encyclopedia-of-life

Possible Projects

** Encyclopedia of Life ** // Jenny Preece //Preece@umd.edu// & Cynthia Parr // [|parrc@si.edu]
 * Encyclopedia of Life: **, This ambitious project to create web pages for all 1.8M living species on the earth presents many challenges for the developers who expect highly participatory contributions (see [|http://www.eol.org]) . Their hope to integrate citizen scientists with professional scientists has generated tension, so finding strategies that enable such collaborations might be helpful to many other collaborative ventures. The volume of information for each species is potentially large with text, data, images, videos, messages from observers, references, etc. so searching across species, finding common attributes across species, etc. are all major technical challenges. Dozens of projects tied to the Encyclopedia of Life would span topics such as educational tools for environmental awareness for citizens, data for land use planners, focused conservation projects to help endangered species, scientific taxonomies, activities for K-16, etc. Each of these projects would require interdisciplinary teams of technically sophisticated implementers, scientists, and social scientists.

// The compelling national and international need // for this project cannot be stated too strongly. With hundreds of species disappearing daily due to habit loss and climate change, the US must focus on preserving its own flora and fauna and on leading the world in conversation efforts. EOL provides a unique opportunity to catalog the world’s species and educate citizens.

Uses cases serve both professional and citizen scientists. Ecologists can use EOL to accurately identify the organisms they are study; without such identifications, many areas of ecological study are compromised (Bortolus 2008). Moreover, ecological modelers need access to information about species to build models with stronger predictive power and more accuracy. For example, without easy-to-use and accessible information about species, plants may get treated as one group with single values for photosynthetic and growth rates in the model. Most biologists know that different types of plants can be physiologically different and, thus the model ideally should include separate parameters for each species. Public health and safety relies on the ecological study of harmful species such as toxin-producing algae that can cause shellfish poisonings (Hargraves and Maranda 2002).

The IUCN Red List (http://www.iucn.org) reports the conservation status of organisms based on the analysis and opinions of more than 7,000 experts. With a fully developed EOL and integrated datasets (species distributions, protected area coverages, maps of large-scale environmental threats), not only could the production of the Red List and Red Data Books be accelerated, the results could be translated into concrete recommendations for decision-makers. Conservation biologists pondering the causes of decline in a particular species will be able to obtain information from EOL about the morphology, ecology, and behavior of the target species, as well as the characteristics of its close phylogenetic relatives, its mutualists, pathogens, competitors, predators, or ecological equivalents. The comprehensive data collected, at least in part by citizen scientists and curated by scientists, and available at EOL will thus greatly improve the efficiency of comparative biodiversity analyses by providing instant access to rich contextual information about any species of plant, animal, fungus, or microbe.

Citizen scientists involved in Audubon Christmas Bird Counts, butterfly counts or Bioblitzes can take advantage of EOL's free online resources to better identify and understand the organisms they are discovering. A major part of EOLs vision is to support and spark new monitoring efforts in areas of the tree of life that haven't received attention before because of lack of visibility. For many organisms, and in many parts of the world, there are so few trained scientists and so little funding that otherwise fascinating and important creatures are overlooked in citizen science efforts.

The scientific value of non-scientist participation in biodiversity monitoring and identification continues to be debated and studied (Butcher et al. 1990, ). Much may depend on the nature of the effort -- monitoring easily recognized birds or trees (e.g. Holck 2008) may be very different than identifying difficult wildflowers or beetles (Abadie 2008, Majka & Bondrup-Nielsen 2006). For Encyclopedia of Life, the challenge lies not just in recruiting, training, and supporting non-scientists, but also in effectively engaging professional scientists in disseminate their knowledge online. The professional landscape itself is changing to be increasingly collaborative and digital (Hine 2008, Wheeler 2008), but these are early days. The core task of assembling basic background information about species online may be easier for citizen scientists than rigorous identification and monitoring, but will trained scientists also be willing and able to contribute and to provide guidance and review?

