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Hindawi Publishing Corporation International Journal of Zoology Volume 2012, Article ID 349630, 14 pages doi:10.1155/2012/349630 Review Article The Citizen Science Landscape: From Volunteers to Citizen Sensors and Beyond Christina L. Catlin-Groves Department of Natural and Social Sciences, University of Gloucestershire, Cheltenham GL50 4AZ, UK Correspondence should be addressed to Christina L. Catlin-Groves, firstname.lastname@example.org Received 1 March 2012; Accepted 22 June 2012 Academic Editor: Simon Morgan Copyright © 2012 Christina L. Catlin-Groves. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Within conservation and ecology, volunteer participation has always been an important component of research. Within the past two decades, this use of volunteers in research has proliferated and evolved into “citizen science.” Technologies are evolving rapidly. Mobile phone technologies and the emergence and uptake of high-speed Web-capable smart phones with GPS and data upload capabilities can allow instant collection and transmission of data. This is frequently used within everyday life particularly on social networking sites. Embedded sensors allow researchers to validate GPS and image data and are now aﬀordable and regularly used by citizens. With the “perfect storm” of technology, data upload, and social networks, citizen science represents a powerful tool. This paper establishes the current state of citizen science within scientiﬁc literature, examines underlying themes, explores further possibilities for utilising citizen science within ecology, biodiversity, and biology, and identiﬁes possible directions for further research. The paper highlights (1) lack of trust in the scientiﬁc community about the reliability of citizen science data, (2) the move from standardised data collection methods to data mining available datasets, and (3) the blurring of the line between citizen science and citizen sensors and the need to further explore online social networks for data collection. 1. Introduction and data upload capabilities . This allows almost instant collection, transmission, and submission of data and pro- Within conservation and ecology, volunteer participation vides researchers with a way to validate data (e.g., to verify hasalwaysbeenanimportant componentofresearch[1– the identiﬁcation of an organism or the location through 5]. Within the past two decades, use of volunteers in GPS locators) . The availability of new technologies research has begun to proliferate and evolve into the current containing sensors could be argued to move citizen science form of “citizen science” [6, 7]. Citizen science, a term into a new era whereby citizen scientists also become citizen ﬁrst coined by Irwin , is used to describe a form of “sensors.” Collection of high-quality data can be made research collaboration or data gathering that is performed through the sensing capabilities of personal computing and by untrained or “nonexpert” individuals, often involving communication technologies, making the user part of a members of the public, and frequently thought of as a form more passive framework for data collection [17–19]. Some of crowd-sourcing [1, 8–12]. of the key strengths of citizen science projects lie in the Citizen science will usually incorporate an element of ease and speed with which data can be gathered by a large public education [2, 6, 13–15]. Silvertown described number of individuals in a short time. Ordinarily constraints the diﬀerentiation between historical and modern forms of such as money and time would make studies unfeasible citizen science by potential for it to be “available to all, not or impossible for an individual organisation [10, 15, 20]. just a privileged few.” This has been recently demonstrated Indeed, citizen science programmes are often more resilient by the rapid development of mobile phone technologies, in particularly the emergence and uptake of high-speed Web- to variations in ﬁnancial support than other programs capable smart phones with GPS data collection facilities [19, 21, 22]. 2 International Journal of Zoology With technological connectivity peaking, the ability to to tracking of invasive species is severely limited by both select virtual “ﬁeld assistants,” to help gather data is within logistical and ﬁnancial constraints. There are simply not easy reach; indeed Irwin  said that citizen scientists can enough resources, whether this is in the form of time, be considered as the “world’s largest research team.” A personnel, or money to establish large scale datasets [6, 10, further step is the potential for mining data, for ecological 33, 34]. Citizen science circumvents many of these problems or biological research, from the huge quantities of data which and has proven eﬀective in a number of research areas that are voluntarily uploaded onto personal social media accounts can have diﬃculty gathering large datasets. The areas in for the primary reason of storage or sharing with friends. For which it has, and most probably will continue to have, the example, there are over 26,000 images tagged with “manta greatest impact and potential are that of monitoring ecology ray” on Flickr (as of December 12th 2011), a species with or biodiversity at large geographic scales (see Table 3 for stable patterning that can be individually identiﬁed . examples). This is particularly prevalent due to the recent Custom Application Programming Interfaces (API) could proliferation of built in GPS technology and Web-capable theoretically identify these individuals and collect GPS data features that many handheld devices, such as mobile phones (where its available). This would create vast quantities of and increasingly cameras, now have in an aﬀordable and ecological and spatial data that could be utilised in research widely available format [10, 11]. which tracks individuals. However, despite this, citizen When monitoring for