What do volunteers want from citizen science technologies? A systematic literature review and best practice guidelines

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DOI: 10.22323/2.18010202
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Abstract
Although hundreds of citizen science applications exist, there is lack of detailed analysis of volunteers' needs and requirements, common usability mistakes and the kinds of user experiences that citizen science applications generate. Due to the limited number of studies that reflect on these issues, it is not always possible to develop interactions that are beneficial and enjoyable. In this paper we perform a systematic literature review to identify relevant articles which discuss user issues in environmental digital citizen science and we develop a set of design guidelines, which we evaluate using cooperative evaluation. The proposed research can assist scientists and practitioners with the design and development of easy to use citizen science applications and sets the basis to inform future Human-Computer Interaction research in the context of citizen science.
JCOM
USE R EXPERIENCE OF DIG ITAL TECHNOLOGIES IN
CITIZEN SCIENCE
What do volunteers want from citizen science
technologies? A systematic literature review and best
practice guidelines
Artemis Skarlatidou, Alexandra Hamilton, Michalis Vitos and
Muki Haklay
Although hundreds of citizen science applications exist, there is lack of
detailed analysis of volunteers’ needs and requirements, common usability
mistakes and the kinds of user experiences that citizen science applications
generate. Due to the limited number of studies that reflect on these
issues, it is not always possible to develop interactions that are beneficial
and enjoyable. In this paper we perform a systematic literature review
to identify relevant articles which discuss user issues in environmental
digital citizen science and we develop a set of design guidelines,
which we evaluate using cooperative evaluation. The proposed research
can assist scientists and practitioners with the design and development of
easy to use citizen science applications and sets the basis to inform future
Human-Computer Interaction research in the context of citizen science.
Abstract
Citizen science; Public engagement with science and technologyKeywords
https://doi.org/10.22323/2.18010202DOI
Submitted: 3rd April 2018
Accepted: 25th July 2018
Published: 17th January 2019
Introduction The ubiquity of technology and the Internet has dramatically changed the landscape
of information availability, including the ways in which we interact with it to make
better decisions and improve our quality of life. Technological innovations have
resulted in changes not only in the economy and the workplace, but also in the ways
people choose to live their lives, spend their free time, and interact with others.
Such changes have led to social innovations, which have ushered in a new wave
of social change. One such change took place within the scientific context, with
the ongoing growth number of amateur volunteers, with the help of technology,
now work together with scientists to explore and address scientific issues.
This collaboration, or partnership, between professional scientists and amateur
volunteers is known as citizen science (CS). In its simplest form it involves amateur
Article Journal of Science Communication 18(01)(2019)A02 1
scientists collecting data; an activity which reduces the costs of addressing scientific
questions that require the collection of massive amounts of data, and which further
bridges the intellectual divide magnified by the professionalisation of science, and
the scientific expertise that it may assume. Many CS scholars situate the activity
over two centuries ago when amateur scientists, such as Charles Darwin, made
significant contributions to science [Silvertown, 2009]. Currently, hundreds of CS
projects engage thousands of volunteers across the world. A relatively recent
analysis of 388 CS projects revealed that they engaged 1.3 million volunteers,
contributing up to US$2.5 billion in-kind annually [Theobald et al., 2015]. The eBird
project alone collects five million bird observations monthly, which has resulted in
90 research publications [Kobori et al., 2016]. Technological innovations such as the
Internet, smartphone networked devices equipped with sophisticated sensors, and
high resolution cameras have had a massive impact on science, especially the way
in which CS is currently practiced.
Volunteers who interact with these technologies come from different age groups
and geographic locations; their cultural contexts and the languages they speak may
vary; as do their skills, motivations and goals. A typical user might be an MSc
marine biology student who uses a mobile CS application to identify invasive
species, or equally an illiterate hunter-gatherer in the Congo basin who collects
data to address the challenges of illegal logging and its impact on local resource
management. Making sure that users can fully utilise the technology at-hand is
fundamental. Within this context, Preece [2016] calls for a greater collaboration
amongst “citizens, scientists and HCI specialists” (p. 586). Human-computer
interaction (HCI), the discipline which studies how humans interact with
computers and the ways to improve this interaction, has a long tradition in the
design and development of technological artefacts, including aviation technology,
websites, mobile devices, 3D environments and so on.
Volunteers’ involvement in the use and design of CS applications is fundamental
for effective data collection. Issues such as motivating users to remain active,
ensuring that users can effectively use the applications, and guaranteeing
satisfaction of use, should be central in the design and development of such
applications; issues that according to Prestopnik and Crowston [2012] look beyond
“building a simple interface to collect data” (p. 174). Existing studies which investigate
user needs and requirements, usability, and user experience (UX) elements (such as
having fun and joy) of CS applications provide interesting insights, usually in
specific contexts of use. Nevertheless, there is a lack of reflection on the lessons
learned from these studies. A more holistic overview is needed to explore the
current state of HCI research within CS, and how this knowledge and preliminary
empirical evidence can inform the design and development of ‘better’ CS
applications. This paper attempts to address this gap. With the preliminary aim of
identifying key design features, as well as other relevant interaction
recommendations, a systematic literature review (SLR) was utilised to capture
research studies which discuss user issues of CS applications that support data
collection (either web or mobile based). This evidence and knowledge is
summarised in a set of design guidelines, which were further evaluated in a
cooperative evaluation (CE) study with 15 people.
Before we explain how these methods were employed in this study in section 3, the
next section provides their theoretical background. Section 4 briefly presents the
https://doi.org/10.22323/2.18010202 JCOM 18(01)(2019)A02 2
results, and section 5 discusses, in more detail, the studies that we analysed in the
SLR, together with the findings of our CE. Conclusions are drawn in section 6,
focusing on limitations of this research and suggestions for future research.
