260 likes | 470 Views
Study on VGI Volunteers. Rupa Tiwari, 12/02/2010. Outline. Introduction Problem Motivation Problem Statement Related Work Contribution Validation Challenges Findings Future work. Volunteered Geographic Information (VGI).
E N D
Study on VGI Volunteers Rupa Tiwari, 12/02/2010
Outline • Introduction • Problem Motivation • Problem Statement • Related Work • Contribution • Validation • Challenges • Findings • Future work
Volunteered Geographic Information (VGI) The harnessing of tools to create, assemble, and disseminate geographic data provided voluntarily by individuals (Goodchild, 2007). E.g. Wikimapia, Flickr, OpenStreetMap, Cyclopath OpenStreetMap portion of UMN east bank
Problem Motivation • The pool of volunteers is either increasing at a slower rate or decreasing. [Independent Sector, 2001] • Problems in volunteer’s retention to an organization [Bussell & Forbes 2002]. The solution to this problem would help in designing future VGI projects in better and appealing way and would answer the need for new volunteers and retention of existing ones. • This problem is applicable to all the projects and initiatives involving detailed locations update, urban and regional development to under-served developing communities, environmental analysis enhancement and fostering economic as well as community development.
Why is the Problem Interesting? • Volunteers contribute to the breadth and effectiveness of services [Hiatt & Jones 1998]. Thus apart from their contribution to the growth and welfare of geowiki sites, they should be considered as an essential human resource for many organizations, dealing with geospatial information and services. • VGI has proved to be a boon in managing disasters. Volunteers from various VGI organizations have contributed significantly during natural disasters like hurricane Katrina, Haiti and Chile earthquakes.
Problem Statement Given: • A set S, of VGI organizations, P1, P2 …Pn. • Sets of spatial volunteers, V1, V2 …Vn from the projects, P1, P2 …Pn respectively. Find: • A ranked list L, of motivation factors behind the volunteerism activity of volunteers. • Qualitative study of volunteer demographics Objective: • To find a statistically meaningful list of volunteer motivation factors ranked relatively for the VGI organization under consideration. This would help in understanding the dynamics of volunteer psychology. Example: • Volunteers of OpenStreetMap – a geowiki site form a candidate volunteer set.
Related Work Citizens as sensors: the world of volunteered geography by M.F. Goodchild, 2007 This geojournal summarizes few factors underlying VGI volunteerism, like: “Self-promotion” (for non-anonymous projects only) “convenient way of making it available to friends and relations” and “Personal satisfaction” (for OpenStreetMap only). Limitation: It is unclear as how the motivational factors have been arrived upon. Probably the outcomes are influenced by volunteer communities of Citizen Science projects like Christmas Bird Count and Project Globe. There is no mention of any kind of experimental approach backing up the findings. • The Motivations to Volunteer: Theoretical and Practical Considerations by Clary, E. Gil and Mark Snyder, 1999 • The authors applied functionalist theory and hypothesized following 6 personal and social functions: • Values (like humanitarianism) • Understanding (learning unused worldly skills) • Enhancement (growing psychologically) • Career (gaining career-related experience) • Social (strengthening relationships) • Protective (reduce personal problems) • Limitations: • The volunteer subjects on whom they worked were general social volunteers of unpaid helping activities. • We have come 11 years down the line. Changes in economic situation, availability of information and technology at volunteer’s disposal have resulted changes in motivational factors.
Contribution • Factors and the rank concluded from Survey Results • More factors and Qualitative Analysis as compared to 3 and 6 from related work • Statistical Ranking of the Factors • “Personal Satisfaction” matches with Goodchild • This study has new factors like to “Building Professional Network”, “Better Time Utilization” and “To Look for New Employment” etc in comparison to Prof. Snyder’s work. • Based on the survey responses, suggestions for improvements of VGI projects have also been included
Challenges • During the study, access to the volunteers of only two organizations OpenStreetMap and GISCorps was achieved. Hence the results and conclusions are based only on volunteers from both organizations. • Responses to the primarily important question of why people volunteer were collected in terms of 5-point likert scale. Likert scales are subject to distortion from several causes like central tendency biasof participants and social desirability bias. These two biases are constraints to this work. • Inferring Human Psychology is Non-trivial
Sample Details • GISCorps • Started October 2003, Atlanta, Georgia • Highly specialized GIS expertise to underprivileged communities • Strengthens local capacity by effective use of spatial information technologies • Develops web-based interactive mapping applications • Assists in strategic planning of GIS systems and their implementation. • E.g. : Created an accurate base map for northwest Albania, developed several data layers including a detailed road network (on Open Street Map – OSM interface), damaged buildings, and various Points of Interests. • OpenStreetMap • Started July 2004 by Steve Coast • Free editable map of the whole world • Allows viewing, editing and using geographical data in a collaborative way from anywhere on Earth • The project was started because most of the available maps had legal or technical restrictions on their use, holding back people from using them in creative, productive, or unexpected ways • Registered users can upload GPS track logs and edit the vector data using the given editing tools. • E.g.: During Haiti earthquake, OpenStreetMap used available satellite imagery to map the roads, buildings and refugee camps of Port-au-Prince. • 134 out of 150 deployed GISCorps and 118 OpenStreetMap volunteers
Participant Location Major participants from USA, followed by Germany, UK & France
Clustered Representation • Shades of green represent strong agreement, yellow signifies moderate agreement and pink and red symbolize disagreement • A clear trend being displayed from left to right, this made the ranking easy
Findings Ranked list table of the motivational factors: Other factors as indicated my 5% of the survey participants were reasons like adventure,fun of working on new projects,fordemonstrating the benefits of spatial information technology during disaster situationsandimproving the use of geospatial techniques in local governments.
Gender Relatively low Female participation with 37% in GISCorps and only 4% in OpenStreetMap
Age All age groups contribute, predominant being those between 20-50 years. OpenstreetMap seems to consist of younger lot of volunteers; the small fraction consisting of below 20 years of age is solely due to OpenStreetMap.
Occupation • Majority (64% in OSM and 83% in GISCorps) of the participants are professionals followed by students and academicians. • Others constitute people who are retired, unemployed or both professional and student at a time.
Relation with GIS GISCorps OSM Majority of GISCorps volunteer’s professional work and areas of study are related to GIS. While for OpenStreetMap the opposite holds, they volunteer as a hobby.
Volunteering Frequency Specifically speaking 46% of GISCorps volunteers volunteer on an annual basis whereas 46% of the OSM volunteers do so, on a weekly basis.
Volunteering Duration Around 69% of volunteers have been contributing for years or more.
Desire for Geospatial Training 55% of volunteers would undergo geospatial training only if it were free
Participation Incentive • More than half of them do not need any incentive • A considerable portion desired technical training, followed by award, honor and recognition • No wonder we have personal satisfaction, altruism and desire to gain geo-spatial knowledge as the top factors.
Non-statistical Inferences • Need for a Centralized Online Community for Volunteers • Insufficiency of Resources and Infrastructure • Ways to attract new volunteers: • Publicity through media • Ease of contributing • Easy documentation • Appreciation of Contribution • Encouragement from employers • Better organization among volunteers
Future Work • Study other VGI organizations • Factors based on Gender and other demographics • Target rich sample size • Study varied geographies, stress on continents which showed less participation like Asia
Thank You Any Questions?