rare, unusual, or declining phe- science projects are often limited to: (1) informal education nomena, the scale of a large workforce over a large area activities or outreach to promote understanding [1, 6, 14, 24, will increase rates of detection in comparison to a lone 25]; (2) natural resource monitoring to promote stewardship researcher on a strict rotation despite having greater expert [26–28]; (3) to promote social activities and action [29, 30]; knowledge . Indeed in early 2006, the rare nine-spotted (4) purely virtual whereby the entire project is ICT-mediated ladybird (Coccinella novemnotata) was rediscovered during with no physical attribute (e.g., classifying photographs) a citizen science programme designed to educate the public ([31, 32], see Table 1). Table 2 provides examples of citizen science projects alongside their primary goals. in biodiversity and conservation. This nine-spotted ladybird Few scientiﬁc investigative projects exist in ecology or was the ﬁrst discovered in eastern North America in over biology using these new technologies for data collection, and fourteen years, and only the sixth in the whole of North where they do, they often encounter diﬃculties with gaining America within 10 years . robust data [5, 6]. Even less take advantage of the rapidly Traditional citizen science or volunteer programs have increasing and evolving capabilities of Web 2.0 and social resulted in some of the longest ecological temporal networks such as Facebook (http://www.facebook.com/), datasets that we can access, particularly in the ﬁeld of Twitter (http://www.twitter.com/) and Flickr (http://www.ﬂi ornithology. The Christmas Bird Count (CBC—http://birds ckr.com/), through which millions of people upload and .audubon.org/christmas-bird-count/) was launched 1900 by share photographs and location data, many citizen science the Audubon Society (in US and Canada) and provides studies also concentrate on data being collected within long-term comprehensive data trends for many species for a very rigid framework, very similar to previous volun- over 100 years. The British Trust for Ornithology, founded teer data collection whereby paper forms are replaced by in 1932, also regularly uses data collected by amateur online submission forms (examples include e-bird, Project birdwatchers and makes up a very substantial amount of Budburst, What’s Invasive, and Neighbourhood Nestwatch the National Biodiversity Network (http://www.nbn.org.uk/) Program). The possibility of using Web 2.0 and less rigid which contains over 31 million records. The data of these data collection techniques is relatively underexplored within programmes have helped to inform conservation actions, for scientiﬁc literature, even less so for biological and ecological example, by providing information to target conservation applications. management at particular sites by environmental organisa- This paper will predominantly cover the uses of citizen tions . science for ecology, biodiversity, and biological insights. Citizen science programmes conducted in the last 10 However, it may touch on various interdisciplinary citizen years have successfully followed the spread of invasive science programs or concepts where it is felt that it will be species or diseases, impacts of land use or climate change, beneﬁcial and may bring together other approaches which and have been instrumental in understanding distributions, may add value. The aim is to establish the current state ranges, and migration pathways (e.g.,[38, 39]). Researchers of citizen science within scientiﬁc literature, examine main at Cornell University, USA, have performed a large range of underlying themes, and explore the possibility of utilising an citizen science projects centred around avian species. Some untapped resource and the beneﬁts that this can hold for the of these projects have resulted in datasets that track the scientiﬁc community. It will also attempt to identify possible spread of conjunctivitis (Mycoplasma gallisepticum)inwild directions for further research. house ﬁnches (Carpodacus mexicanus) and the impact of forest fragmentation on tanager populations and nesting success . These eﬀorts have led to a large database called 2. The Citizen Science Landscape eBird, where amateur birdwatchers can upload sightings. These citizen science data have become the basis of trends The ability for intense monitoring by expert individuals on discovered through data mining and modelling techniques, any subject ranging from individual or species distributions International Journal of Zoology 3 Table 1: Citizen science typologies as described by Wiggins and Crowston . Type Description Example Shermans Creek Conservation Association Employ volunteer-initiated participatory action research to Action (http://www.shermanscreek.org/) encourage participant intervention in local concerns. Missouri Stream Team Project Address natural resource management goals, involving Conservation (http://www.mostreamteam.org/) participants in stewardship for outreach and increased scope. Focus of scientiﬁc research goals focussed on collecting data BirdTrack Investigation from the physical environment, usually underpinned by an (http://www.bto.org/volunteer-surveys/birdtrack) hypothesis or research goal. Whale FM Similar goals to the investigation project, but are entirely Virtual (http://whale.fm/) mediated by ICT having no physical element. Education and outreach are their primary goals, often data is Bird Sleuth not collected in a meaningful way that might be useful to Education (http://www.birds.cornell.edu/birdsleuth) other researchers. Often provides formal and informal learning resources. Table 2: Primary goals of citizen science projects (adapted and modiﬁed from Wiggins and Crowston ). Project URL Primary goal Description Learning about light pollution with use of Globe at Night http://www.globeatnight.org/ Education mobile phone or Web cam and internet connection. Learning