Theoretical
overview of
methods used
A systematic literature review (SLR) provides a standardised method for reviewing
literature which is “replicable, transparent, objective, unbiased and rigorous” [Boell and
Cecez-Kecmanovic, 2015, p. 161]. SLRs emerged in evidence-based medicine
during the 1990s, but have since been found, in increasing numbers, within various
fields including education, psychology and software engineering [Boell and
Cecez-Kecmanovic, 2015]. SLRs have also been used in the context of HCI and CS.
For example, Kullenberg and Kasperowski [2016] outline a scientometric
meta-analysis, using datasets retrieved from the Web of Science, to investigate the
concept of CS, its development over time, the research that it covers and its
outputs. In their study they mention implications associated with the use of key
terms (e.g. use of terms related to CS, such as crowdsourcing, participatory
monitoring, public participation and acronyms such as PPGIS), but generally no
other criticisms are mentioned.
Zapata et al. [2015] use a SLR approach to review studies that perform usability
evaluations of mHealth applications and their user characteristics on mobile
devices. Due to the narrow focus, and the fact that the results were further
analysed qualitatively, Zapata et al. [2015] only screen 22 papers (out of the 717
articles which were initially retrieved). Connolly et al. [2012] review the impacts of
computer games on users aged above 14 years old. With an initial 7,391 articles
retrieved from various databases, they applied a relevance indicator (from 1 least
relevant to 9 most relevant) to each paper and analysed the papers that received a
rank higher than 9, resulting in a final screening of 70 papers which discuss several
dimensions of the detected impacts. Other studies investigate the accessibility and
usability of ambient assisted living [Queirós et al., 2015]; studies which integrate
agile development with user centred design [Salah, Paige and Cairns, 2014] to
identify challenges, limitations, or other characteristics, thus requiring a qualitative
analysis of the papers reviewed.
Although the previously mentioned studies offer a limited insight into the
limitations of SLRs, the most widely acknowledged limitation surrounds the
weaknesses of search terminology, as effective keyword combinations cannot be
always known a priori [Connolly et al., 2012; Boell and Cecez-Kecmanovic, 2015].
Likewise, the process’ internal validity, such as problems related to data extraction,
the so-called recall-precision trade off, and a lack of evaluation, is also considered a
limitation [Boell and Cecez-Kecmanovic, 2015]. To adjust for these limitations, this
research evaluated the content of our meta-analysis in a user testing experiment.
We employed cooperative evaluation method; a user testing method which allows
for the observer to interact with the user subjects in order to direct their attention
and record their opinion about specific design features while they work together as
collaborators. Thus, the observer can answer questions and doesn’t have to sit and
observe in silence while the user interacts with the application involved in the
experiment [Monk et al., 1993].
Furthermore, this research focuses on the environmental CS context. As an
increasing number of CS projects in various fields (e.g. astronomy, linguistics)
https://doi.org/10.22323/2.18010202 JCOM 18(01)(2019)A02 3
make use of digital technology to engage their volunteers in data collection
activities, only some of these projects consider user issues in their design [e.g.
Sprinks et al., 2017]. The interfaces, tasks, and therefore design issues or user needs
and requirements vary across different contexts of use. For example, in
astronomy-related CS applications image classification is a major task, whereas in
conservation applications tasks such as adding an observation using a mapping
interface are more common. In order to narrow down the focus, and also due to the
authors’ interest in the way geographical interfaces assist volunteers in data
collection, the term ‘environment’ has been included in all keyword searches.
Although this might limit the scope and extent of retrieved studies, it should be
noted that the term is already quite broad, since it may include applications from
contexts where CS is widely used, including, but not limited to, ecology,
conservation, environmental monitoring, etc. In the next section we review the
methodological implementation and experimental design.
Methodological
procedure and
experimental
design
A two-stage methodological approach was applied. In the first part, a systematic
literature review (SLR) was conducted to review and evaluate relevant research
studies; section 3.1 describes this process. In the second stage, discussed in section
3.2, 15 CE experiments were implemented to evaluate three online CS applications,
which provided a context to discuss the preliminary guidelines with our
participants.
Systematic literature review
The following databases were included in our search: Web of Science1of Thomson
Reuters, Scopus2of Elsevier, and Google Scholar.3The sources comprise access to
multidisciplinary research studies (i.e. peer-reviewed and grey literature) from the
fields of sciences, social sciences, and arts and humanities. We decided to employ
all of them to obtain reliable, robust, and cross-checked data; including a
reasonable amount of ‘grey literature’ via Google Scholar, so that we could include
in our search technical reports and government-funded research studies which are
not usually published by commercial publishers [Haddaway, 2015]. The searches
took place in June (i.e. Google Scholar) and December 2017 (i.e. Web of Science and
Thomson Reuters) following the same methodological protocol. In order to
automate the otherwise time-consuming search process, we used the free software
“Publish or Perish”, which allows importing a set of keyword combinations,
executing a query on Google Scholar for each of them and collecting the results into
a CSV file. The software was configured to execute 120 queries per hour.
Our database search aimed at retrieving papers with a focus on user issues of CS
technologies in the environmental context. The majority of key terminology (i.e.
user, citizen science, technology) is not standardised; for example, in the literature
alternative terms that are used for user requirements may include “user needs”,
“volunteer needs” or “volunteer requirements”, which were all included in the
SLR. Similarly, other terms related to citizen science such as “participatory science”
and “crowdsourced science” we deemed relevant as several of these terms are used
1Web of Science: http://apps.webofknowledge.com/.
2Scopus: https://www.scopus.com/search/form.uri.
