STATE-OF-THE ART STUDY IN CITIZEN

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STATE-OF-THE ART STUDY IN CITIZEN OBSERVATORIES: TECHNOLOGICAL TRENDS, DEVELOPMENT CHALLENGES

AND RESEARCH AVENUES

SYKE Timo Pyhälahti Yrjö Sucksdorff Saku Anttila Hanna Alasalmi Eeva Bruun Sofia Junttila LUT

Maria Palacin Silva Ahmed Seffah Kari Heikkinen Jari Porras

AUTHORS

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Lappeenranta University of Technology Department of Innovation and Software www.lut.fi

Address: Skinnarilankatu 34, 53850 Lappeenranta, Finland

Tel: +358 294 462 111 SYKE

Finnish Environment Institute www.syke.fi

Address: Mechelininkatu 34a

P.O.Box 140, FI-00251 Helsinki, Finland Legal Notice:

Neither the Lappeenranta University of technology nor the Finnish Environment Institute is responsible for the use which might be made of this publication.

Reproduction is authorized when the source is acknowledged.

Tel: +358 295 251 00

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List of Terms and Definitions

Participatory data collection: Users are actively involved in the collection process by deciding on the spot when to report data.

Opportunistic data collection: Sensor sampling occurs whenever the state of the device (e.g. geographic location) matches the application’s requirements described in a sensing task, without the knowledge of the individual phone user.

Spectrum monitoring (In this report):

 The entire range of wavelengths of electromagnetic radiation.

 Used to classify something in terms of its position on a scale between two extreme points.

BON: Biodiversity Observation Network LUKE: Natural Resources Institute Finland SYKE: Finnish Environment Institute LAJI: Finnish Biodiversity Info Facility

FinBIF: Finnish Biodiversity Information Facility LUOMUS: Finnish Museum of Natural History

Metadata: Data that provides information about other data. The main purpose of metadata is to facilitate in the discovery of relevant information, more often classified as resource discovery.

IoT: Internet of things

EnvO: Environment ontology

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Introduction

Citizen Science and Citizen Observatories:

Key Findings from a State of Art Review

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Citizen Science: The Original Definition and Objective

The term citizen science has been introduced and used to describe a range of ideas, from a philosophy of engaging in scientific research to the work of scientists, or even politicians, driven by a social needs or awareness. Citizen science represents massive scale collaboration in science as seen nowhere else, providing an opportunity for understanding aspects of other massively distributed collaborations (15). Originally, citizen science typically refers to research collaborations between scientists and volunteers, particularly (but not exclusively) to expand opportunities for scientific data collection and to provide access to scientific information for community members.

Citizen repositories emerged, first as the use of technology, to support this definition citizen science approach. In a broader definition, citizen repositories can be seen a platforms through which volunteers partner with scientists to answer real-world questions. This introductory chapter traces the evolution of citizens’ science and repositories in different domains, from natural science to sustainability development.

Citizen science has taken on several different meanings since it was coined in 1995. Many definitions exist about citizen science, making sometimes the concept very fuzzy. In a general sense, citizen science refers to the public participation in scientific activities and research projects related with environment and its biodiversity are taking advantage of new technologies such as internet and mobile phones with recording capabilities for an easy data collection and sharing (1).

We define citizen science as a range of collaborative activities between professional scientists and engaged laypeople (citizens) in the conduct of research(32). The key benefits of citizen science are (32):

 Citizen science is about citizen participation in research in order to provide a valuable resource for scientists

 Citizen science serves as a vehicle for public engagement, education, and outreach

 Citizen science aims to democratize the research process by giving laypeople a stake in the scientific issues of concern to them and their families

The basic idea of involving the public in data gathering has been termed ‘citizen science’ by natural scientists (e.g. ‘volunteered geographic information’ and ‘crowdsourcing geospatial data’ by geographers and ‘people-centric sensing’ and ‘participatory sensing’

by computer scientists(2). Participation approaches have progressed through a series of phases (Reed, 2008): awareness raising in the 1960s, incorporation of local perspectives in the 1970s, recognition of local knowledge in the 1980s, participation as a norm as part of the sustainable development agenda of the 1990s, subsequent critiques and recently a

‘post-participation’ consensus regarding best practice(3).

However, there is a difference between engaging the general public in a scientific project and entering an established expert community to conduct research(36). Research is underway extended the set engaged citizens to include other stakeholders. For example, diversity of vendor-designed “walled garden” repositories, ultimately repositioning individuals as producers, consumers, and remixes of a vast openly shared public data set.

By empowering people to easily measure, report, and compare their own personal environments, such tools transform everyday citizens into reporting agents who uncover and visualize unseen elements of their own everyday experiences (4).

