

Crowdsourcing projects discussed

Useful blogs

References

Alam, Sultana Lubna, and John Campbell. 2012. “Crowdsourcing Motivations in a Not-for-profit GLAM Context : the Australian Newspapers Digitisation Program.” ACIS 2012 : Location, Location, Location : Proceedings of the 23rd Australasian Conference on Information Systems 2012 (November 8): 1–11.
Clary, E. Gil, Mark Snyder, Robert D Ridge, John Copeland, Arthur A Stukas, Julie Haugen, and Peter Miene. 1998. “Understanding and Assessing the Motivations of Volunteers: a Functional Approach.” Journal of Personality and Social Psychology 74 (6) (June): 1516–30.
Dunn, Stuart, and Mark Hedges. 2012. Crowd-Sourcing Scoping Study: Engaging the Crowd with Humanities Research. London.
Holley, Rose. 2010. ‘Crowdsourcing: How and Why Should Libraries Do It?’ D-Lib Magazine.
Howe, Jeff. 2006, ‘The Rise of Crowdsourcing’, Wired.
Oomen, Johan, and Lora Aroyo. 2011. “Crowdsourcing in the Cultural Heritage Domain: Opportunities and Challenges.” In 5th International Conference on Communities and Technologies, Queensland University of Technology, Brisbane, Australia. Vol. 29.
Ridge, Mia. 2011. Playing with Difficult Objects – Game Designs to Improve Museum Collections. In J. Trant and D. Bearman (eds). Museums and the Web 2011: Proceedings. Toronto: Archives & Museum Informatics.
Ridge, Mia. 2012. Frequently Asked Questions about crowdsourcing in cultural heritage, Open Objects
Shirky, Clay. (2011). Cognitive surplus: creativity and generosity in a connected age. London, Penguin.
Terras, M (2009) Digital Curiosities: Resource Creation Via Amateur Digitisation. Literary and Linguistic Computing , 25 (4) 425 – 438. 10.1093/llc/fqq019.
Trant, J. (2009) Tagging, Folksonomy and Art Museums: Results of steve.museum’s Research. In: Archives & Museum Informatics: 2009.
http://conference.archimuse.com/files/trantSteveResearchReport2008.pdf

Resources for ‘Data Visualisation for Analysis in Scholarly Research’

mia — Sun, 20 Jan 2013 12:35:01 +0000

Woodcut, An anatomy of Daniel’s statue, 1585.

A collection of links for further reading for the British Library’s Digital Scholarship course on ‘Data Visualisation for Analysis in Scholarly Research’. I update this each time I teach the course, so please leave a comment if you know of any great sources I’ve missed. Slides and exercises for each version of the workshop are below. Many thanks to workshop participants for their feedback, as it directly helps make the next version more effective. And of course huge thanks to Nora McGregor and the British Library’s Digital Scholarship team!

Last updated 4 May 2013. Image: Woodcut of the statue described by the prophet Daniel, from Lorenz Faust’s Anatomia statuae Danielis (“An anatomy of Daniel’s statue”), 1585. In Alan Jacobs, History as wall art.

Sources cited and references to find out more

Histories of data visualisation

Milestones in the history of data visualisation
CABINET // A Timeline of Timelines
Brody, Howard, Michael Russell Rip, Peter Vinten-Johansen, Nigel Paneth, and Stephen Rachman. 2000. Map-making and myth-making in Broad Street: the London cholera epidemic, 1854. The Lancet 356, no. 9223: 64-68.
The Changing Goals of Data Visualization
Flow Map of Napoleon’s March on Moscow

Definitions of data visualisation

Few, Stephen. 2013. ‘Data Visualization for Human Perception’. Ed. Mads Soegaard and Rikke Friis Dam. The Encyclopedia of Human-Computer Interaction, 2nd Ed. Aarhus, Denmark: The Interaction Design Foundation.
Visualisation Workflow: Finding Stories and Telling Stories by Andy Kirk (also check out his blog, Visualising Data)
A Tale of Two Types of Visualization and Much Confusion
Information Visualization Manifesto, Manuel Lima

Types of visualisations

A Tour through the Visualization Zoo: A survey of powerful visualization techniques, from the obvious to the obscure, Jeffrey Heer, Michael Bostock, Vadim Ogievetsky
Chart and image gallery: 30+ free tools for data visualization and analysis provides a useful overview chart that can be sorted by skill level, platform, etc, with related reviews and screenshots. See also A Periodic Table of Visualization Methods, Brian Suda’s Top 20 data visualisation tools, or idea.org’s Great tools for data visualization.
Selected tools for visualisations, a curated selection from datavisualization.ch – recommended
Narrative Visualization: Telling Stories with Data, Edward Segel, Jeffrey Heer
Timelines: the London 2012 Olympic Games on Twitter, emoto (also an example of visualising sentiment analysis, where computational techniques are used to detect subjective emotions)
Timelines: Wellcome Library History of Genetics timeline
N-grams: Google Ngram viewer
N-grams: bookworm Open Library
Text mining for Historians
Topic mining: Mining for meanings, Tim Sherratt
Topic mining: Mining the Dispatch, Robert K. Nelson
Topic mining: Topic Modeling Tool
Network visualisations: Les Misérables character interaction presented as a force directed graph.
Network visualisations: O rocks! Tell it to us in plain images (A THATCamp/Bloomsday Visualization)
Infographics: The Fascinating World of (Good) Infographics (and some infographics on bad infographics)
Infographics: Ending the Infographic Plague, Megan McArdle
Infographics: We’ve Reached Peak Infographic, and We’re No Smarter for It, Dylan C. Lathrop
Visualising media: One million manga pages, Lev Manovich and “How to Compare One Million Images?” In David Berry, ed., Understanding Digital Humanities (Palgrave, 2012).