3Google Scholar: https://scholar.google.co.uk/.
https://doi.org/10.22323/2.18010202 JCOM 18(01)(2019)A02 4
interchangeably in the literature and the similarities in the way these are practiced
especially concerning user issues of those digital technology-based
implementations. Considering that the search for the right terminology in SLRs
becomes a search “for certain ideas and concepts and not terms” [Boell and
Cecez-Kecmanovic, 2015, p. 165] which are relevant to the particular topic, we
decided to include the concepts/keywords that are shown in Table 1; with the
keyword ‘environment’ consistently applied to all searches. Our extensive concept
identification analysis resulted in 1,045 keyword combinations, which significantly
increased the effort and time needed to gather and analyse the data. SLR searches
“are optimised to return as many (presumably) relevant documents as possible thus leading
to a high recall” [Boell and Cecez-Kecmanovic, 2015, p. 165], which may be at the
expense of data accuracy. Although each keyword search combination was
designed to return only 200 results, we were confident that by including such a
broad range of concepts we would be able to effectively capture the broader
state-of-the-art literature in the area of environmental digital CS with a focus on
user issues or detailed user studies.
Table 1. Concepts/Keywords used in the Systematic Literature review. Highlight in bold
are the most popular terms in each category according to the number of articles retrieved.
Themes User-focus Citizen Science -
focus
Technology -
focus
Keywords HCI, human-computer interac-
tion, usability, evaluation, user
experience, UX, user needs, user
requirements, user research,
human factors, UCD, user-
centred design, human-centred
design, accessibility, volunteer
needs, volunteer requirements,
user testing, volunteers’ needs,
volunteers’ requirements
Citizen science, particip-
atory science, DIY science,
grassroot science, civic
science, crowdsourced
science, community sci-
ence, community-based
participatory research,
community-based monitor-
ing, public participation in
scientific research, PPSR
Technologies,
technology,
digital, ICT,
technology-
mediated
For each result the following information was retrieved: title, author(s), date,
number of citations, publisher and the article URL. After duplicates were removed
and any missing fields (i.e. mainly dates) were manually filled in, we applied our
exclusion criteria. These included: studies published before 2000, as digital CS only
gained momentum in the mid-2000s [Wald, Longo and Dobell, 2016; Silvertown,
2009]; studies in languages other than English, as it would not be possible to
further analyse their content. The studies that were included in the analysis all
discussed digital CS in the environmental context (i.e. either focusing entirely on an
environmental CS application or including examples of such applications) and had
a user focus (i.e. recommendations for design features based on user studies or on
user feedback; insight into user issues and design suggestions based on broader
experience; expert inspections for usability improvements, etc). To ensure that
these themes were all covered by the remaining studies the following were
separately assessed by two of the authors: title, followed by the abstract and, if
necessary, the introduction and conclusions. The final list of SLR papers (i.e. 62
papers in total) were all read in-full to inform our preliminary set of best practice
guidelines. More than one paper mentioned the same design issue in order for it to
be included it in the preliminary list of design guidelines.
https://doi.org/10.22323/2.18010202 JCOM 18(01)(2019)A02 5
Cooperative Evaluation (CE)
The preliminary guidelines that resulted from the meta-analysis of the final articles
were further evaluated, through the use of CE experiments, and extended upon so
that users’ direct feedback is taken into account. For the purposes of this study,
three applications were evaluated, which featured either a mobile or a web
interface (or both). The three applications which were included in the CE
experiments are:
– iSpot;4nature-themed CS application provided by Open University, with
over 65,000 registered users (as in March 2018). The application provides
users with a web-based interface, which people can use to upload
geo-referenced pictures with various wildlife observations, explore and
identify species, and connect with other enthusiasts worldwide (Figure 1a). It
further supports gamification (via badges, which are popular in the
engagement and retainment of online volunteers.).
– iNaturalist;5environmental CS application developed originally at UC
Berkeley and now maintained by the California Academy of Sciences with
over 0.5 million registered users (Figure 1b). It provides both a web-based
interface and a mobile application to contribute biodiversity data in the form
of photographs, sound recordings or visual sightings. The data are open
access and available for scientific or other purposes.
– Zooniverse;6one of the most popular digital CS platforms, with over 1.6
million registered users6was developed by Citizen Science Alliance. The
platform includes several CS projects, of which the most popular is the
Galaxy Zoo project. The platform was included in the evaluation for the
assessment of overall interface design and assessment of such design features
as tutorials and communication functionality and therefore we decided to
investigate these features within as well as beyond the environmental context
(i.e. projects of environmental interest). The project pages included in the
evaluation are: Wildlife Kenya, Shakespeare’s World, the Elephant Project,
Galaxy Zoo and Understanding Animal Faces.
It should be noted that iSpot and iNaturalist applications were chosen on the basis
of their popularity and strong environmental focus. Zooniverse was chosen due to
its popularity and the significant number of users that it attracts to mainly focus on
design features of the communication functionality category which extends to the
broader CS context.
Fifteen participants (seven male and eight female) were recruited, via opportunity
sampling, to evaluate the applications and offer user feedback with respect to the
SLR preliminary guidelines. Since all of the applications’ projects are designed to
be inclusive towards a wide user audience we decided against restricting
participation to specific conditions, which would in turn influence the usefulness of
4iSpot: https://www.ispotnature.org/ It should be noted that while in the past iSpot had a
dedicated Android app, it was withdrawn in February 2015, and the web-based interface is used on
mobile phones, too.
5iNaturalist: https://www.inaturalist.org.
6Zooniverse: https://www.zooniverse.org/.
https://doi.org/10.22323/2.18010202 JCOM 18(01)(2019)A02 6
Figure 1. Interfaces of applications included in the CE experiments; a. iSpot; b. iNatural-
ist.org; c. Zooniverse.
this study. Nonetheless, the majority of our participants (9/15) were between 18–25
years old (with a further two between 25–34; three between 45–54 and one 55+).
Only six of the participants had prior knowledge or experience with CS projects, all
had experience interacting with online/mobile mapping interfaces and, in terms of
their technological skills, five rated themselves as ‘intermediate’, six as ‘advanced
and four as ‘experts’.