ICT: The Birthday to a Second Generation of Citizen Repositories

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The fast growth of ICT of services, namely the pervasive computer devices and social networking, are driving the environment for democracy innovation and societal transformations at all levels of our society. Citizens are becoming more knowledgeable and demanding in their needs. Civic collaboration and participation has been increasing, strengthening the commitment to the common good and the democratic dynamics, where general interests prevail over individual interests (5)(6).The IoT (Internet of things) is making it possible that everyday things are now connected to the internet. This phenomena is changing the way we live, work and interact. This creates not only technological opportunities for smarter cities but also interactional opportunities for the citizens (7).

Fundamentally, ICT creates a new model of public service delivery, where those who have been normally targeted as passive end-users now tend to become collaborative co- producers, as an alternative, if not in substitution, for local public authorities; and to a next generation of urban smart citizenship, where those who have traditionally been considered as parts of the problem become effective agents of the most appropriate solution (6). This makes it that collective interventions due to global issues like climate change should not exclusively rely on global approaches, but can also be undertaken on smaller scales(8).

In 2006, participatory sensing (PS) is a distributed data collection and analysis approach where individuals, acting alone or in groups, use their personal mobile devices to systematically explore interesting aspects of their lives and communities(9). For example, users of Earth observations have a wide range of data requirements and priorities that depend on their specific applications. Some users need both basic datasets of directly observed phenomena and derived forecasts and products, while others utilize only a particular type of dataset. Users have varying technical sophistication levels, ranging from researchers who work with raw datasets, to intermediate users who utilize processed data products, to end users who employ highly processed products, tools, or forecasts. Earth observation users also span a wide range of sectors, including the public sector, the private sector, academia, and the media(10).

The recent emergence of low-cost, easy-to-use, portable micro-sensors for air pollution applications, provides a platform for making observations at a high spatial density (20).

‘Citizens’ Observatory as being the citizens themselves observing and understanding environment related problems and, particularly, reporting and commenting on them (20). Citizen observatories raise awareness, enabling dialogues, promote data exchange (22). Collaborative participation demands that the citizens not only consume information, but also provide it, leading to the joint production of knowledge (22). This is the essence of citizen repositories.

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Related Concepts to Citizen Science and Repositories

Citizen repositories is not the only concept that aims to engage citizens in something (research among others). The following are concepts that also count for citizen science or at least share the same goal, citizen participation.

Crowdsourcing

Crowdsourcing is a type of participative online activity in which an individual, an institution, a non-profit organization, or company proposes to a group of individuals of varying knowledge, heterogeneity, and number, via a flexible open call, the voluntary undertaking of a task. The user will receive the satisfaction of a given type of need, be it economic, social recognition, self-esteem, or the development of individual skills, while the crowd-sourcer will obtain and utilize to their advantage what the user has brought to the venture, whose form will depend on the type of activity undertaken”(11)(12). The use of crowdsourcing to improve the engagement of volunteers with Science is known as

‘citizen science’, ‘crowdsourcing for science’, ‘networked science’, or ‘crowd science’ (12).

Crowdsourcing is a growing area that is attracting attention from the academic community and the industry(12).

Thanks to the Internet, crowdsourcing is expanding its reach and establishing itself as a cheap and viable alternative for scientific work that was previously restricted to the limited capacity of professional teams (12). With more than half of the planet’s population residing in urban areas (38) and adapting to a lifestyle that demands more than meeting the basic needs of water, food and shelter, the promotion of an environmentally sustainable manner of living is becoming an important priority for policy makers and governments on a worldwide scale. Our everyday practices and interactions as city residents have consequences that reach beyond the quality of conditions in our immediate surroundings and furthermore, via complex processes, contribute, to some extent, to the environmental crisis (39).

Global debate

At the turn of the twenty-first century, we have become involved in a global debate about the nature and impact of climate change and our role as individuals and societies in managing this. To pursue this debate, we must address three key challenges. We need to gather information about the environment on a greater scale than ever before, including scientific measurements, documentation of local conditions and accounts of people’s behaviors. We need to inform debate by conveying environmental knowledge in new ways that engage the widest possible audience. Ultimately, we will also need to persuade people to change their behaviors(13).

E.Governance or the active participation of citizens in political issues

e.Governance aspires to utilize ICTs to transform government towards efficient, effective, and citizen-centric service delivery (14). Citizens also need the desire to exercise their rights and the political space to do so without unreasonable resistance or harassment from authorities or others. Citizen participation programs – including support of civic and voter education, get-out-the-vote efforts, issue organizing and advocacy, budget oversight and government monitoring – help citizens master the techniques needed to initiate action, solve complex problems and become leaders in their own right.