Planning and designing good data visualisations

How to Design an Excellent Chart is focused on charts for telling stories (rather than exploring to find new ones) and includes Andrew Abela’s ‘chart chooser’ diagram for showing distribution, composition, relationship or comparison data. See also Juice Lab’s interactive Chart Chooser.
Statistics glossary on Presenting data (for a refresher on ordinal, nominal, interval etc data)
Effective Graphs blog by Naomi Robbins (including some great ‘what not to do‘ examples)
Eenie, Meenie, Minie, Moe: Selecting the Right Graph for Your Message (PDF), Stephen Few
Information Display Tips, Connie Malamed (useful on ‘visually distinct objects’)
How to Avoid Designs that Split Attention, Connie Malamed
Information Visualization Framework, Manuel Lima
Make for Data Scientists and Introducing Drake, a kind of ‘make for data’ (getting a bit techie but useful for thinking about ways to manage different versions of your datasets as you clean and refine)

Data visualisation for scholarly research

See also the projects listed in the Exercises section below.

Modeling Networks and Scholarship with ORBIS, Elijah Meeks and Karl Grossner, Journal of Digital Humanities
Reading digital sources: a case study in ship’s logs or Keeping the words in Topic Models, Ben Schmidt (and his blog Sapping Attention on text mining and the digital humanities generally)
The Six Degrees of Francis Bacon project is blogging entertainingly about ‘reassembling the early modern social network’
HASTAC forum, Visualization Across Disciplines

Critiquing visualisations

On ‘big data’ as the next big trend: video from , or written interview with Crawford at Untangling algorithmic illusions from reality in big data.
In Liveblogged Review of Macroanalysis by Matthew L. Jockers, Part 2 Scott B. Weingart discusses choices and standards for visual representations of humanities data
Lattice Uncertainty Visualization: Understanding Machine Translation and Speech Recognition, Christopher Collins, Gerald Penn, Sheelagh Carpendale
Data visualizations should be as much about facilitating interaction as conveying information, Michael Schrage
Mia Ridge explores the shape of Cooper-Hewitt collections, me on ’messiness’ and humanities data in visualisations on the Cooper-Hewitt Museum Labs blog

General references

Data Visualization Talks Online, 2010 post from Alark Joshi listing various videos
Data and visualization blogs worth following (early 2012 post by Nathan Yau)
Few, Stephen. 2009. Now I See It: Simple Visualization Techniques for Quantitative Analysis. Analytics Press.
Lima, Manuel. 2011. Visual complexity: mapping patterns of information. New York: Princeton Architectural Press.
Moretti, Franco. 2005. Graphs, maps, trees: abstract models for a literary history. London: Verso.
Rosenberg, Daniel, and Grafton, Anthony. 2010. Cartographies of Time: A History of the Timeline. Princeton Architectural Press
Tufte, Edward R. 1983. The Visual Display of Quantitative Information. Graphics Press.
Tufte, Edward R. 2007. Beautiful evidence. Cheshire, Conn: Graphics press.
Ware, Colin. 2008. Visual Thinking for Design. Morgan Kaufmann.
Yau, Nathan. 2011. Visualize this: the FlowingData guide to design, visualization, and statistics. Indianapolis, Ind: Wiley Pub.

Links for exercises

January 2013 versions: Data Visualisation for Analysis in Scholarly Research slides and Datasets for playing

April 2013: Exercises for Data Visualisation for Analysis in Scholarly Research (PDF), Data Visualisation for Analysis in Scholarly Research_April2013_slideshandout (PDF), Inspiring Women through History_April2013 (Excel dataset).

My bio as a sample timeline and map in Neatline

Scholarly visualisations to explore and discuss

Trying entity recognition and data enhancement

I’ve suggested a few tools as they each have different strengths and weaknesses. If you don’t have any of your own text to hand, try a paragraph or two of text from a news website.

Stanford Natural Language Processing Group tool, ‘An integrated suite of natural language processing tools for English in Java, including tokenization, part-of-speech tagging, named entity recognition, parsing, and coreference’.
Voyant Tools, their principles and user guide
You can also try the entity recognition extension for Refine from freeyourmetadata.com

Cleaning data as preparation for visualisation

Download OpenRefine (was Google Refine) website
Free Your Metadata’s example of Cleaning metadata in Refine
A Librarian’s Guide to OpenRefine
A Wrangling Example With OpenRefine: Making “Oven Ready Data”
Data cleaning with DataWrangler

ACH Election Results Announced

mia — Mon, 10 Dec 2012 10:00:02 +0000

I am proud to share that I was elected to serve on the Executive Council of the Association for Computers and the Humanities (ACH) for the 2013-2016 term, alongside Brian Croxall, Jennifer Guiliano, and Ernesto Priego (2013).