Understanding citizen science and environmental monitoring: final report on behalf of UK Environmental Observation Framework

Citizen science can broadly be defined as the involvement of volunteers in science. Over the past decade there has been a rapid increase in the number of citizen science initiatives. The breadth of environmental-based citizen science is immense. Citizen scientists have surveyed for and monitored a broad range of taxa, and also contributed data on weather and habitats reflecting an increase in engagement with a diverse range of observational science. Citizen science has taken many varied approaches from citizen-led (co-created) projects with local community groups to, more commonly, scientist-led mass participation initiatives that are open to all sectors of society. Citizen science provides an indispensable means of combining environmental research with environmental education and wildlife recording. Here we provide a synthesis of extant citizen science projects using a novel cross-cutting approach to objectively assess understanding of citizen science and environmental monitoring including: 1. Brief overview of knowledge on the motivations of volunteers. 2. Semi-systematic review of environmental citizen science projects in order to understand the variety of extant citizen science projects. 3. Collation of detailed case studies on a selection of projects to complement the semi-systematic review. 4. Structured interviews with users of citizen science and environmental monitoring data focussing on policy, in order to more fully understand how citizen science can fit into policy needs. 5. Review of technology in citizen science and an exploration of future opportunities

Cyber–Physical–Social Frameworks for Urban Big Data Systems: A Survey

The integration of things’ data on the Web and Web linking for things’ description and discovery is leading the way towards smart Cyber–Physical Systems (CPS). The data generated in CPS represents observations gathered by sensor devices about the ambient environment that can be manipulated by computational processes of the cyber world. Alongside this, the growing use of social networks offers near real-time citizen sensing capabilities as a complementary information source. The resulting Cyber–Physical–Social System (CPSS) can help to understand the real world and provide proactive services to users. The nature of CPSS data brings new requirements and challenges to different stages of data manipulation, including identification of data sources, processing and fusion of different types and scales of data. To gain an understanding of the existing methods and techniques which can be useful for a data-oriented CPSS implementation, this paper presents a survey of the existing research and commercial solutions. We define a conceptual framework for a data-oriented CPSS and detail the various solutions for building human–machine intelligence

Practicable Soundmapping: JavaScript enabled Edge Compute

In this paper, we report on developments of the Citygram, a comprehensive sensor network platform for capturing, streaming, analyzing, mapping, visualizing, and providing easy access to spatiotemporal soundscape data. Launched in 2011, Citygram’s recent strategic decision has resulted in system redesign to enable migration from a codebase built on multiple computer languages to a cross-platform single JavaScript codebase. Citygram now runs on V8 engines including standard web-browsers and in the node.js environment. The Citygram sensor network significantly alleviates problems concerning soundmapping complexities including operating system limitations, hardware dependency, software update and dissemination issues, data access mechanism, data visualization, and cost. This strategy has made practicable a key design philosophy for soundmapping: rapid sensor network growth for capturing spatiotemporally granular soundscapes. We summarize research and development for the following Citygram modules (1) cost-effective sensor module allowing high-value data transmission through edge compute paradigms, (2) machine learning module focusing on environmental sound classification, and (3) visualization and data access prototypes

Integrating big data into a sustainable mobility policy 2.0 planning support system

It is estimated that each of us, on a daily basis, produces a bit more than 1 GB of digital content through our mobile phone and social networks activities, bank card payments, location-based positioning information, online activities, etc. However, the implementation of these large data amounts in city assets planning systems still remains a rather abstract idea for several reasons, including the fact that practical examples are still very strongly services-oriented, and are a largely unexplored and interdisciplinary field; hence, missing the cross-cutting dimension. In this paper, we describe the Policy 2.0 concept and integrate user generated content into Policy 2.0 platform for sustainable mobility planning. By means of a real-life example, we demonstrate the applicability of such a big data integration approach to smart cities planning process. Observed benefits range from improved timeliness of the data and reduced duration of the planning cycle to more informed and agile decision making, on both the citizens and the city planners end. The integration of big data into the planning process, at this stage, does not have uniform impact across all levels of decision making and planning process, therefore it should be performed gradually and with full awareness of existing limitations

