Making molehills out of mountains: Crowdsourcing digital access to natural history collections Laurence Livermore, John Tweddle, Lisa French, Lucy Robinson, Sarah Phillips and Vincent S. Smith

Link to full report in Google Docs: Note: This is the working version of the report and will contain comments, notes and rough edges!

Background Dual Digital Collections Programme and SYNTHESYS3 report Audience - SYNTHESYS3 Taxonomic Access Facilities and internal NHM Aims: –Review current natural history crowdsourcing platforms; –Provide case studies of natural history crowdsourcing projects; –Summarise motivation of volunteers; –Recommend strategies for crowdsourcing success and future crowdsourcing research.

Crowdsourcing Definition & Context Crowd-based activity Clear task and goal Crowd is rewarded Distinct crowdsourcer (e.g. the NHM) Benefits the crowdsourcer Online and open participatory process Tasks and goals: Majority are transcription based (labels, registers or diaries) Tasks are well-suited for human intelligence (handwriting interpretation and data categorisation)

Crowdsourcing Platforms

Platform Comparison TC Data Entrysingle multi single ReviewYYNNY Open sourceYNNY? MobilePartialNNNN PM + AdminYN?NY Georef toolYNNN? Projects23218** Community , Contributions128,135145,5741,365,2001,025,033? Plat. Age4 years7 years3 years2 years Statistics gathered on 08/01/2014 unless other stated in notes Platform age is rounded up

NHM Case Studies – Science Uncovered 3 weeks to make prototype (1 dev) AngularJS, nodeJS, MongoDB (open source) Images from Flickr Live imaging on the night Showcased entire digitisation process from collection to Data Portal Dataset: Stats: collection/resource/07555c45-ed3f a4- dfa0144e35d2?view_id=59d600c ad-8435-a408f724f246http://data.nhm.ac.uk/dataset/crowdsourcing-the- collection/resource/07555c45-ed3f a4- dfa0144e35d2?view_id=59d600c ad-8435-a408f724f246 Demo available from:

NHM Case Studies – Notes from Nature Led by Tim Conyers and Robert Prys-Jones Bird register project – initial test project for NfN 2,950 pages 315,785 transcriptions 75% of transcriptions by 1 volunteer! Project page: Contributor stats: nature/resource/7f8fc5f5-90ae-4959-b286- 9cb7951f2875?view_id=ce329dfd-99cb-4223-b615-ce95d6c707c7http://data.nhm.ac.uk/dataset/notes-from- nature/resource/7f8fc5f5-90ae-4959-b286- 9cb7951f2875?view_id=ce329dfd-99cb-4223-b615-ce95d6c707c7

Collaboration with Oxford, Leicester, Royal Society, RCS Project that will help to advance and inform NHM crowdsourcing Developing two new projects on Zooniverse platform (Spring 2015): 1.Images of nature within C19 th periodicals (BHL) – CAHR & Leicester 2.Orchid phenology – AMC, Origins & Evolution Initiative & Oxford

Motivating the Crowd Understanding why volunteers participate in crowdsourcing endeavours and how to support, maintain and reward their involvement is central to success Narrative, tasks, supporting resources & feedback all affect participation Social aspects of crowdsourcing are critical and should not be ignored Motivations of participants vary and can be hard to determine Increasing number of studies, but biased coverage Report synthesises available evidence and relates this to effective project design

Initial decision to participate: –Enthusiasm and interest in project topic –Desire to record, find and discover –Learning and development of new skills –Contribution to the greater good (society/science) –Sense of purpose and belonging to a community (social) Maintaining volunteer participation (reward mechanisms): –Rapid feedback –Discussion with scientists and other contributors (forums) –Opportunity to develop skills and project responsibility (e.g. transcription to verification) –Acknowledging contributions made –Gamification (stats, leaderboards and badges)

Report conclusions: Benefits of Crowdsourcing A stronger online presence/brand Increased rate of collections digitisation, hence access to data Higher scientific output An effective way of engaging (dispersed) members of the public Deeper and more meaningful engagement with our collections

Report conclusions: project choice and design Clear project rationale with both cultural and scientific benefits Projects should be actively promoted and monitored Scientists should be visible and engaged with volunteers Develop best practice for motivating and retaining volunteers (self- establishing community structure and forum, good science, tasks of interest, different rewards etc) Platform should use existing data standards – reduce bottle neck for collections management ingestion Resulting data should be freely available – projects do not end when all tasks are complete!

Recommended Areas of Organisational Investment Technical infrastructure (e.g. software, hardware and developers) Communication, outreach and support (e.g. dedicated staff time to develop and provide feedback to an external community, internal project manager and scientists) Strategic project selection (e.g. strong narrative, potential scientific outputs, public appeal, well-structured tasks of known complexity) Preparation of underlying data (e.g. data for autocomplete fields such as collector names or localities) Post-processing of data and subsequent import into institutional collections management system

Next steps? Discussion… Investigate platforms and differentiators (technical, sustainability, control) Consider options for implementation Create list of potential projects Funding potential What is the future of crowdsourcing? Can the “crowd” perform research- orientated activities?