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Dissertation proposal defense for a comparative case study of virtual citizen science projects, focusing on the concepts of virtuality, technology, organizing, participation, and outcomes....

Dissertation proposal defense for a comparative case study of virtual citizen science projects, focusing on the concepts of virtuality, technology, organizing, participation, and outcomes.

Successfully defended with no revisions on 5 May, 2010.

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Crowdsourcing Science Crowdsourcing Science Presentation Transcript

  • Crowdsourcing Science Organizing Virtual Participation  in Knowledge Production Andrea Wiggins 5 May, 2010
  • Citizen Science • Projects involving the public with scientists in  collaborative research – Diverse contributors, activities, and goals – Volunteers contribute data collection or reduction • Virtual citizen science – All public participation is ICT‐mediated
  • Motivation •What does it take to do science with  strangers on the Internet? – Man is still the most extraordinary computer of all.   ~John F. Kennedy – Many hands make light work.  ~John Heywood
  • Problem Statement • Creating effective technologies for virtual  participation requires understanding how  research design and implementation decisions  influence processes and outcomes in citizen  science. • Goal: support design and management of  citizen science cyberinfrastructure
  • Research Questions • RQ1: – How do virtuality and technology alter organizing in citizen science? • RQ2: – How do virtuality and technology shape participation in citizen science? • RQ3: – How do organizing and participation influence scientific outcomes in citizen science?
  • Concepts Discontinuities, continuities, & physicality Virtuality Watson‐Manheim, Chudoba & Crowston; Harrison & Dourish Technology Tools & routines for participation Process of creating order; goal‐oriented activity Organizing Cyert & March; Stinchcombe; Weick; Galbraith Participation Taking part Scientific  Formal knowledge production: papers, data sets Outcomes
  • Related Research • Public participation in science – Purposes and forms of engagement – Informal science education, policy, STS • Irwin, Bonney (et al, et al, et al) • Scientific collaboration – Broader context of practice • Sonnenwald, Finholt • Online communities – Participation in virtual environments • Crowston, Haythornthwaite, Preece & Shneiderman
  • Virtual Participation Process Model • Literature – Small group theory • Hackman, McGrath, Ilgen,  Hollenbeck, Guzzo & Dickson – Volunteerism • Pearce, Wilson, Cnaan &  Cascio, Sproull & Kiesler • Pilot study – Context – Processes
  • Pilot Study • Goals – Test theory & field research methods – Familiarity with context of practice  • Case study of a new citizen science project – Partnership for monitoring at National Parks – Phenology: the study of recurring plant and animal  life cycle stages, or phenophases
  • Northeast Phenology Monitoring • Organized virtually by diverse partners – Federal agencies, nonprofits, networks, academics – Different goals that rely on the same data – Coordinating via email & conference calls • Findings – Complex organizing in decentralized projects – Context shapes research design & implementation
  • Methodology • Comparative case study methodology – Complex sociotechnical phenomenon – Early stage of research – Explanatory process theory • Theoretical sampling – 2 ‐ 4 projects with different characteristics • Multiple data sources and analysis techniques
  • Research Design • Four overlapping phases – Data collection from June 2010 ‐ December 2010 – Data analysis from July 2010 ‐ July 2011
  • Field Research Data Collection • Interviews – Ethnographic, semi‐structured & informal – Project leaders & volunteers • Participant observation – Contribute as a volunteer – Observe volunteers & project leaders • Secondary data, documents & artifacts
  • Qualitative Analysis • Analysis concurrent with data collection – Flexible set of techniques • Within‐case analysis – Case descriptions & process analysis • Cross‐case analysis – Comparisons building on within‐case analysis • Validation – Auditor, participant review, expert panel
  • Theoretical Sampling Criteria RQ Concept Model Dimensions Input: environment spatial, temporal, physical Virtuality Input: technology task support, social support Technology Processes: organizing,  project development, research  Organizing research design, coordination Participation Processes: participation idealized, task, social Scientific  Outputs: knowledge,  research products, discovery,  Outcomes innovation new/revised approaches
  • Three Potential Cases Project Organization Tasks Spatial Temporal Physical Social IT Outcomes Multiple  GalaxyZoo academic PIs Reduction ✓ ✓ ✓ ✓ Great  Single  Sunflower  academic PI Collection ✓ ✓ ✓ ✓ Project 2 nonprofit  Collection,  eBird organizations analysis ✓ ✓ ✓ ✓
  • Great Sunflower Project • Collecting data on pollinator service (bees!) – Started in 2008 by a single academic researcher – Very successful in volunteer recruitment •2 weeks: 15K volunteers •1 year: 55K volunteers •2 years: 77K volunteers – Participation involves: •Planting sunflowers, 15‐minute observation samples •Online garden description & data entry on Drupal site
  • eBird • Collecting bird abundance and distribution data – Launched in 2002 by Cornell Lab of Ornithology  (with National Audubon Society) – Considered a “gold standard” by other projects •Currently: 1.5M ‐ 2M observations/month •2002 ‐ 2009: 21M observations, 35K users, 180K locations – Participation involves: •Choosing count method & recording bird observations •Entering observations and metadata online
  • Galaxy Zoo • Classifying images of galaxies – Started in 2007 by a team of academic astronomers – Instant success and exciting new discoveries •Galaxy Zoo 1, Year 1: 50M classifications, 150K volunteers •Galaxy Zoo 2, Year 2: 60M classifications in 14 months •Galaxy Zoo : Hubble, Year 3: Launched April 2010 – Participation involves: •Online visual classification tasks using a custom platform
  • Expected Contributions • Practical and theoretical – Citizen science •Empirical study •Theorizing practice – Virtual organizations •Extending theory – Cyberinfrastructure •Conceptualizing large‐scale collaboration
  • Summary • What – Comparative case study of virtual citizen science • How – Field research methods with qualitative analysis • Why – Provide context for technology design and  management in citizen science
  • Thanks! • www.ebird.org • www.galaxyzoo.org • www.greatsunflower.org • More: – www.scienceforcitizens.net – www.birds.cornell.edu/citscitoolkit/projects