Characteristics of Citizen-contributed Geographic Information

Ponencias, comunicaciones y pósters presentados en el 17th AGILE Conference on Geographic Information Science "Connecting a Digital Europe through Location and Place", celebrado en la Universitat Jaume I del 3 al 6 de junio de 2014.Current Internet applications have been increasingly incorporating citizen-contributed geographic information (CCGI) with much heterogeneous characteristics. Nevertheless, despite their differences, several terms are often being used interchangeably to define CCGI types, in the existing literature. As a result, the notion of CCGI has to be carefully specified, in order to avoid vagueness, and to facilitate the choice of a suitable CCGI dataset to be used for a given application. To address the terminological ambiguity in the description of CCGI types, we propose a typology of GI and a theoretical framework for the evaluation of GI in terms of data quality, number and type of contributors and cost of data collection per observation. We distinguish between CCGI explicitly collected for scientific or socially-oriented purposes. We review 27 of the main Internet-based CCGI platforms and we analyse their characteristics in terms of purpose of the data collection, use of quality assurance and quality control (QA/QC) mechanisms, thematic category, and geographic extents of the collected data. Based on the proposed typology and the analysis of the platforms, we conclude that CCGI differs in terms of data quality, number of contributors, data collection cost and the application of QA/QC mechanisms, depending on the purpose of the data collection

Nudging lifestyles for better health outcomes: crowdsourced data and persuasive technologies for behavioural change

For at least three decades, a Tsunami of preventable poor health has continued to threaten the future prosperity of our nations. Despite its effective destructive power, our collective predictive and preventive capacity remains remarkably under-developed This Tsunami is almost entirely mediated through the passive and unintended consequences of modernisation. The malignant spread of obesity in genetically stable populations dictates that gene disposition is not a significant contributor as populations, crowds or cohorts are all incapable of experiencing a new shipment of genes in only 2-3 decades. The authors elaborate on why a supply-side approach: advancing health care delivery cannot be expected to impact health outcomes effectively. Better care sets the stage for more care yet remains largely impotent in returning individuals to disease-free states. The authors urge an expedited paradigmatic shift in policy selection criterion towards using data intensive crowd-based evidence integrating insights from system thinking, networks and nudging. Collectively these will support emerging potentialities of ICT used in proactive policy modelling. Against this background the authors proposes a solution that stated in a most compact form consists of: the provision of mundane yet high yield data through light instrumentation of crowds enabling participative sensing, real time living epidemiology separating the per unit co-occurrences which are health promoting from those which are not, nudging through persuasive technologies, serious gaming to sustain individual health behaviour change and intuitive visualisation with reliable simulation to evaluate and direct public health investments and policies in evidence-based waysJRC.DDG.J.4-Information Societ

A review of Citizen Science within the Earth Sciences: potential benefits and obstacles

The field of citizen science is a rapidly evolving type of scientific research focussing on the collaboration of motivated volunteers (citizen scientists) with professional scientists to generate new knowledge and information. In recent years, there has been a steady growth of Earth Science related citizen science projects that aim to build knowledge, awareness and ultimately resilience to key local- to global-scale environmental issues (e.g., geohazards, environmental monitoring). In addition, there has also been progression from small pilot studies to large data collection Earth Science citizen science initiatives that are used to underpin modelling. However, despite this, numerous operational and strategic challenges exist and whilst the awareness of citizen science has improved markedly, it is clear that the direct impact of citizen science on policy and decision making is still limited. Within this paper, we review these challenges alongside defining citizen science itself, and its benefits. The range of methods and applications of citizen science are explored through a series of case studies centred on geohazards, observations & classification, multi-topic, and education/outreach. The paper also explores future citizen science opportunities within Earth Science