There are many //computer science research challenges//. Developing a huge multimedia database containing millions of records that can be searched and edited by scientists and citizens poses technical and user interaction design challenges. What kinds of visualizations and other sense-making techniques are needed to support users with different goals and scientific knowledge?

An //overarching research question// is what functionality, usability and sociability (i.e., software features and social support) are needed for a healthy EOL community comprising scientists and citizens of all ages? Some subquestions are: Related to all of these are the questions “how important are cooperation, competition, and trust in individual participation trajectories" and also "What are good ways to organize multiple participation opportunities?" EOL offers many opportunities to participate:
 * 1) What motivates participants to come to the site and read?
 * 2) What motives them to contribute?
 * 3) What motivates them to collaborate with others?
 * 4) What motivates them to become leaders?
 * 5) What keeps participants motivated and the community growing in the face of competing opportunities?

i) uploading photos ii) adding text iii) tagging, which may include "tag-fest events" iv) commenting v) rating vi) curating vii) mining text from scanned publications viii) proofing automatically mined text

Trying out different roll-out scenarios to see how they impact the reader-to-leader process would be interesting.

Of course for each question we need to establish a baseline:

How many people? How do these people move through the stages?

Then we can try different kinds of interventions, eg: Research methods Triangulating qualitative and quantitative data is promising. Possible techniques include:
 * software functionality/usability changes (e.g., introduce some kind of rating system)
 * introduce facilitators/moderators
 * ask a certain group of participants to frame their messages in a certain way (i.e., message conversation style)

Tricky issues: privacy and the need for demographic data, timing of project and development cycle, etc. Abadie J-C, Andrade C, Machon N, Porcher E. 2008 On the use of parataxonomy in biodiversity monitoring: a case study on wild Flora/ Bortolus, A. 2008. Error cascades in the biological sciences: the unwanted consequences of using bad taxonomy in ecology. Ambio 37(2):114-118.
 * interaction logging (analysis by examining no. of logins, contributions etc. over time, changes in social networks)
 * message content analysis (to elucidate underlying motivation in observed social network behavior)
 * interviews with selected participants (ditto above – and done as necessary)

Butcher, GS, Fuller MR, McAllistor LS, Geissler PH. 1990. [|An Evaluation of the Christmas Bird Count for Monitoring Population Trends of Selected Species]

[|Wildlife Society Bulletin],18 (2): 129-134. Hargraves, P. E. and L. Maranda. 2002. Potentially toxic or harmful microalgae from the northeast coast. Northeastern Naturalist 9(1):81-120. Hines, C. 2008. Systematics as cyberscience: Computers, change, and continuity in science. Cambridge, MA: MIT Press. Majka CG, Bondrup-Nielsen S (2006) Parataxonomy: a test case using beetles. Anim Biodivers Conserv 29:149–156 Wilson, Edward O. 2003. The encyclopedia of life. Trends in Ecology and Evolution 18, no. 2: 77-80. Available from [|http://www.sciencedirect.com/ science/article/B6VJ1-47C8RDN-3/2/befac60e32dd59e55ff8bfc75f9848c6]. ISSN 0169-5347, DOI: 10.1016/S0169-5347(02)00040-X. Balmford A, Bennun L, ten Brink B, Cooper D, Côté IM, Crane P, Dobson A, Dudley N, Dutton I, Green RE, Gregory RD, Harrison J, Kennedy ET, Kremen C, Willianms NL, Lovejoy TE, Mace G, May R, Mayaux P, Morling P, Phillips J, Redford K, Ricketts TH, Rodriguez JP, Sanjayan M, Schei PJ, van Jaarsveld AS, Walther BA (2005) The Convention on Biological Diversity’s 2010 target. Science 307:212–213 Wheeler, Q, Ed. The new taxonomy. Systematcs Association Special Volume Series 76. Possible Projects