about Devonian Fossils through Education Fossil Finders http://www.fossilﬁnders.org/ authentic inquiry-based investigation. Learning about birds through inquiry-based Education Bird Sleuth http://www.birds.cornell.edu/birdsleuth/ investigation. Missouri Stream Team Promotes the formation of “stream teams” http://www.mostreamteam.org Conservation Project which monitor streams in their area. Conservation What’s Invasive http://whatsinvasive.com/ Locating invasive plants. Started to oppose the building of a power plant Shermans Creek Action http://www.shermanscreek.org/ on local land, they now monitor the area and Conservation Association have regular talks. Promotes environmental involvement by growing and maintaining baby clams and ReClam the Bay http://www.reclamthebay.org/ Action oysterstostock theirlocal bay. Asks participants to listen to and classify whale Virtual Whale FM http://whale.fm/ song. Invites participants to classify images of Galaxy Zoo http://www.galaxyzoo.org/ Virtual galaxies. Collaborative online environment for citizen Pathﬁnder http://www.pathﬁnderscience.net/ Virtual scientists. Virtual Foldit http://www.fold.it/ Proving human superiority at protein folding. Part of Zooniverse—https://www.zooniverse.org/projects—citizen science hub for virtual citizen science projects exploiting the human ability to spot patterns and classify data where traditional statistical analysis struggles. which have led to further more focussed studies (visit in the discovery of new patterns and processes being found http://ebird.org/content/ebird/about/ebird-publications for in ecological systems (e.g.,[42–44]). Howard and Davis [45, more information and a full list of publications). 46] have published a number of peer-reviewed papers on Datasets that have been gathered for a speciﬁc purpose data predominantly collected by citizen scientists, gathering will often result in unexpected phenomena or patterns useable scientiﬁc data on autumn migration ﬂyways of emerging, that will then promote further more focussed monarch butterﬂies (Danaus plexippus). Citizen scientists studies. Many studies are available in scientiﬁc literature record overnight roosts and report their ﬁrst spring sightings where data mining and model construction have resulted to assess spring recolonisation rates. 4 International Journal of Zoology Table 3: Citizen science projects and data collection/submission process(s). Data collection/submission Project URL Description process(s) Project http://www.birds.cornell.edu/ A US program run by Cornell University. Participants count pigeons and record courtship Virtual form submission PigeonWatch pigeon watch behaviours observed in their neighbourhood pigeon ﬂocks. Initially US-ebased but moving more into global records. eBird’s goal is to maximize the utility and accessibility of the vast numbers of bird observations made each year by recreational and eBird http://ebird.org/ Virtual form submission professional bird watchers. Has an online accessible database and visualisation facilities for the participant and other interested parties. The ECOCEAN Whale Shark Photo-identiﬁcation Library is a visual database of whale shark Ecocean http://www.whaleshark.org/ (Rhincodon typus) encounters and of individually catalogued whale sharks. It asks participants to Virtual form submission upload images and sightings of Whale Sharks. http://www.usanpn.org/participate/ A US program run as part of the National Phenology Network, it asks people to report the Natures notebook Virtual form submission observe phenophases of particular species in their local areas. Partnership working between the British Trust of Ornithology, Royal Society for the protection of http://www.bto.org/volunteer- Birds, Birdwatch Ireland, and the Scottish Ornithologists’ Club, it collects data on migration BirdTrack Virtual form submission surveys/birdtrack movements and distributions throughout Britain and Ireland. Has an online accessible database and visualisation facilities for the participant and other interested parties. British Trust for Nongovernmental organisation dedicated to using volunteers who follow statistically designed http://www.bto.org/ Virtual form submission Ornithology sampling strategies in their research into birds. A US project participants observe plant phenophases. Scientists can use the data to learn more Virtual form submission Project Budburst http://neoninc.org/budburst/ about the responsiveness of individual plant species to changes in climate locally, regionally, and and mobile application nationally. submission Virtual form submission Asks participants to locate invasive species by making geotagged observations and taking photos What’s Invasive http://whatsinvasive.com/ and mobile application to map their spread. submission http://nationalzoo.si.edu/ Participants ﬁnd and monitor bird nests and record and report their observations. Researchers Neighbourhood scbi/MigratoryBirds/Research/ are especially interested in comparing how successful nests are in urban, suburban, and rural Virtual form submission Nestwatch Neighborhood Nestwatch/default.cfm backyards. Tagging and data mining A completed pilot project which asked participants to upload geo-tagged images of bees and tag http://www.