The applications were evaluated in a random order to minimise bias introduced by
the learning effect. The experiments were carried out in July and August 2017.
Each experiment was carried out over one hour and a set of tasks were provided to
the users to guide their interaction with the application they interacted within the
CE session. The tasks were designed to gain a better understanding of the design
guidelines derived from the SLR (e.g. Find the forum page and read discussion about
‘adding photo to button’ on iSpot; check notifications for new messages/comments on
Zooniverse; check news feed for updates from iNaturalist community). Of course more
simple tasks that helped participants get a good understanding of the application’s
context of use were also included (e.g. Explore photos for observations in your local area
on iSpot; explore projects and then select a project to contribute an observation on
Zooniverse). A total of 10 tasks per application were provided to guide interaction
and participants were asked to think aloud.
https://doi.org/10.22323/2.18010202 JCOM 18(01)(2019)A02 7
Results Systematic literature review
The 1,045 keyword combinations returned 24,147 results from all three databases,
dated from 1970 to 2017. In the three categories of keywords the most popular
were: technology/technologies (13,781; followed by digital with 6,057 results);
citizen science (8,793 results; followed by participatory science with 2,168 results)
and evaluation (5,160; followed by usability with 3,038 and human computer
interaction with 2,088 results).
After removing duplicates, non-English results and any publications dated before
2000 we ended up with 844 results (Figure 2). Figure 3 summarises the top ten
keyword combinations returning the majority of results in this stage. This dataset
includes articles and other results from various disciplines, mainly healthcare,
education, environmental studies and HCI. The terms ‘technology’ or
‘technology-mediated’ are especially popular in education literature and
‘community-based participatory research’ is popular amongst health scholars, yet
the majority of these articles do not satisfy the rest of the SLR criteria. Moreover,
the keyword ‘evaluation’ returned almost 5,160 results, the majority discussing
different aspects of evaluations (e.g. project, methodological or result evaluations),
with only a few focusing on evaluations of user issues.
Figure 2. Systematic Literature Review procedure.
The next step involved inspecting all n=844 results (i.e. examination
of title, abstract, methodology and conclusions); a process undertaken by two of the
authors of this paper. During this process irrelevant results (i.e. studies that do not
satisfy the search criteria) were excluded together with: i. Results that we could not
access (e.g. conference proceedings, other n=47); ii. Books (not available online or
in a digital form) (n=3 entries), as it would be difficult to further process content in
the meta-analysis study; iii. Slideshare, poster presentations and keynotes (n=18),
as they did not provide enough insight to inform meta-analysis; iv. Studies that
targeted only children (n=4), as the user audience of all other studies included in the
SLR is much broader and including these articles would introduce a bias; v. Studies
https://doi.org/10.22323/2.18010202 JCOM 18(01)(2019)A02 8
Figure 3. Ten most popular keyword combinations (for n=848) based on number of articles
returned. ‘Tech’ is used for technology; ‘CS’ for Citizen science; and ‘env’ for environment.
discussing technologies at a conceptual level (i.e. applications do not yet exist)
(n=4); and vi. Studies which describe sensors (non-phone based) and wearable
technologies (n=2); these technologies have different characteristics that need
to be considered for their effective design. Keywords such as “community-based
monitoring” returned several results focusing on the development and
user issues of Web Geographical Information Systems (GIS), which is commonly
used in CS. We included only studies which described technologies to support
data collection, and not studies on data visualisation for public consultation,
another popular area in Public Participation GIS. Theoretical papers providing
overviews of CS were included only when provided insight into technology-related
user issues [e.g. Newman, Wiggins et al., 2012; Wiggins and Crowston, 2011].
Also we included papers on user design suggestions even if the focus was not
entirely on a specific application [e.g. Jennett and Cox, 2014; Rotman et al., 2012].
Further application of the exclusion criteria resulted in 62 relevant articles suitable
for meta-analysis. It should be noted that the keyword combinations at this stage
vary with most popular being: “technology”, “environment”, “citizen science” and
“usability” (n=7), followed by “user experience” (n=6), “human-computer
interaction” (n=5) and user-centred design” (n=4). “Evaluation”, which was the
most popular keyword of initial search results, was the least popular amongst the
final list of articles (n=62). Nine results use the term “technology-mediated”, but
“technology” was the most popular term in this category. Publication dates range
from 2002 up to 2017, with the majority (n=55) unsurprisingly published after 2010.
The results include three reports, one dissertation thesis, 28 journal papers, 27
conference proceedings, with most of them being peer-reviewed (e.g. CHI, CSCW,
GI Forum), and three book chapters which are available online.
https://doi.org/10.22323/2.18010202 JCOM 18(01)(2019)A02 9
The final list includes several studies (n=18) where users are directly involved in
usability evaluations [e.g. R. Phillips et al., 2013; Kim, Mankoff and Paulos, 2013;
Jennett, Cognetti et al., 2016; D’Hondt, Stevens and Jacobs, 2013], co-design [e.g.
Fails et al., 2014; Bowser, Hansen, Preece et al., 2014] and user-centred design
processes [e.g. Woods and Scanlon, 2012; Newman, Zimmerman et al., 2010;
Michener et al., 2012; Fledderus, 2016], in contexts such as wildlife hazard
management [e.g. Ferster et al., 2013]; water management [e.g. Kim, Mankoff and
Paulos, 2013]; environment-focused CS games [e.g. Bowser, Hansen, He et al., 2013;
Bowser, Hansen, Preece et al., 2014; Prestopnik and Tang, 2015; Prestopnik,
Crowston and Wang, 2017]; species identification, reporting and classifications [e.g.
Newman, Zimmerman et al., 2010; Sharma, 2016; Jay et al., 2016]; and noise and
ecological monitoring [e.g. Woods and Scanlon, 2012; Jennett, Cognetti et al., 2016].
