Usability engineering for GIS: learning from a screenshot

In this paper, the focus is on the concept of Usability Engineering for GIS – a set of techniques and methods that are especially suitable for evaluating the usability of GIS applications – which can be deployed as part of the development process. To demonstrate how the framework of Usability Engineering for GIS can be used in reality, a screenshot study is described. Users were asked to provide a screenshot of their GIS during their working day. The study shows how a simple technique can help in understanding the way GIS is used in situ

Public Web Mapping: preliminary usability evaluation

April 5 - 7, 200

Zooming to the study area in GIScience research: a three stage approach

6-8 Apri

Citizen science impact pathways for a positive contribution to public participation in science

Positioning citizen science within the broader historical public engagement framework demonstrates how it has the potential to effectively tackle research and innovation issues. Citizen science approaches have their own challenges, which need to be considered in order to achieve this aim and contribute to wider and deeper public engagement. However, programme evaluations, which discuss lessons learned in engaging the public and other stakeholders with science are rare. To address this gap, we present the H2020-funded DITOs project and discuss the use of logic models in citizen science. We share the project’s assumptions, design considerations for deeper engagement and its impact pathways demonstrating how logic models can be utilised in citizen science to monitor programme effectiveness and for their successful implementation. We hope that this work will inspire citizen science practitioners to use similar tools and by doing so, share their experiences and potential barriers. This knowledge is essential for

The Impact of Biases in the Crowdsourced Trajectories on the Output of Data Mining Processes

The emergence of the Geoweb has provided an unprecedented capacity for generating and sharing digital content by professional and non- professional participants in the form of crowdsourcing projects, such as OpenStreetMap (OSM) or Wikimapia. Despite the success of such projects, the impacts of the inherent biases within the ‘crowd’ and/or the ‘crowdsourced’ data it produces are not well explored. In this paper we examine the impact of biased trajectory data on the output of spatio-temporal data mining process. To do so, an experiment was conducted. The biases are intentionally added to the input data; i.e. the input trajectories were divided into two sets of training and control datasets but not randomly (as opposed to the data mining procedures). They are divided by time of day and week, weather conditions, contributors’ gender and spatial and temporal density of trajectory in 1km grids. The accuracy of the predictive models are then measured (both for training and control data) and biases gradually moderated to see how the accuracy of the very same model is changing with respect to the biased input data. We show that the same data mining technique yields different results in terms of the nature of the clusters and identified attributes

How Does Policy Conceptualise Citizen Science? A Qualitative Content Analysis of International Policy Documents

Policy and science show great interest in citizen science as a means to public participation in research. To recognize how citizen science is perceived to foster joint working at the science-society-policy interface, a mutual understanding of the term “citizen science” is required. Here, we assess the conceptualisation and strategic use of the term “citizen science” in policy through a qualitative content analysis of 43 international policy documents edited by governments and authorities. Our results show that most documents embrace the diversity of the research approach and emphasize the many benefits that citizen science may provide for science, society, and policy. These include boosting spatio-temporal data collection through volunteers, tapping into distributed knowledge domains, increasing public interest and engagement in research, and enhancing societal relevance of the respective research. In addition, policy documents attribute educational benefits to citizen science by fostering scientific literacy, individual learning, and skill development, as well as by facilitating environmental stewardship. Through active participation, enhanced ownership of research results may improve policy decision-making processes and possibly democratise research as well as public policy processes, although the latter is mentioned only in a few European Union (EU) documents. Challenges of citizen science mentioned in the analysed policy documents relate mainly to data quality and management, to organisational and governance issues, and to difficulties of the uptake of citizen science results into actual policy implementation due to a lack of citizen science alignment with current policy structures and agendas. Interestingly, documents largely fail to address the benefits and challenges of citizen science as a tool for policy development, i.e., citizen science is mainly perceived as only a science tool. Overall, policy documents seem to be influenced strongly by the citizen science discourse in the science sector, which indicates a joint advocacy for citizen science

Nothing about us without us: A co-production strategy for communities, researchers and stakeholders to identify ways of improving health and reducing inequalities