ﬂickr.com/groups/beeid from existing social BeeID them with “beeid2010” tag on the Flickr photography Website, researchers then extract these network site with integral images, identify and tag with the species id. mobile upload facilities International Journal of Zoology 5 One of the common features of traditional and many products or engage audiences. This paper will not examine current projects is the formal submission process which these factors in depth, as they are far too large to be able occurs on a stand-alone Website or through one-to-one to cover appropriately (for more further information on communication between researcher and citizen. The sub- this topic, (see [51–53])). Society at large is beginning to mission is often closed or inaccessible until a result is understand the increased power of “the social network eﬀect” published, and even in citizen science programmes where behind Web 2.0, which increases value to existing users in a data is shared: it is very diﬃcult for the ordinary citizen to feedback loop (e.g., more and more users begin to embrace visualize; this is shown to have an impact on participation a service, increasing its popularity, and resulting in rapidly [6, 47]. e-Bird has gone through some lengths to overcome increasing adoption) [54–56]. this. By creating an online database system which has many Figure 1 shows a brief diagram of citizen science. In portals and visualisation techniques, citizen scientists and addition to running programs of research that encourage researchers alike can explore the e-Bird database . In users to engage in a more traditional data submission April 2006, when this newly improved Website was upgraded process, there is also the underexplored option of mining allowing participants to explore their own and others data, data from social networks and taking a more opportunistic the number of individuals submitting data nearly tripled approach. Indeed, many images, especially those taken on . Resources such as this require the citizen scientist to mobile phones, contain GPS information and can readily make an active eﬀort to discover the project, ﬁnd the Website be searched and mapped via the integrated search facilities and input, and retrieve data. By integrating data collection on Websites. The mobile interface allows the mobile phone into social media and fully exploiting Web 2.0, the quality, to become a people-centric sensor which is capable of geographical range, and quantity of data collected could aggregating inputs from local surroundings, enabling data to potentially be signiﬁcantly increased, and this is something be collected at a higher resolution . This may be useful in that requires further research. However, despite the lack plotting distributions and migration patterns or movements, of ﬁnancial cost that social media and Web 2.0 present, it both of individuals or species. Indeed, large charismatic is possible that the time and eﬀort cost might not make species with stable patterning such as whales, sharks, rays, the process worthwhile when considering the amount of and big cats are photographed regularly by tourists and additional data gained. shared online, and the ability to collate and analyse these images could prove valuable to the study of their movement, social grouping, and ultimately conservation. An emerging and particularly promising but under 3. Social Networks and Web 2.0 developed area of citizen science is that of using online Web 2.0 is an ambiguous term with almost as many facets social networking sites such as Facebook, Twitter, and mobile and conﬂicting opinions and deﬁnitions as the term citizen social networks such as Foursquare. Many of these have science, some even argue against the existence of Web 2.0 as a integrated image and location data upload facilities. Indeed, concept. However, for the purposes of this paper Web 2.0 can throughout 2011 there has been a proliferation of these be regarded as the socially connected and interactive internet facilities throughout popular social networking Websites. These features have been incorporated into basic interfaces, which facilitates participatory data sharing and encourages user-generated content. This medium consists of blogs, enabling users to simultaneously capture images; GPS tag podcasts, social networking sites, wikis, crowd-sourcing them, add, comments, and post, to followers or friends instantly via mobile internet. tools, and “cloud-based” group working environments. Web 2.0 has been expanded to a mobile computing context with Since it’s advent in 2004, Facebook (http://www.face- the proliferation of new technologies such as smart phones, book.com/), the most popular social networking site, has laptops, and tablet computers . grown to having more than 800 million active users globally, The most obvious purpose for exploiting Web 2.0, which with, on average, more than 250 million photographs up- is beginning to be used by researchers, is the power of loaded every day. More than 350 million people access it marketing and advertising, expressing branding, recruiting, through a mobile phone . Research by commercial online retaining, and sharing, and collecting data with the citizen marketing and data collection agency comScore Media Metrix suggested that Facebook reached 73% of Americans scientist [5, 49]. Delaney et al.  advocated the use of Web 2.0 capabilities for the ease of collecting and sharing data in June 2011 . With Flickr, the story is similar; Yahoo! via new cloud technologies. Delaney suggests that dynamic announced in August 2011 that it had reached 51 million linked databases that use online mapping technology such users and had, on average, 4.5 million photos uploaded every as Google Earth (free and familiar to citizen scientists) day. On the February 28th 2012 it had 176,605,443 geo- would prove ideal for creating a complete graphical “global” tagged photographs in total. With an integrated approach database of species. This would likely increase engagement and the correct marketing and publicity, in addition to and retention of individuals as they watch their contributions the increase of GPS-capable mobile devices it is likely that Flickr may become increasingly useful for gathering data, become part of the “bigger picture.” In essence, social media is being adopted as part of the communication strategy particularly for charismatic species. for engaging individuals who collect data or participate in The potential for scientiﬁc research is immense, partic- ularly for image-based data collection where EXIF informa- virtual citizen science programs; this adoption is seemingly in line with that of organisations at large to promote