For more than 20 years, NDI has conducted programs to activate and empower citizens and civic groups, establish strong civic cultures and achieve an appropriate balance of power between citizens and government.

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Sociotechnical systems (STC)

STC environments are needed because cultures of participation are not dictated by technology; they are the result of changes in human behavior and social organization, in which active contributors engage in the innovative design, adoption, and adaptation of technologies to their needs and in collaborative knowledge construction(18). Water governance therefore consists of the processes of decision-making and definition of goals by a range of actors, while water management (and flood risk management more specifically) consists of targeted activities to attain such goals(3). The quality of the environment within urban areas is of vital importance. Urban and peri-urban growth is increasing, and Europe is now one of the most urbanized continents in the world. Today, more than two thirds of the European population lives in urban areas and this proportion continues to grow (20)

Once solely the province of academic, industrial and military scientists and engineers, robotics and sensing technologies are increasingly being used in commercial products and systems. But research on how such technologies might be used by non-experts in everyday settings is still nascent(19).

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Summary of Chapters and Key Findings

In chapter I, Trends in the World: Past, Present and Future, the findings from the 108 observatories are presented which were studied in depth to identify trends in the focuses, engagement techniques, technologies, practices, stakeholders, standards, limitations and recommendations.

The key findings of this chapter are the following:

 Remarkably, 69% of the identified world observatories have an environmental goal which involves species, water, streams, snow, sea, biodiversity, air, spectrum and global monitoring.

 The three domains that have most of the citizen observatories applications are: city management (25%), species (23%) and water, streams snow and sea monitoring (18%) projects.

 USA, UK and Canada are the leaders in citizen observatories and environmental citizen observatories in the world.

 The most common model for data collection is the participatory, in which citizens are actively involved as data providers.

 There is a raise since 2000s in observatories using opportunistic data collection methods, such as automatic background data collection.

The top three stakeholders for citizen observatories are:

 Citizen: This group (represents 58% of the total), is mainly providing raw data (34%), installing sensors or apps that collect background information (9%), deploying their own observatories according to their interest (6%) and, its focus of all the types of observatories.

 Academy and government: This cluster (represents 22% of the total), is providing data (4%), installing sensors or apps that collect data (4%), deploying their own observatories (2%), and using information from observatories for decision making, research and development (12%). The observatories that involve this type of stakeholder are: city management observatories, tools for citizen observatories, species monitoring and air and spectrum monitoring projects.

 Nature enthusiasts: This stakeholder’s group (represents 10% of the total), is providing data (6%), installing sensors and apps to collect background information (2%) and, using the data for decision making (2%). information from observatories for decision making, research and development (12%). The observatories that involve this type of stakeholder are: biodiversity monitoring, species monitoring, water, streams, snow and sea observatories and city management observatories.

The most used techniques for engagement are:

1. Present Data Benefit: This cluster was the most common among citizen observatories and embraces the discussion with stakeholders, to present them the benefit of the data they will provide, for themselves such as: better roads and cities, better knowledge about the status of the environment –air, water, pollution, etc. - around their areas, solve their issues and, share their opinion about city concerns.

2. Citizens Interest based monitoring: This category, included techniques that allow citizens to set up and manage their own concern observatory.

3. Unify observatories with recreational activities: This group of techniques included to use recreational activities, competitions, learning games and, art campaigns that raise emotional feelings among the stakeholders, while they submit observations.

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4. There is a clear trend of dematerialization of the observations submission, which translates into the popular use of web (38%), mobile (23%) and both (2%) technologies to collect data. On the other hand, the least common technologies are:

dedicated games (2%), phone-based (3%) - using Interactive voice response known as IVR – and public displays (5%).Remarkably, 69% of the identified world observatories have an environmental goal which involves species, water, streams, snow, sea, biodiversity, air, spectrum and global monitoring.

5. The common problems and limitations of citizen observatories are caused by: user practices, standardization issues, limited knowledge, limited resources, narrow focus, privacy issues, need for recognition of contributions, centralized data, data accessibility problems, data analysis and technology.

6. Common practices among observatories include: co-creation, data aggregation, environmental campaign in public spaces, feedback from observations, gamification, identify stakeholders and their motivations, interest based observatories, involve decision makers, measure motivation, observatory component based, open data for engagement, opportunistic data collection, participatory data collection, provide technology, provide training material, real time visualization, set common protocols for observers.

Chapter II, Citizen Repositories: Current Initiatives in Finland and Europe, brings a detailed overview about European citizen observatories, their focus areas, and practices; special detail is given to Finland where there a survey and interview studies were carried with key players running citizen observatories, focus, practices, challenges and trends were identified.