Some of these studies include an impressive number of user subjects; e.g. Luther
et al. [2009], in their evaluation of Pathfinder — a platform that enables CS
collaboration — include over 40 users and Bowser, Hansen, Preece et al. [2014] in a
co-design study for the development of Floracaching evaluated the application
with 58 users. Several other studies involve users through surveys and interviews
[e.g. Idris et al., 2016; Wald, Longo and Dobell, 2016; Eveleigh et al., 2014; Wiggins,
2013]; or other forms of user feedback such as online forums and discussions [e.g.
Wiggins, 2013; Sharples et al., 2015].
Methods used within the studies included personas and user scenarios to identify
user needs and requirements [e.g. Dunlap, Tang and Greenberg, 2013], and
heuristic evaluations to examine virtual CS applications [Wald, Longo and Dobell,
2016]. Other studies did not include users directly, but still provided insights on
user requirements, needs and other design issues from the design and
development of a specific application or by reviewing existing ones [e.g. Connors,
Lei and Kelly, 2012; Ferreira et al., 2011; Johnson et al., 2015; Newman, Wiggins
et al., 2012; Stevens et al., 2014; Kosmala et al., 2016].
Six categories were created to inform the meta-analysis. The categories, created in
agreement by two of this paper’s authors who analysed the data and they were
designed to effectively group key design features and which include: Basic features
and design recommendations (e.g. homepage; registration); Design for Communication
Functionality (i.e. functionality that supports communication between users such as
activity updates, comments, likes, forums, links to social media etc); Design for Data
Collection;Design for Data Processing and Visualisation;Gamification Features;User
Privacy Issues (e.g. setting various levels of access in the collected data). In section 5
we present and discuss the guidelines in detail, as these were influenced by the CE.
Cooperative Evaluation (CE)
In the CE experiments, participants were given a set of tasks and explored features
from the same six categories that we described in the previous section as discussed
in section3.2. Here, we briefly present some general observations with respect
to each one of the three applications. Additional findings that informed the
guidelines are discussed more extensively in section 5 where we discuss the
guidelines in more detail.
https://doi.org/10.22323/2.18010202 JCOM 18(01)(2019)A02 10
Table 2. Summary of design features and content identified by participants in each of the
three applications examined with the method of CE.
iSpot website iNaturalist app Zooniverse website
Most
Useful/usable
features
Information content;
external links; termin-
ology; data collection
formats
Search by location;
search autocomplete
function; data collec-
tion formats
Projects page — cat-
egorisation tabs
Least useful/
least usable
features
Filtering on main page;
lack of mobile app for
data collection; locat-
ing & filtering the map
Search function; help
page and tutorials
News page hard to
read; distracting colour
and small font size;
Controversial
amongst
participants
features
Social media login fea-
ture
Opening pages in
new/same window’;
use of back button
Suggestions Forums and help pages
separate menu items;
main page’s filtering
should accommod-
ate needs of global
community;
introduce ‘expert
status’
Homepage of the mo-
bile app to contain
links to news and
external articles;
Tab to check notifica-
tions; place search tab
on top of the screen; ap-
plication zooms to the
new observation point
added
Newsfeed to resemble
that of Facebook’s lay-
out; ‘talk’ tab to be re-
named to ‘forum’; skip
tutorial option
iSpot. Participants appreciated the fact that the main iSpot’s homepage is
informative and contains links to news articles and educational material.
Nonetheless, participants suggested that the main page should not be organised by
‘communities’, neither it should show content based on user’s ‘location’. They
recommended that end users should have control of such filtering options so that it
is more open towards its global community. Logging in using social media was
quite controversial (“It’s a nice feature. . .I don’t need to remember another password”;“It
depends on the permission settings, because I don’t like having to change all the permission
settings on Facebook” user comments). Participants also liked features for entering
data in various formats, and the concurrent use of both scientific and lay
vocabulary to explain species identification. Problematic features included finding
the interactive map, filtering the map results and the lack of a search by location
function. CE participants were not interested in the badges award feature, although
they expressed greater trust levels to data contributed by volunteers with badges.
They suggested that an ‘expert status’ feature which takes into account skills and
professional qualifications would be more effective in this respect.
iNaturalist.org. Participants found the ‘search by location’ function particularly
useful; tutorials and help pages and the search function were hard to locate and
participants suggested that these should be located on the top of the screen. Users
were not interested in communication features (“Everybody just uses Facebook
messenger” user comment) and gamification features. Participants suggested that a
feature similar to that provided by Facebook to check notifications would improve
the user experience, as well as external links to news or relevant articles from the
mobile app’s homepage. The fact there is no legend provided caused frustration.
Participants further suggested that once a new data point is added the application
should zoom in on this observation automatically.
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Zooniverse. Participants appreciated external links and the news stories, yet they
found the page hard to read and suggested it should be reorganised to resemble
that used of Facebook. They disliked the orange colour on the background of the
headings and the small font size. They did not immediately understand the
purpose of the ‘talk’ feature, and when they did, they suggested it should be
renamed to ‘forum’. With respect to tutorials, participants suggested that pop-ups
work best (“Nobody has the time to watch a video” participant comment) and that a
skip option should be provided. Communication and gamification features were
again not highly rated, yet one participant commented in his think aloud “what do
I get with my points?”, and suggested that such a gamification feature would only
make sense if users are truly awarded with something in return (e.g. zoo vouchers).
Designing for
citizen science:
design guidelines
Basic features and design recommendations
General interface design should follow popular name and navigation conventions (e.g.
‘forum’ instead of ‘talk’). Both CE experiments and the SLR meta-analysis [e.g. see
Teacher et al., 2013; Kim, Mankoff and Paulos, 2013] agree that the project’s main
page should contain information about: project description; data collected; project
outcomes; and links to news and external links for additional information.