tion can be mined using a custom API and identiﬁcation can 6 International Journal of Zoology Mostly standardised Organised paper-based volunteer data collection Online submission (more widely available, “citizen science” is born) Mobile submission Social networking sites Mobile application Online submission forms via submission mobile internet Citizen sensing in an active Data mining Active participation framework in a passive framework (virtual citizen science) Mostly opportunistic or directed Figure 1: A brief diagram of citizen science, the diagram shows the proliferation in citizen science as new technologies have become available. ◦ ◦ ◦ 110 0’0”W 90 0’0”W 70 0’0”W 45 0’0”N 40 0’0”N 35 0’0”N 30 0’0”N 25 0’0”N 20 0’0”N (a) (b) Figure 2: (a) Screenshot of Flickr map displaying 250 of 13,329 geo-tagged photos tagged with “monarch butterﬂies butterﬂy” on February 28th 2012. (b) Map of Journey North roost sightings from all years combined (2005–2007). Dashed line indicates division of central and eastern ﬂyways in analysis. Roosts in Florida were not included in the analyses. Inset map shows the locations of all Journey North participants from 1997 to 2007. Star indicates location of Mexico overwintering sites . Reproduced with kind permission of Springer Science and Business Media. be veriﬁed by trained individuals or automatic recognition from a citizen science program called Journey North which software [60–63]. Figure 2 shows a small example of relies on a more traditional data submission process albeit what Flickr can do with a simple search term “monarch via an online form—http://www.learner.org/jnorth/). Using butterﬂies butterﬂy” (signifying a search for either butterﬂies a custom API and transposing all results onto Google or butterﬂy) which pulls up 13,329 geo-tagged photos within Maps or other mapping software, it would be possible to the US (February 28th 2012), 250 of which it can plot on limit the geo-tagged photo search by date and compare it a map on the Flickr Website. The map seemingly holds directly with Journey North’s monarch butterﬂy monitoring a cursory resemblance to Howard and Davis’s map program, which has received 4078 sightings within the last of monarch butterﬂy migration roosts (created using data year. However, without creating an API, a simple search International Journal of Zoology 7 on Flickr’s advanced search facility with the search term collect and submit information about invasive species whilst “monarch butterﬂy” brought up 15,499 photographs within they are observing them (http://whatsinvasive.com/). Project the same time period (using data collected on February Noah is similar in that respect but is built primarily to engage 28th 2012). Despite being likely that a large proportion and educate individuals in addition to collecting species contains no useful information (i.e., not pictures of the target data through a tagging and classiﬁcation system. Project species) and/or is not geo-tagged, (although estimates show Noah also incorporates “missions” to increase motivation >40% may be geo-tagged, ), this suggests that if this and promote the collection of speciﬁc species sightings method of data collection was further explored the number (http://www.projectnoah.org/). of potentially useful monarch butterﬂy sightings data could A recently developed formatting language, Hypertext be greatly increased. Markup Language 5 (HTML5), allows easier development Currently, a general internet user’s image and location across platforms and allows many of the features of mobile uploads are predominantly limited to “events” that the user phone applications to be incorporated into Websites. Web wants to share this might be “checking in” to restaurants, pages can then be developed to contain full multimedia attractions, clubs, cinemas, or concerts, often reviewing content that is easily accessible to popular technologies, products, or sharing visual experiences [65, 66]. Sharing something which some smart phones have found prob- these data with another user can be as simple as tagging them lematic due to limited Flash support (especially on Apple . By exploiting social networks in this way, for ecological devices). In the past, this inability has limited some of the or biological research, many of the most common mistakes content available and increased the amount of work needed or inaccuracies that are found within volunteered data could to replicate Web pages on smart-phones. be minimised. For example, by sharing images, and temporal Undoubtedly, with the advent of Web 2.0 and the quickly and GPS data, misidentiﬁcations and location inaccuracies developing technological breakthroughs, citizen science pro- can be ﬂagged and checked by trained individuals [5, 37, grams exploiting this technology are likely to increase 64, 67, 68]. Despite this, there are very few examples of exponentially in future years and should be encouraged. It social networking sites being used actively to collect data is hoped that as the full potential is revealed the negative bias for biological or ecological research; this may be because of among the scientiﬁc community that such approaches have confusion over copyright laws or limitations of API systems. attracted will begin to lessen. As the population increases At time of writing, there are very few examples of such and we are more isolated from nature and wildlife, the use of usages, and those few that do exist are limited to self- citizen science for biodiversity studies will enable individuals contained “groups” within Flickr which search images of to be further engaged in decision-making processes and the individual animals to export to an external catalogue for championing and protection of the natural environment. It identiﬁcation or use them to advertise the program and is a paradigm that is evolving alongside our relationship with attract new submissions (Table 4). technology, our environment and urban ecology and cannot Despite