The key findings detailed in chapter ii include:

 Most of the European observatories (up to 80%) have been collecting environmental information – about species, biodiversity, air and spectrum, water, streams, snow, sea, precipitations, climate change-

 The top three focus area of European citizen observatories are: species monitoring, biodiversity monitoring and air and spectrum monitoring.

 United Kingdom is by far the most active country in this field with 47.5% of the total citizen’s observatories in the continent, being followed by Ireland and Netherlands with 7.5% observatories each.

 Among European citizen observatories the most common practice is to gather their data using participatory data collection method

In Finland:

 Over half of the sample had a positive – already implemented, maybe or ongoing- opinion about opening their data for public use, combination, reuse and redistribution.

 Less than half of the surveyed sample uses social media to communicate with their users

 The participatory method of collecting data is the most common in the country

 Less than half of the sample use scientists to review and ensure the data quality.

However, there is interest about techniques to generate automated classifications systems that are based on citizens’ contributions.

 The biggest challenge for the surveyed observatories is technology management.

Where the main issue is a lack of knowledge about the field.

 The most common data type to store crowd-sourced data was XLS: Excel File Format and the last common were HTML: Hypertext Markup Language and XML: Extensible Markup Language.

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In chapter III, Research Avenues: Citizen Motivations, Active Involvement and Awareness, the top highlight is that: Citizens appreciate being given space and time to arrive at their own responses and interpretations. Therefore, persuasion might not be an accurate technique when it comes to involving citizens as data providers –since to persuade a solution must be known ahead -. However, co- creation of solutions that involve data transparency, gamification elements, social media and common goals with citizens, have the potential to co-create successful crowd-sensing applications.

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Recommendations from the Study

How to run Citizen Observatories:

Key Recommendations from the State of Art

Review

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About data collection (more details in Chapter I):

 Organizations that are currently forced to opt for non-technological approaches to gather citizen observations would benefit greatly from an approach in which they can build their own observatory and it is not focused only in data collection but also in citizen coordination and feedback.

 Wearable technologies that can capture and propagate different information important for policy decision making, for example augmented reality support for citizens to match a real-life situation with a policy case and proceed according to the policy using the algorithmic instructions applied to the current use case and facilitated by the augmented reality annotations, all within their wearable device.

 Factors such as context knowledge of community members, accountability and adherence to social norms, are key for successful reception of social engagement applications.

 Mobile phones can help citizens engage directly with governments to provide feedback targeted at improving the performance of welfare schemes.

 Setting protocols for observations increases the quality in the data from observers.

About Engagement:

 From our studies, there are seven reasons why a citizen participates actively in a citizen observatory:

1. The participant understand the data benefits from his/her contribution for society and in particular for himself/herself.

2. The participant has special interest about monitoring certain phenomena due to personal concerns such as activism, allergies or generate savings.

3. The participant practices particular recreational activities and, submit observations does not influence negatively its experience.

4. The participant appreciates public recognition and, in some cases is very eager to pursue it (e.g. citizen of the year in xyz town or certification as citizen observer of water).

5. The participant enjoys getting immersed in games (which can be of different types) and achieve goals on it that can translate into real awards.

a. Story-based games can be a powerful tool for attracting participants to citizen science tasks.

6. The participant (citizen or organization) is eager to be a partner in a citizen science project, to receive responsibilities and gains from it.

7. The participant is looking for new ways to save/earn benefits.

 The most common practices to build, manage and disseminate a citizen observatory are:

o co-creation, data aggregation, environmental campaign in public spaces, feedback from observations, gamification, identify stakeholders and their motivations, interest based observatories, involve decision makers, measure motivation, observatory component based, open data for engagement, opportunistic data collection, participatory data collection, provide technology, provide training material, real time visualization, set common protocols for observers. More details in Chapter I.

 Most of the feedback when building a citizen observatory is often received outside the context of the website – during walks, travelling to deploy recording devices and, discussions.

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 The motivation element has been little studied and should be taken seriously in the implementation of crowdsourcing systems, as with no participants the crowdsourcing platform is doomed to fail.

About Data Analysis and Visualization:

 There is a need to develop tools for the analysis and further use of open government data as well as of big data and unstructured data conveying subjective opinions of individuals extracted e.g. from the social media.

About Standards:

 There is a need to develop data collection and metadata standards for the different EBVs (Essential Biodiversity Variables) in order to promote a more varied collection of environmental data.

 There is a need for a framework to build citizen observatories that can interoperate globally.