Providing a news section, according to articles reviewed, serves as a motivation
incentive feature [Eveleigh et al., 2014] and its design should follow name
conventions, as suggested by the majority of our participants and the SLR [e.g.
McCarthy, 2011]. A forum should be provided as separate menu item to support
volunteers collate and respond to feedback, offer their suggestions and support, as
well as for social interaction purposes [Woods, McLeod and Ansine, 2015; Wald,
Longo and Dobell, 2016]. Similarly, a help page should be provided as a separate
menu item, a suggestion made by our participants, which is also in line with other
guidelines [e.g. Skarlatidou, Cheng and Haklay, 2013].
Registration is a common feature that many studies discuss, with a growing number
of applications providing the option to sign up using social media [e.g. Dunlap,
Tang and Greenberg, 2013; Ellul, Francis and Haklay, 2011; Wald, Longo and
Dobell, 2016]. Jay et al. [2016] demonstrated that “it is possible to increase
contributions to online citizen science by more than 60%, by allowing people to participate
in a project without obliging them to officially sign up” (p. 1830). Participants in our
study expressed their support towards the social media login function.
Nevertheless they were concerned with changes in permission settings in their
social media accounts. We thus suggest that sign up using social media should not be
the only option and that a registration page is also provided. Several of the articles in the
SLR discuss that CS technologies should provide tutorials in various forms (e.g.
textual, videos) [Yadav and Darlington, 2016; Dunlap, Tang and Greenberg, 2013;
Stevens et al., 2014; Kim, Mankoff and Paulos, 2013; Prestopnik and Crowston,
2012, etc]. Our participants recommended that tutorials should be provided using
pop-up functionality (which highlight relevant features) with the option to skip them
and/or allow to return at some later point in time. Photographs in tutorials should be
used to communicate scientific objects of interest [e.g. see Dunlap, Tang and
Greenberg, 2013].
Overall interface design should also take into account cultural and environmental
characteristics. There is, for example, a growing number of studies in CS which
https://doi.org/10.22323/2.18010202 JCOM 18(01)(2019)A02 12
investigate how such technologies should be designed to support data collection by
illiterate or semi-literate people [Stevens et al., 2014; Liebenberg et al., 2017; Vitos
et al., 2017; Idris et al., 2016; Jennett, Cognetti et al., 2016]. Studies from this context
suggest early engagement with end users, placing the user at the centre of the
design and development lifecycle, removing any form of text from user interfaces,
and so on [Idris et al., 2016]. Also, several of these applications are designed to be
used in remote areas and/or the outdoors (e.g. in the forest, parks or recreation
areas). Therefore, the design of buttons should be usually larger than in standard
application design and the screen lighting and battery life should be tested separately
[Ferster et al., 2013; Stevens et al., 2014; Vitos et al., 2017].
Design for communication functionality
The SLR articles emphasise the importance of providing (real-time) communication
functionality [e.g. see Newman, Wiggins et al., 2012; Wald, Longo and Dobell, 2016;
Fails et al., 2014; Woods, McLeod and Ansine, 2015] to support communication
amongst volunteers, or between volunteers and the scientists, to retain volunteers,
and to communicate further information about how the data are used or will be
used. The latter has been discussed within the context of trust-building, for
example, its potential for increasing confidence in the project and corresponding
scientists [Ferster et al., 2013]. Map tagging and adding comments on map have also
been suggested, together with chats and forums [Dunlap, Tang and Greenberg,
2013]. CE participants showed no preference towards the inclusion of a chat
function but they all thought that a forum page adds value. Nevertheless, it should
be acknowledged that the artificial experimental setting of CE is perhaps not
appropriate to fully appreciate the benefits in the same way that actual volunteers
experience this feature. Furthermore, communication functionality depends on the
nature of the project, its geographical extent, and other attributes, and we therefore
suggest that these are all taken into account when designing for communication in
CS applications.
Design for data collection
Data collection is perhaps the most widely discussed feature. The SLR articles
provide suggestions for: real-time data collection [e.g. Panchariya et al., 2015];
supporting de-anonymisation from sharing data with close friends and other groups
[e.g. Fails et al., 2014; Maisonneuve, Stevens, Niessen et al., 2009]; enabling the
collection of user’s GPS location data [e.g. Maisonneuve, Stevens and Ochab, 2010;
Kim, Mankoff and Paulos, 2013], only if it is of high accuracy, otherwise users can
become frustrated/confused [Bowser, Hansen, He et al., 2013]; the ability to collect
various data types such as numbers, videos, photographs, text, coordinates [Ellul, Francis
and Haklay, 2011]; the ability to combine various data types derived from various
sources, which requires a good understanding of the types of data that are useful in
the specific project [e.g. Wehn and Evers, 2014; Kim, Mankoff and Paulos, 2013];
and the ability to add qualitative data to observations [Maisonneuve, Stevens and
Ochab, 2010], which is an attribute that it is very popular amongst the SLR articles.
Adding a photograph to showcase the observation captured can be a significant trust cue (as
noted previously, it may also support the development of data validation
mechanisms) [e.g. see Kim, Mankoff and Paulos, 2013].
https://doi.org/10.22323/2.18010202 JCOM 18(01)(2019)A02 13
In terms of design, form design should be simple to improve accessibility [e.g. see
Prestopnik and Crowston, 2012]; the use of images and drop-down lists can improve
the time required to enter data and should be preferred over text [Idris et al., 2016],
especially in mobile devices. When users are not required to fill in all data fields make
sure they understand this, thus preventing them entering incorrect data [Woods and
Scanlon, 2012]. Data collection supported by showing the location of the user (using
GPS tracking) in the application (mapping interface), should use symbology that
stands out from base map [e.g. Dunlap, Tang and Greenberg, 2013]. Moreover, the
provision of additional reference points shown on the map help users validate the data they
collect [Kim, Mankoff and Paulos, 2013]. When possible, allow for data tailoring and
personalisation to improve motivation [Sullivan et al., 2009]. In some contexts, the
submission of high quality images is absolutely essential (e.g. in species
identification), however, the handsets that users are equipped with might not
support zooming to the required level [Jennett, Cognetti et al., 2016]. In this case,
we suggest that users should be made aware of their handset limitations well in advance,
before they contribute any data.