Introduction: Co-production with communities is increasingly seen as best practice that can improve the quality, relevance and effectiveness of research and service delivery. Despite this promising position, there remains uncertainty around definitions of co-production and how to operationalize it. The current paper describes the development of a co-production strategy to guide the work of the ActEarly multistakeholder preventative research programme to improve children's health in Bradford and Tower Hamlets, UK. Methods: The strategy used Appreciative Inquiry (AI), an approach following a five-step iterative process: to define (Step 1) scope and guide progress; to discover (Step 2) key issues through seven focus groups (N = 36) and eight in-depth interviews with key stakeholders representing community groups, and the voluntary and statutory sectors; to dream (Step 3) best practice through two workshops with AI participants to review findings; to design (Step 4) a co-production strategy building on AI findings and to deliver (Step 5) the practical guidance in the strategy. Results: Nine principles for how to do co-production well were identified: power should be shared; embrace a wide range of perspectives and skills; respect and value the lived experience; benefits should be for all involved parties; go to communities and do not expect them to come to you; work flexibly; avoid jargon and ensure availability of the right information; relationships should be built for the long-term; co-production activities should be adequately resourced. These principles were based on three underlying values of equality, reciprocity and agency. Conclusion: The empirical insights of the paper highlight the crucial importance of adequate resources and infrastructure to deliver effective co-production. This documentation of one approach to operationalizing co-production serves to avert any misappropriations of the term ‘co-production’ by listening to service users, stakeholders and other relevant groups, to develop trust and long-term relationships, and build on the learning that already exists amongst such groups. Patient or Public Contribution: The work was overseen by a steering group (N = 17) of individuals, both professional and members of the public with experience in undertaking co-production, and/or with some knowledge of the context of the two ActEarly field sites, who provided regular oversight and feedback on the AI process

Temporal Analysis of Activity Patterns of Editors in Collaborative Mapping Project of OpenStreetMap

In the recent years Wikis have become an attractive platform for social studies of the human behaviour. Containing millions records of edits across the globe, collaborative systems such as Wikipedia have allowed researchers to gain a better understanding of editors participation and their activity patterns. However, contributions made to Geo-wikis_wiki-based collaborative mapping projects_ differ from systems such as Wikipedia in a fundamental way due to spatial dimension of the content that limits the contributors to a set of those who posses local knowledge about a specific area and therefore cross-platform studies and comparisons are required to build a comprehensive image of online open collaboration phenomena. In this work, we study the temporal behavioural pattern of OpenStreetMap editors, a successful example of geo-wiki, for two European capital cities. We categorise different type of temporal patterns and report on the historical trend within a period of 7 years of the project age. We also draw a comparison with the previously observed editing activity patterns of Wikipedia.Comment: Submitte

Citizen science and Post-Normal Science's extended peer community: Identifying overlaps by mapping typologies

At first sight, citizen science – the opening of scientific enterprise to a wider group of people, many of whom are not professionally engaged in research institutions, seems to align well with the concept of an extended peer community of the framework of Post-Normal Science (PNS). PNS is concerned with the social robustness of applied science, science-based professional consultancy, and scientific advice for policy in situations of high stakes, high uncertainties, and contested values. Creating opportunities for engagement of citizens in science seems an obvious fit – but is that true for all diverse forms that citizen science can take? Current citizen science includes many types of activities and practices. As a result, the role of the participants within a given scientific knowledge production practice and their relation to scientists vary. This paper leverages the PNS framework to gain a more in-depth understanding of different ways in which diverse citizen science initiatives can contribute to improving the science-policy interface and provide tool sets and approaches for extended peer review, or not. For this purpose, this paper develops an analytic framework drawing on several widely used typologies of citizen science. The twenty four activities and practices of citizen science that they cover are mapped onto different zones of problem solving strategies – applied science, professional consultancy, and post-normal science, which are presented in the literature on PNS in terms of uncertainty and decision stakes while also noticing their value conflicts and urgency. The analysis shows that each of the four zones of scientific activities can be associated with citizen science initiatives. We deduce that citizen science is not automatically imbued with transformative potential, but that this potential depends on the purpose and design of the citizen science initiative. Certain types of citizen science activities and approaches are more relevant to researchers and practitioners with an interest in PNS who are actively seeking to reconfigure the science-policy-practice interface than others. This analytic framework and consequent mapping can support PNS practitioners in identifying the type of citizen science activities and designing fit-for-purpose initiatives. Moreover, the mapping exercise conveys a more nuanced understanding of different possible dimensions, merits, and limitations of the extended peer community concept. Similarly, for citizen science researchers and practitioners, the mapping of typologies within the three zones of problem solving strategies can allow a better selection of citizen science activities for those purposes

Bottom-up Environmental Justice in the UK: a fairer, greener London

April 17-21, 200