About ICT management:

 For citizen science projects with few resources, technologies with the least complexity and lowest cost are the only sustainable choices. In this study such tools are classified under the cluster “Tools for citizen observatories” (more details in Chapter I and Appendix 5.1)

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Chapter I:

Trends in the World: Past, Present and Future

Citizen observatories as data repositories for active monitoring of the environment have been used in a wide range of areas around the world since the 20^th century –such as ornithology, astronomy, biology, biodiversity monitoring, and city management among others-. Citizen observatories can transform the relations between citizens, businesses, and other areas of government interested in the data and information collected by citizens. Yet, there are no standards that specify in which ways data should be collected, aggregated (from various formats) and analyzed (to deduce useful information) (24).

Despite the differences citizen observatories might have regarding their practices, they seem to have vital common characteristics, such as(22):

(i) A CO should involve citizens as active partners in environmental monitoring and decision-making, since this is central for protecting and enhancing our environment;

(ii) (CO-related environmental monitoring should target an array of natural resources and/or a range of environmental components;

(iii) Generally, the involvement of citizens in CO has multiple purposes, with education and raising public awareness being the most common objectives associated with a CO;

(iv) There is value in CO as a way to bring community groups together. CO, like other forms of civic engagement, can build social capital within the community;

(v) Evaluation of the effectiveness of a CO as well as of the public involvement in environmental decision-making is generally lacking (22).

This study found 108 observatories which were studied in depth to identify trends in the focuses, engagement techniques, technologies, practices, stakeholders, standards, limitations and recommendations. This chapter is organized as follows:

 Statistical Trends

o Major domains and applications of citizen observatories o Environmental observatories commonalities and goals

o Common: Challenges, Opportunities, Best Practices and Recommendations o Standards, Networks and Initiatives

 Literature Highlights

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Key findings of the chapter:

 Remarkably, 69% of the identified world observatories have an environmental goal which involves species, water, streams, snow, sea, biodiversity, air, spectrum and global monitoring.

 The three domains that have most of the citizen observatories applications are: city management (25%), species (23%) and water, streams snow and sea monitoring (18%) projects.

 USA, UK and Canada are the leaders in citizen observatories and environmental citizen observatories in the world.

 The most common model for data collection is the participatory, in which citizens are actively involved as data providers.

 There is a raise since 2000s in observatories using opportunities data collection methods, such as automatic background data collection.

 The top three stakeholders for citizen observatories are:

o Citizen: This group (represents 58% of the total), is mainly providing raw data (34%), installing sensors or apps that collect background information (9%), deploying their own observatories according to their interest (6%) and, its focus of all the types of observatories.

o Academy and government: This cluster (represents 22% of the total), is providing data (4%), installing sensors or apps that collect data (4%), deploying their own observatories (2%), and using information from observatories for decision making, research and development (12%). The observatories that involve this type of stakeholder are: city management observatories, tools for citizen observatories, species monitoring and air and spectrum monitoring projects.

o Nature enthusiasts: This stakeholder’s group (represents 10% of the total), is providing data (6%), installing sensors and apps to collect background information (2%) and, using the data for decision making (2%). information from observatories for decision making, research and development (12%). The observatories that involve this type of stakeholder are: biodiversity monitoring, species monitoring, water, streams, snow and sea observatories and city management observatories.

 The most used techniques for engagement are:

o Present Data Benefit: This cluster was the most common among citizen observatories and embraces the discussion with stakeholders, to present them the benefit of the data they will provide, for themselves such as: better roads and cities, better knowledge about the status of the environment –air, water, pollution, etc. - around their areas, solve their issues and, share their opinion about city concerns.

o Citizens Interest based monitoring: This category, included techniques that allow citizens to set up and manage their own concern observatory.

o Unify observatories with recreational activities: This group of techniques included to use recreational activities, competitions, learning games and, art campaigns that raise emotional feelings among the stakeholders, while they submit observations.

 There is a clear trend of dematerialization of the observations submission, which translates into the popular use of web (38%), mobile (23%) and both (2%) technologies to collect data. On the other hand, the least common technologies are:

dedicated games (2%), phone-based (3%) - using Interactive voice response known as IVR – and public displays (5%).Remarkably, 69% of the identified world

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observatories have an environmental goal which involves species, water, streams, snow, sea, biodiversity, air, spectrum and global monitoring.

 The common problems and limitations of citizen observatories are caused by: user practices, standardization issues, limited knowledge, limited resources, narrow focus, privacy issues, need for recognition of contributions, centralized data, data accessibility problems, data analysis and technology.

 Common practices among observatories include: co-creation, data aggregation, environmental campaign in public spaces, feedback from observations, gamification, identify stakeholders and their motivations, interest based observatories, involve decision makers, measure motivation, observatory component based, open data for engagement, opportunistic data collection, participatory data collection, provide technology, provide training material, real time visualization, set common protocols for observers.