In conditions where there is limited (or no) Internet access, scholars emphasise the
importance of collecting data offline, storing them and uploading them automatically once
a connection is established [Stevens et al., 2014; Fails et al., 2014; Bonacic, Neyem and
Vasquez, 2015; Kim, Robson et al., 2011]. We also suggest that, within specific
contexts of use, developers should consider the benefit of providing effective data
validation functionality when new data are being submitted [e.g. averaging data
records, flag errors and provide feedback to the user to correct errors, ask users to
inspect data to throw out outliers/check data accuracy, view redundant data
collected by others and decide whether it is helpful etc., as in Dunlap, Tang and
Greenberg, 2013], as it can improve the quality of data and user trust in the data. A
feature explicitly mentioned in the CE sessions by several participants is the
feedback provision to notify volunteers when a new observation has been
submitted.
Design for data processing and visualisation
Features relevant to data processing and visualisation include: a data sharing and
viewing website and mobile application to see the data collected instantly, preferably on a
map but other visualisations are also suggested, e.g. tables [Kim, Mankoff and
Paulos, 2013; Woods, McLeod and Ansine, 2015; Maisonneuve, Stevens, Niessen
et al., 2009]; a search function with autocomplete capabilities [Yadav and Darlington,
2016; Ellul, Francis and Haklay, 2011]; search by location [e.g. Sullivan et al., 2009;
Elwood, 2009]; and filter data on the map using different variables [Kim, Mankoff and
Paulos, 2013]. Other features include: map zooming and panning tools [Higgins et al.,
2016; Kar, 2015]; the ability to switch between different map backgrounds, especially in
applications on mobile devices to save battery life and conserve on data
consumption; and the ability to read details of data collected while browsing the map
interfaces, e.g. using a hover text showing details for each data pin [e.g. in Kim,
Mankoff and Paulos, 2013]. When observations on a map are linked to other
information on other parts of the interface (e.g. textual information or graphs on
the site) provide visual cues for the user to understand association [Fledderus, 2016].
https://doi.org/10.22323/2.18010202 JCOM 18(01)(2019)A02 14
Gamification features
Gamification is popular in CS literature for its potential to motivate users and
increase numbers of contributions. Therefore several studies explore the use of
badges, awards or leaderboards to incentivise users and keep them active [e.g.
Prestopnik and Crowston, 2012; Newman, Wiggins et al., 2012; Crowley et al., 2012;
Panchariya et al., 2015; Bowser, Hansen, He et al., 2013; Bowser, Hansen, Preece
et al., 2014; Wald, Longo and Dobell, 2016]. Nevertheless, studies acknowledge that
gamification might not be such a significant motivation factor in terms of collecting
scientific data [e.g. one of the participants in Bowser, Hansen, Preece et al., 2014,
mentions that “contributing to science. . .that’s kind of motivating to me” p. 139]
[Preece, 2016; Prestopnik, Crowston and Wang, 2017], which is in line with the
results of our CE. Preliminary evidence suggests that leaderboards, rating systems
and treasure hunting type of game features might improve user experience of CS
applications [e.g. see Bowser, Hansen, Preece et al., 2014]. The option to skip the use
of gamification features is also strongly recommended [Bowser, Hansen, Preece et al.,
2014], so that volunteers do not have to deal with the competitive part of a
gamified application if they don’t want to [Preece, 2016].
CE participants suggested that gamification would not make them contribute more
data and that an option to opt out is essential. They also suggest that gamification
features would be more effective if they lead to tangible outcomes (i.e. non-diegetic
reward features, such as sponsorships from local organisations for vouchers
to participate in CS activities and events). This is congruent with the wider
gamification literature, where point systems and leaderboards, although once
addictive features, are being replaced by experience-based gamification features
[McCarthy, 2011]. Other features such as badges or ‘expert’ status, may also help to
tackle trust concerns in the same way that reputation systems, seals of approval, and
other trust cues are discussed in other contexts such as online shopping, education
and even Web GIS [Dellarocas, 2010; Skarlatidou, Cheng and Haklay, 2013].
User privacy issues
The articles of our meta-analysis make extensive reference to privacy issues and con-
cerns [e.g. R. D. Phillips et al., 2014; Kim, Mankoff and Paulos, 2013; Preece, 2016].
Filtering, moderation, ensuring that the data stored do not support identification of indi-
viduals and providing the option to collect data without sharing it are some of the options
that are suggested in the SLR as potential solutions [e.g. Ferster et al., 2013; Leao,
Ong and Krezel, 2014; Maisonneuve, Stevens, Niessen et al., 2009]. Anonymity (via
the option to contribute without registration/signature) has been also suggested to
address privacy concerns [e.g. Dale, 2005] and improve participation. Nevertheless,
it is suggested by existing studies that applications should be designed with attribu-
tion, which improves volunteers’ trust, and therefore anonymity should not always
be encouraged [e.g. Luther et al., 2009]. In the CE experiments only five participants
expressed privacy concerns and they suggested that complying with security standards
and offering the ability to change privacy settings would definitely be beneficial.
https://doi.org/10.22323/2.18010202 JCOM 18(01)(2019)A02 15
Conclusions and
future work
The research carried out demonstrates the current trends and main design
considerations, as suggested in user-related research and user testing findings,
within the environmental digital CS context. It resulted in design guidelines
which developers in CS can follow to improve their designs. Likewise, they
can also be used to inform future research, for example, addressing methodological
implications of the methods employed herein, as well as extending this work further.