this ability to gather data quickly, they are be ignored . currently underutilised for ecological or biodiversity data collection. BeeID is a program of research which used 4. Trust and Reliability Flickr as a base for data collection [64, 67]. Researchers asked individuals to tag photographs of bees with speciﬁc The reluctance of the scientiﬁc community seems to pre- searchable metatags and place location data on them if it was dominantly stem from a mistrust of citizen science datasets not already embedded. Trained individuals then conﬁrmed due to the lack of validity assessments in academic research species identiﬁcation and marked the images as processed and published literature [70, 71]. Although many recognise via the addition of a new tag. A simple custom API that citizen science has increased the amount of data that extracted tagged photographs from Flickr and collected the is available, it is a concern that the quality, reliability, and data which successfully plotted bee species distributions. overall value of these data is still preventing its adoption in Considering the project had no funding and was run by many research programmes . Assurance of the quality a small group of individuals with limited promotion other of the data is needed through rigorous scientiﬁc methods in than on social networking sites, its success demonstrates the order to allow the acceptance of citizen science data into the potential beneﬁts of using social networking for collection scientiﬁc ﬁeld . of scientiﬁc data. Furthermore, the study took part before The literature suggests that the reliability of inherently the recent integration of easily accessible location data in patchy data is the most questioned aspect of citizen science. social networks and the continued rise of smart-phone and Thus, being able overcome this mistrust, a huge untapped aﬀordable GPS and wiﬁ enabled camera ownership. resource of citizen scientists could be opened up, increasing Another facet of Web 2.0 is the very recent addition of the scope and insight of conducted research. Potentially, phone applications or “apps.” These are easily integrated and this could result in large standardised spatial and temporal simple to use; however, the release of a mobile application datasets collected by citizen sensor networks . Traditional is not enough on its own to motivate participants and solutions to gaining credibility are to provide reliable infor- it is important to use mobile applications in an holistic mation or gain credentials such as qualiﬁcations; however, approach . “What’s Invasive” is a very recent citizen this works only when there are “gatekeepers” to ﬁlter science programme which uses a combination of a Website information, something which is not possible with the and custom mobile application to allow mobile devices to internet on a global scale . 8 International Journal of Zoology Table 4: Utilising Flickr for image-based citizen science programs. Passive Active Active data Project Project title and URL Description promotion promotion searching base To collect images to be submitted to http://www.whaleshark.org for identiﬁcation Whale Shark Identiﬁcation Recruits from group members and other Flickr users (http://www.ﬂickr.com/groups/ Y members YN through the search facility. It is worth noting that whalesharkidentiﬁcation/) to this Flickr Group has been formed by a volunteer promote and is not oﬃcially part of the project. A place for enthusiasts to meet and a promotion MantaWatch tool directing people to their Website (http://www.ﬂickr.com/ (http://mantawatch.com). Does not seem to YN N N groups/mantawatch/) actively recruit members or search out images of manta rays on Flickr. To collect images to be submitted to http://www.coa.edu/nahwc.htm for identiﬁcation from group members and other Flickr users through the search facility. The same project also has a whale catalog Humpback whale ﬂukes Recruits (http://www.ﬂickr.com/photos/ (http://www.ﬂickr.com/groups/ Y members YN ﬂukematcher/) located on Flickr so that humpbackﬂukes/) to individuals can manually match their sightings. A promote further more regional group (http://www.ﬂickr.com/groups/ northatlanticﬂukes/)has formed duetothe volume of photos uploaded. Recruits Citizen Science: Great Blue Heron This group aims to create a database of members (http://www.ﬂickr.com/groups/ geo-tagged images of the Great Blue Heron, Y YY to csgreatblueheron/) entirely run and initiated by volunteers promote A completed project run by student volunteers, and overseen by a lecturer, whereby members of Y the public are encouraged to upload photos of UK Recruits BeeID bees (Honeybees, bumblebees, and solitary bees) Y members NY (http://www.ﬂickr.com/groups/beeid/) to their Flickr account and “geotag” them to place to them on a map, with the aim of studying promote distribution and phenology. The dependability of volunteer-derived data is an old quizzes which help in assessing a contributors’ knowledge; problem within biology and ecology, and therefore a number they have also implemented an automated meso-ﬁlter which of methods to help to increase the reliability of the infor- evaluates data input and evaluates it based on already known mation gathered have been developed [6, 22]. Firstly, the parameters, submissions which fall out of these categories are researchers must concisely and without jargon ask the right ﬂagged for expert review, the contributor contacted, and the questions in the right way to get the quality of answer that entry either veriﬁed or disregarded [6, 10, 81]. is needed, and instructions and processes must be clear and Although there is not enough space to review all the as simple as possible [3, 9–11]. Projects are usually kept literature which has been published as a result of data relatively simple; for example, they might include counting collected through the use of citizen science participation, a few common avian species frequenting a feeding table