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Statistical Trends

The trends that will be presented in this section, were result of the analysis of 108 citizen observatories around the world and their: focuses, engagement techniques, technologies, practices, stakeholders, standards, limitations and recommendations. Special emphasis is put on the environmental related observatories which represent the 69% of our findings. This section, is organized as follows:

 Major domains and applications of citizen observatories

 Environmental observatories commonalities and goals

 Common: Challenges, Opportunities, Best Practices and Recommendations

 Standards, Networks and Initiatives

Major domains and applications of citizen observatories

Our study classified the identified (108) observatories into eight categories according to their focus (Figure 1):

1. City management (25%): Grouped observatories that support decision makers managing city’s issues such as: transportation, bicycle routes, land usage, energy consumption, surroundings classification, environmental conditions, traffic and parking monitoring, citizen needs and perceptions.

2. Species monitoring (23%): Involving species and tropical species monitoring projects – such as bugs, bats, birds, butterflies, sea spice, and game animals, among others -.

3. Water, streams, snow, sea (18%): Grouped observatories that are collecting data about water quality, precipitations, streams, lakes, snow, ice and sea environments.

4. Biodiversity monitoring (12%): Included observatories that focused on monitoring biodiversity, flora, forests, mountains, biosphere and trees.

5. Air and spectrum monitoring (10%): Band together observatories that gather data about air quality, noise, sounds and radiation.

6. Tools for citizen observatories (8%): Involving tools that are useful for creation or integration of citizen observatories, such as: configurable citizen observatories (plug and play tools), image classification components and sensors monitoring components.

7. Global monitoring (2%): Included astronomy and climate change observatories that monitor global trends.

8. Disasters monitoring (2%): Grouped observatories that are looking at earthquake monitoring and early detection.

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Figure 1: Types of Citizen Observatories

The geographic reach of a citizen observatories can go from local (in a specific country and city) to worldwide (with features that adapt for global needs). The (Figure 2) resumes the distribution of citizen observatories by location and type. The 13% of the total observatories has a global reach and has been defined under the location of “worldwide”

with strong focus on: tools for citizen observatories (creation or integration), city management and species monitoring. While 5%, of the total observatories has a European reach and has been defined under the location of “Europe” with strong focus on air, spectrum and biodiversity monitoring. On the other hand, the three most active countries hosting citizen observatories are:

1. United States: Hosting 38% with a special wide number of observatories for: water quality, cities management and species monitoring.

2. United Kingdom: Having the 16% of the total observatories, where the most common types of observatories are for: species monitoring, biodiversity monitoring and city management.

3. Canada: With 8% of the total identified observatories, having special focus for:

water, streams, snow, sea observatories, species and biodiversity monitoring.

Disasters Monitoring 2 %

Species Monitoring 23 %

Biodiversity Monitoring

12 %

Air and spectrum monitoring

10 % Tools for citizen

observatories 8 % Water, Streams,

Snow, Sea observatories

18 % City management

observatories 25 %

Global Monitoring 2 %

Types of Observatories

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Figure 2: Citizen Observatories’ distribution by location and type.

Citizen science projects have been shown to enable large-scale data collection, increase scientific literacy, and monitor environmental quality(26), as either people-centric or environment-centric sensing. People-centric applications mainly focus on documenting activities (e.g., sport experiences) and understanding the behavior of individuals (e.g., eating disorders). In contrast, environment-centric sensing apps collect environmental parameters (e.g., air quality or noise pollution)(12).In addition, citizen-contributed data has high resolution and requires low calibration in contrast to official databases (low resolution, high calibration)(7).

There are two modern data collection models used by citizen observatories around the world:

a) The participatory model, in which users are actively involved in the collection process by deciding on the spot when to report data and, b) the opportunistic model, where sensor sampling occurs whenever the state of the device (e.g., geographic location) matches the application’s requirements described in a sensing task, without the knowledge of the individual phone user (4).

These two models were used to classify the identified observatories (108) of this study (Figure 3).

0 5 10 15 20 25 30 35

Belgium Brasil Canada Denmark Finland France Global Greece India Ireland Japan Mexico Netherlands Norway Serbia Spain Switzerland UK Europe Eastern Europe United States USA Worldwide

Citizen Observatories Focus by Location

Air and spectrum monitoring Biodiversity Monitoring City management observatories Disasters Monitoring Global Monitoring Species Monitoring

Tools for citizen observatories Water, Streams, Snow, Sea observatories

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Figure 3: Citizen Observatories’ by participation model

In overall, the most used model for data collection is participatory (83%), which according to (Figure 4) has been used since 1900 and has become widely spread since 1960s and continues positively growing, while the opportunistic model is less common (10%) but, has been positively growing since 2000s (Figure 4) and it is expected to continue growing while the mobile technologies development keep developing. However, it is also feasible for citizen observatories combine this two approaches, the 6% of the identified observatories work under this approach which has emerged after 2005 and seems to be increasing (Figure 4).