The SLR was a time-consuming process given the extensive number of keywords,
however it resulted in the identification of a satisfactory number of resources to
include in the meta-analysis study. It should be noted that user research in the
context of CS is in its infancy, and therefore many of the studies were making
suggestions based on the authors’ experiences rather than on hard evidence
derived from the involvement of actual users. Nevertheless, we were also
impressed by the number of studies which did involve users in evaluation, UCD
practices, or simply in capturing user needs and requirements. We acknowledge
the fact that a significant number of studies (i.e. n = 7,169) were removed due to
language barriers. Although this sample was not further processed to assess its
relevance it still may poses a limitation and therefore a future study that aims at
investigating non-English research studies could significantly contribute to the
proposed design guidelines for digital CS applications. Overall we suggest that
wider communication of findings, preferably in more than one languages, will
inspire more CS practitioners and researchers to involve end users in the design
process, thus significantly improving the usability and user experience of CS
applications. Moreover, the SLR described focuses only on the environmental
context. Thus, our preliminary findings can be extended by further analysing
similar studies in other contexts of digital CS.
The second limitation arises from the CE implementation, which involved 15 users.
Although this sample provided us with enough insight into the proposed
guidelines, increasing the number of applications tested and the number of users
involved in CE could provide more in-depth insight to significantly improve the
proposed guidelines. Introducing a set of recruitment criteria to inform user
participation in any future studies may also extend the usefulness of our approach.
For example, repeating the experiments with two groups of participants (i.e. users
with some or significant experience in the use of CS applications and users who
never used CS applications) can improve our understanding around user issues
and corresponding design features that are important in terms of both attracting
new users as well as retaining them. Similarly, participants of specific age groups,
cultural backgrounds and especially those who speak languages other than English
may help uncover more user issues which may be applicable to all or to specific
design categories (e.g. gamification features and communication functionality) and
contribute to the establishment of a more inclusive set of guidelines. Considering
the current state of research in this area, we also suggest that any user testing
focuses on additional user experience elements to understand not only usability or
volunteer retainment, but also issues surrounding communication, privacy and
improving trust via interface design.
Finally, the proposed guidelines can inform the design and development of
environmental design CS applications and several of the guidelines are in line with
similar work within the broader digital CS context [e.g. Sturm et al., 2018]. It
should be however acknowledged that guidelines cannot replace contextual and
https://doi.org/10.22323/2.18010202 JCOM 18(01)(2019)A02 16
environmental considerations. We therefore propose that user studies are
fully-integrated in citizen science, especially with respect to its technological
implementations, in terms of understanding user issues that are relevant to specific
contexts of use. The wider CS community can further benefit from the
communication of user-based research in terms of not only improving our
knowledge and understanding of what users want, but also in terms of providing
the methodological protocols that others can easily replicate for exploring user
issues in various contexts of use.
Acknowledgments This research project is funded by European Research Council’s project Extreme
Citizen Science: analysis and Visualisation under Grant Agreement No 694767 and
it has the support of the European Union’s COST Action CA15212 on Citizen
Science to promote creativity, scientific literacy, and innovation throughout Europe.
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https://doi.org/10.22323/2.18010202 JCOM 18(01)(2019)A02 22
Authors Artemis Skarlatidou is a postdoctoral researcher in the Extreme Citizen Science
(ExCites) group at UCL. She is chairing WG4 of the COST Action on citizen science
CA15212 and co-chairing the ICA Commission on Use, User and Usability Issues.
Her research interests include HCI and UX aspects (e.g. usability, aesthetics, trust)
of geospatial technologies and especially of Web GIS representations for expert and
public use and citizen science applications. She is also interested in trust issues
within the context of VGI and PPGIS; philosophical, as well as, ethical issues for the
‘appropriate’ and effective use of geospatial and citizen science technologies.
E-mail: a.skarlatidou@ucl.ac.uk.
Born and raised in the United States, Alexandra Hamilton moved to Europe with
her family at the age of 14. After completing school in Brussels, Belgium she then
obtained her BSc in Geography and Education Studies from Oxford Brookes
University in 2016. Shortly after, in 2017, she was awarded her MSc in Geospatial
Analysis from the University College London. Interested in the application of
geospatial analytics within the social sciences, Alexandra hopes to commence her
Ph.D. in the fall of 2019. E-mail: alexandra.hamilton.16@ucl.ac.uk.
Michalis Vitos is a postdoctoral researcher in the Extreme Citizen Science (ExCites)
group at UCL. His research interests include the areas of Human-Computer
Interaction and Software Engineering in combination with the emerging area of
Participatory GIS and Citizen Science. E-mail: michalis.vitos@ucl.ac.uk.
Muki Haklay is a professor of GIScience and the director of the Extreme Citizen
Science (ExCites) group at UCL. His research interests include public access to
environmental information and the way in which the information is used by a wide
range of stakeholders, citizen science and in particular applications that involve
community-led investigation, development and use of participatory GIS and
mapping, and Human-Computer Interaction (HCI) for geospatial technologies.
E-mail: m.haklay@ucl.ac.uk.
Skarlatidou, A., Hamilton, A., Vitos, M. and Haklay, M. (2019). ‘What do volunteersHow to cite
want from citizen science technologies? A systematic literature review and best
practice guidelines’. JCOM 18 (01), A02. https://doi.org/10.22323/2.18010202.
c
The Author(s). This article is licensed under the terms of the Creative Commons
Attribution — NonCommercial — NoDerivativeWorks 4.0 License.
ISSN 1824-2049. Published by SISSA Medialab. jcom.sissa.it
https://doi.org/10.22323/2.18010202 JCOM 18(01)(2019)A02 23
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