literature searching has resulted in the location of over 300 rather than searching for rare or diﬃcult to spot species instances of peer-reviewed publications. This suggests that [6, 22, 74, 75]. Projects that require higher levels of skill citizen science has and will continue to produce usable forms can be successfully developed; however, they may require of data (See Figure 3). As with any data, datasets should additional training or longevity of participation in order be approached with caution and “cleaned” or “scrubbed” to increase experience indeed, many volunteer programs before performing analysis to remove any obvious outliers document “learner” eﬀects whereby data collectors become . The literature suggests, however, that if the program more accurate and correct over time [6, 10, 22, 76–80]. protocols have been properly formed and tailored to the Some of the online citizen science programmes that Cornell appropriate audience data does not often diﬀer signiﬁcantly University has run in the past incorporate short tests and from expert data collection. Delaney et al.  found that International Journal of Zoology 9 Table 5: Comparison of avian monitoring projects focused on measuring occurrence and abundance (adapted from ). Results from these programs have been used in over 1000 publications Project Method Placement Eﬀort Extent Interval Participants Audubon Christmas Count circle (24 59,918 Opportunistic V (party hours) International Annual Bird Count km diameter) (2008-09) North American Roadside survey Stratiﬁed random S (3 min count) International Annual 2,749 (2009) Breeding Bird Survey (39.4 km; 50 stops) V (2 days, hours, Project FeederWatch Feeder counts Opportunistic International Annual 9,750 (2009) days) V (hours, eBird Online checklists Opportunistic distance, and International Continuous 18,053 area) Systematic grid Two visits (Winter: (100 km blocks; 4 Regular grid and S/V (roving, Britain and Nov./Dec. & Jan./Feb.; Bird Atlas 10,000–20,000 km tetrads) and opportunistic timed visits) Ireland Breeding: April/May & roving reports June/July) Common Birds Census plots Census (now replaced S (territory Annual (8–10) visits; late (Farmland: 70 ha; Stratiﬁed random Britain 250–300 by Breeding Bird mapping) March–early July) Woodland: 20 ha) Survey) Eﬀort is considered standardised (S) or variable (V). When standardised, the protocol speciﬁcations are presented; when variable, the eﬀort variables that were reported during sampling are presented. Scientiﬁc papers published as the result of citizen statistical power and increased robustness, as statistical science involvement from 1995-Feb 2012 power is a function of sample sizes [22, 37]. Therefore, the common belief that volunteer collected data can only provide noisy and unreliable results that lack precision is generally incorrect [22, 37]. LePage and Francis  compared two citizen science programs with similar data collection protocols to test whether population patterns and distributions were temporally and spatially consistent. The study successfully showed that the two citizen science led studies, Christmas Bird Count and Project FeederWatch, Year published had comparable trends and patterns across the same time periods, suggesting that the data was consistent and not Figure 3: Numbers of published scientiﬁc papers using or resulting signiﬁcantly inﬂuenced by diﬀerent methods and biases. The from citizen science data collection or involvement; it indicates an beneﬁt of these larger datasets is that they allow researchers increasing trend. to draw broader conclusions across large spatial or temporal scales, enabling researchers to make inferences and robust cases for causation over a larger areas, and at a ﬁner resolution, in contrast with small scale studies which cannot far from overlooking data collection methods novices were “more careful” in their measurements and annotations, due be “generalised” over greater areas [3, 6, 9, 11, 38]. It is, however, important to recognise that these datasets to are being very aware of their novice status and shown in can be compromised by potential lack of precision, inherent many studies to yield similar results to experts [22, 50, 83]. biases, and uncertainties which are often present within these Delaney et al.  found experts and nonexperts did not extensive studies [11, 22, 84]. For example, you may have come up with any signiﬁcantly statistical diﬀerences, indeed students were found to be between 80 and 95% accurate more reports of species in areas that are highly populated by humans than in those that are sparsely populated, or with identiﬁcation, with signiﬁcant predictors of accuracy more reports of species that are less cryptic than others. being their age and level of education. Dickinson et al.  reported that during Project FeederWatch between 2008 and It is therefore a challenge to determine whether the data is correct or the reports are biased; this is the reason why 2009 they received 1,342,633 observations, out of those 378 many citizen science programs are so rigidly composed and records required “ﬂagging” resulting in 158 records (54%) use standardised protocols which are replicated across many being conﬁrmed, 45 identiﬁcations (16%) being corrected, stratiﬁed surveyed plots (see Table 5 and [11, 22, 84]). It is and 88 reports (30%) being disregarded due to too little evidence. therefore important to ensure, in hypothesis driven studies, that sampling design does not introduce bias, and that counts Indeed, the very nature of gathering large sets of data are shaped by the data and not the ability of the observer results in decreased detrimental eﬀects of “noise”, greater Number of papers published 2012 10 International Journal of Zoology to detect or record data . This is partially why using species that they might see on a separate sheet. The Garden such count data to establish index of abundance can be BirdWatch goes one step further to collect additional data scientiﬁcally