Nonetheless, citizen observatories need to address the following dimensions: collection (huge amounts of data), aggregation (of data in various formats) and analysis (to deduce useful information). Addressing these challenges require a multipronged approach involving standardization of data formats, data harmonization mechanisms, computational processing and storage infrastructure and mechanisms to ascertain contextual relevance of the data with its consumers(24). While it is true that the large amounts of data captured by sensors provide a “ground truth” base and though new tools and systems offer the power to capture more data, human collaboration, analysis and stewardship are required to extract useful information(36).

0% 20% 40% 60% 80% 100% 120%

Participation Model

Citizen Observatories - Participation Model

Others Opportunistic Participatory Participatory and Opportunistic

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Figure 4: Participation models by years

The citizen scientists that contribute with the citizen observatory projects, normally collect data but they may also help refine project design, analyze data, or disseminate findings;

and co-creating projects, in which projects are code signed by scientists and volunteers(26). However, a citizen science project must consider multiple stakeholders that not only collect and use data but also support the project such as researchers and government.

Also, the citizen observatories present the potential for considerable improvements in terms of social innovations. Their features can enable a two-way communication paradigm between citizens and decision makers, potentially resulting in profound changes to existing governmental management processes(2).

This study clustered the stakeholders of the identified observatories according to their occupation in five categories: citizen, academy and government, nature enthusiasts, families plus specific individuals and developers.

Also, the activities these stakeholders perform were clustered in four types –according to the goal of the activity-, such as: provide data, install sensor/app and let them collect background data, deploy a private citizen observatory campaign, and get training and do classifications.

The (Figure 5) and (Figure 6) summarizes the stakeholder groups by their main activities and, which type of observatories are involving which cluster of stakeholders:

1. Citizen: This group (represents 58% of the total), is mainly providing raw data (34%), installing sensors or apps that collect background information (9%), deploying their own observatories according to their interest (6%) and, its focus of all the types of observatories (Figure 6).

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Others Opportunistic Participatory

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(25)

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2. Academy and government: This cluster (represents 22% of the total), is providing data (4%), installing sensors or apps that collect data (4%), deploying their own observatories (2%), and using information from observatories for decision making, research and development (12%). The observatories that involve this type of stakeholder are (Figure 6): city management observatories, tools for citizen observatories, species monitoring and air and spectrum monitoring projects.

3. Nature enthusiasts: This stakeholder’s group (represents 10% of the total), is providing data (6%), installing sensors and apps to collect background information (2%) and, using the data for decision making (2%). information from observatories for decision making, research and development (12%). The observatories that involve this type of stakeholder are (Figure 6): biodiversity monitoring, species monitoring, water, streams, snow and sea observatories and city management observatories.

4. Families plus specific individuals: This stakeholder’s cluster (represents 10% of the total), is providing data (4%), installing sensors and apps that collect background information (4%), using the information for personal decision making and research (4%). The observatories that involve this type of stakeholder are (Figure 6): city management observatories, biodiversity monitoring and air and spectrum monitoring observatories.

5. Developers: This group (represents 2% of the total), is mostly using the data for research and development (2%) and the observatories that have involved them are the air and spectrum monitoring observatories.

Figure 5: Citizen Observatories’ stakeholders by main activity

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Citizen Academy and Government

Nature Enthusiasts Families and Specific

Individuals Developers

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(26)

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Figure 6: Citizen Observatories’ Type by stakeholder

In overall, the types of data that stakeholders have been reporting for citizen observatories (Figure 7) is mainly data about measurements (69%) via their mobile devices, special devices or their own recordings, opinions (6%) about set topics or proposing topics and, both (25%) through classifications and ideas for new observatories.

Figure 7: Types of Collected Data

There is a rise in social computing (based on social production and mass collaboration) has facilitated a shift from consumer cultures (specialized in producing finished artifacts to be consumed passively) to cultures of participation (in which all people are provided

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Air and spectrum monitoring Biodiversity Monitoring City management observatories Disasters Monitoring Global Monitoring Spices Monitoring Tools for citizen observatories Water, Streams, Snow, Sea observatories

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Nature Enthusiasts Families and Specific Individuals Developers

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with the means to participate and to contribute actively in personally meaningful problems) (18).

Social computing provides a new opportunity for citizens to reach out and change their world. HCI (Human Computing Interaction) researchers have begun to investigate on how social computing can increase citizen engagement and participation with government. In addition, researchers have recently begun to investigate how social computing can support planning activities around urban infrastructure, giving citizens a greater voice in the planning process that reshapes their world(14).

