ICT Services for open and citizen science

Mikoaj Morzy 0 0 M. Morzy ( ) Institute of Computing Science, Poznan University of Technology Poznan , Poland Ideas of open access, open data and open science are transforming the world of scientific inquiry as we speak. Every day thousands of ordinary citizens are engaging in data collection and data processing, giving rise to the new field of citizen science. Never before has the technology enabled scientists to reach out to such vast numbers of collaborators and show their work to the public. From pattern recognition in Hubble space telescope images of distant galaxies to field observations of migration patterns of birds in the rural areas of United States, the possibilities are countless. Certainly this new trend poses important problems and challenges, but it is also obvious that wide acceptance of citizen science can lead not only to great scientific results, but to the popularization of scientific method among the public. In the paper we examine the current state of citizen science, we outline some of the most interesting and difficult challenges in leading scientific projects on such scale, and we present typologies of citizen science projects. We also provide a survey of ICT tools available for citizen science projects. The traditional model of scientific research involves only professionals on all stages of the process. From the formulation of the research question, through study design and data collection phases, to data analysis and interpretation, all steps are limited to science professionals and the general public may be passively involved only in the dissemination of results. However, this model is highly ineffective and costly. All stages of the process may be greatly enhanced by widening of the group of people involved. One may easily imagine the - benefits of distributing the data collection process among the network of independent volunteers who may be able to collect amounts of data of orders of magnitude larger. Amateurs may be involved in data analysis (in particular, when the analysis requires tasks that do not yield well to automation), but their feedback may be useful even during data interpretation and conclusion inference phases. The history of volunteer participation in scientific projects dates back to the XIX century, but only recently, due to the advances in information technology field, the broad employment of amateurs in the scientific process has become a viable option to many fields of research. There are two major scientific movements fueled by the social network revolution that we are witnessing today. The first movement aims at making the scientific process transparent and accessible to public, both amateurs and trained professionals. This movement is often referred to as the open science and it advocates steps such as publishing results in open access venues, making datasets publicly available for easy replication of results, practicing open notebook science (i.e., publishing not only final results, but making all internal steps of the project publicly visible), and putting much effort into communication of science to the public. However, open science does not explicitly promote the involvement of amateurs in the process. This idea is the cornerstone of the second movement, called the citizen science. Following [18] we define citizen science as the form of collaboration involving active engagement of members of the public in scientific projects which address real world problems. We distinguish citizen science from other modes of public involvement in scientific process namely by the active engagement. Projects which require passive engagement, for instance, sharing resources to increase the computational power (e.g., SETI@Home), do not comprise citizen science. Also, we exclude from consideration projects in which members of the public are asked to participate in a study, e.g. by filling surveys and providing personal data, but do not engage actively in the scientific process. In this paper we focus mainly on citizen science, but many of our remarks can be easily applied to open science as well. As previous studies show [15], citizen science can lead to massive scale experiments resulting in high quality data, interesting insights, valid scientific finding and innovation, provided that projects are carefully planned and designed. The availability of modern information and communication technology (ICT) tools and services allows broad audiences to engage in scientific process, usually by providing collected data using agreed upon protocols, or by performing tasks, such as classification, recognition or computation, that require uniquely human capabilities. We want to analyze citizen science from the point of view of modern services and tools offered by ICT, and in particular, we want to establish the minimum set of technical requirements necessary to support a wide range citizen science project. Our attention is focused on Web 2.0 stack of technologies and how these services can be accommodated for citizen science projects. The structure of the paper is the following. In Section 2 we present a brief history of citizen science and we discuss some closely related paradigms. Section 3 presents the typology of citizen science models and projects. We introduce main challenges and problems facing citizen science projects in Section 4 and we describe relevant ICT services, tools and applications in Section 5. We conclude the paper with a summary in Section 6. 2 History of citizen science Using volunteer participation in conducting scientific research has been a popular method of inquiry. Historically, amateurs have been employed mostly in the fields of biology and ecology to assist scientists in large scale research, although other fields of science also benefited from mass participation of amateurs. Often cited as one of the first successful examples of citizen science is the 1874 project of measuring the transit of the planet Venus [14]. The project has been funded by British government and supported by the Admiralty, whose vast personnel has been used to gather and collect data from multiple positions on the globe simultaneously. Another example of a large scale project is the Christmas Bird Count [1], an annual event initiated in 1900 by a single person, Frank Chapman of the American Museum of Natural History, and continued until today under the auspices of the National Audubon Society. Due to the large number of skilled amateurs and willing volunteers, the field of ornithology has enjoyed many successful projects involving the public. Notable examples include the Breeding Bird Survey [5] started in 1966 and nest record counting, initiated by the Cornell Lab of Ornithology and continued until today as one of the most prominent online citizen science projects Neighborhood NestWatch [9]. Today, the Cornell Lab of Ornithology is supervising over 600 citizen science projects. Many projects revolve around organismal monitoring, (...truncated)