hazardous; however, by using capture-recapture and provides a presence and absence record sheet for all algorithms, conversion to actual population estimates can species not mentioned. be made and therefore data can be used to make a valid The key diﬀerence between the RSPB and BTO’s citizen conclusion [86, 87]. science programmes is the method of collection. The RSPB Well known and successful UK citizen science-based has no paper-based submission format, but the BTO does, programmes are those which are based in the public’s back with a scanning machine which automates the data retrieval gardens. The British Trust for Ornithology’s (BTO) and and decoding from the paper-based forms. The BTO suggests Royal Society for Protection of Birds’ (RSPB’s) garden-based that the “relative proportions of participants submitting citizen science programmes have been very successful in returns on paper and online are similar.” collecting biodiversity data, particularly on avian species. Neither of these programmes use social networks for The “Garden BirdWatch” and “Big Garden Weigh-In” run more than publicity. In 2012, the BTO began the Cuckoo by the BTO and the “Big Garden Birdwatch” and ‘Make Tracking project, whereby tagged Cuckoo’s were tracked dur- Your Nature Count survey’ run by the RSPB are just a ing their migrations (http://www.bto.org/science/migration/ few of the citizen science programmes which encourage tracking-studies/cuckoo-tracking). As part of the publicity, the recording of species which are visiting their gardens. sightings were called for and the “hashtag” #heardacuckoo For a full list of citizen science projects run by these was created on the social network Twitter to publicise the organisations visit the BTO (http://www.bto.org/)and RSPB project. Many individuals used the hashtag to report when (http://www.rspb.org.uk/) websites. they had indeed heard a cuckoo. If a tool such as CrowdMap These programmes have a number of key design sim- (https://crowdmap.com/) was used to ﬁlter the tweet’s with ilarities which help standardise the survey and mitigate #heardacuckoo in them and veriﬁed by experts, could the against some of the perceived problems involved with conversion rate from publicity to actual record be higher? nonexpert individuals collecting data. Indeed, they have proved to be reliable enough to result in published scientiﬁc 5. The Shifting Paradigm: From “Knowledge- papers. The Garden BirdWatch alone has resulted in 15 published scientiﬁc papers in addition to providing a strong Driven” Analysis and Hypothesis Testing set of baseline data (visit http://www.bto.org/volunteer- to “Data-Driven” Analysis surveys/gbw/publications/papers for full list of publications). To prevent confounding seasonal variation and to ensure With the advent of the Web 2.0 world and the increase of the continuity of recording eﬀort citizen scientists are asked to “citizen sensor network,” there is a shifting paradigm from record species within a given survey period, the Big Garden “knowledge-driven” analysis created by hypothesis-driven Weigh-In ran between the May 31st and June 5th in 2012 for research to “data-driven” analysis, moving studies into more example. To standardise eﬀort the records are gathered over data-intensive science area [44, 83]. This is resulting in a new a particular time period, an hour is the most popular time, synthesis of disciplinary areas as new methods of analysis and many of the surveys require the species to be physically emerge to explore and identify interesting patterns that may within the garden (not in a neighbouring garden or ﬂying not already be apparent; this is particularly prevalent when over). The Garden BirdWatch asks observers to repeat this looking at data gathered over large spatial and temporal recording at the same time and from the same place and of scales [44, 88, 89]. This approach oﬀers valuable insights the same area for each recording session during the survey enabling further hypothesis for the discovery of underlying period. ecological processes. With such large datasets with such Pseudoreplication is combated by removing the diﬀer- varying attributes; it is no wonder that all disciplines of ence in the ability of the observer to identify diﬀerent science are seemingly beginning to merge into computer individuals; this is achieved by recording the maximum science as it enables scientists in varying ﬁelds to better number of individual birds present at any one time within understand complex systems [83, 90–93]. In ordertobetter the garden. So if an observer sees one Blue Tit at the utilise citizen science collected datasets that provide a wide beginning of the survey but ﬁve in the middle and two range of data over long periods, many researchers are towards the end of the survey, they would report it as ﬁve moving into intelligent analysis. This may involve using novel Blue Tits. probabilistic machine-learning statistical analysis in the form Thespecies whichare surveyed arealso reducedtoa of computational modelling, or methods of analysis which range of easily identiﬁable species. The Garden Weigh-In include Bayesian or neural networking methods [90, 91, 93, reduces the number of birds under observation to 60 avian 94]. Indeed, Link et al.  utilised a hierarchical model species which compose the core avian community. The and Bayesian analyses to account for variations in eﬀort on Garden BirdWatch reduces the number further to the 42 counts and to provide summaries over large geographic areas most commonly recorded birds (nationally), with a further for a complex dataset provided by the Christmas Bird Count breakdown resulting in a list of the top ten which can have in America. They successfully revealed regional patterns of further detail added. 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International Journal of Zoology – Hindawi Publishing Corporation
Published: Sep 19, 2012
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