Furthermore, the citizen observatories present the potential for considerable improvements in terms of social innovations (as result of social computing). However, it is important to define what the social innovation in question consists of, to what extent it is being attained and under what conditions, and how it can be fostered(2).

In this context, citizen observatories are social computing applications that actively involve mass collaboration under common goals. This study, clustered the ways citizen observatories are currently being engaged to perform citizen science activities under seven clusters (Table 1):

1. Be an exceptional citizen: This cluster, grouped techniques that award the activeness of a particular citizen as an observer with social recognition in their communities, TV or schools/work places.

2. Citizens Interest based monitoring: This category, included techniques that allow citizens to set up and manage their own concern observatory.

3. Gamification Strategies: This cluster, grouped the gamified techniques that involve to incorporate game elements into their applications such as puzzles, avatars, competitions or story lines.

4. Partnership: The main focus of this cluster, are techniques that empower city managers to install sensors and apps in their cities, to collect background data about different concern issues.

5. Present Data Benefit: This cluster was the most common among citizen observatories and embraces the discussion with stakeholders, to present them the benefit of the data they will provide, for themselves such as: better roads and cities, better knowledge about the status of the environment –air, water, pollution, etc. - around their areas, solve their issues and, share their opinion about city concerns.

6. Save Money: This category focused on creating monetary saving for the users, due to their activeness using a particular observatory. It is key, to keep the users updated about of how much has been saved because of their actions.

7. Unify observatories with recreational activities: This group of techniques included to use recreational activities, competitions, learning games and, art campaigns that raise emotional feelings among the stakeholders, while they submit observations.

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Table 1: Citizen Observatories – Techniques to engage

Technique to Engage Source

Be an exceptional citizen (6%) of Observatory Projects Citizens Interest based monitoring (19%) of Observatory Projects

Gamification Strategies (6%) of Observatory Projects Partnership (2%) of Observatory Projects Present Data Benefit (53%) of Observatory Projects

Save Money (2%) of Observatory Projects Unify observatories with recreational

activities (13%) of Observatory Projects

The fabric of contemporary cities increasingly incorporates ubiquitous networks of sensing and actuation devices. These systems allow for an unprecedented understanding of numerous aspects, relating to the urban environment itself and the processes that take place in it. Environmental conditions, air quality, occupancy levels, energy consumption, electricity usage, traffic flows, public transport frequency, noise levels, water management are among the few indicators that can nowadays be observed and, subsequently, controlled by such devices. In addition, every obtained observation synchronously constitutes a set of geo-located data, reflecting a minuscule piece of information about the city dynamics(30).

Pervasive computing can ultimately engage millions of people in mass participation environmental campaigns, raising awareness of environmental issues, supporting education, activism and democracy, and delivering environmental data on a scale never before possible(13).

This study analyzed the technologies that are currently used to build citizen observatories (Figure 8). There is a clear trend of dematerialization of the observations submission, which translates into the popular use of web (38%), mobile (23%) and both (2%) technologies to collect data, which is followed by a strong use of sensors (8%) and sensors plus mobile apps or web platforms (4%). Finally, the least common technologies are: dedicated games (2%), phone-based (3%) - using Interactive voice response known as IVR – and public displays (5%).

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Figure 8: Citizen Observatories’ by technology use

In addition, only 21% of the studied citizen observatories offer some services which anyone can use to analyze, reuse and redistribute (Figure 9). Within, the social media use (Figure 10), citizen observatories seem to prefer Facebook, Twitter and G+ for increasing their visibility. Yet, the citizen observatories are also present on Instagram, sound cloud, YouTube, RSS, Github and some even have their own web store.

Figure 9: Citizen Observatories’ by services use

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Figure 10: Citizen Observatories’ by social media use

The advances in computational storage and processing capacities have not only allowed for a finer granularity of the available information sets, but have also given the opportunity to synchronously analyze data of different types; besides that, these data sets are largely referenced in space and time, while reflecting human activities as well as monitoring city- related conditions and events the actual time during which they occur. Subsequently, they constitute invaluable sources for deriving an understanding about urban dynamics (30).

But, what technologies in particular are used for building modern citizen observatories? This study analyzed the web platforms of observatories using the service of BuiltWith, which is service that counts with a website profiler tool that allowed us to find out what websites are built with. The (Figure 10) resumes the trending tools that are used by citizen observatories creators for their sensors and web platforms. The size of the font in the (Figure 11) is proportional to the relevance of certain tool in the field.

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Figure 11: Citizen Observatories’ word cloud of technical tools

Environmental observatories commonalities and goals

Thanks to the Internet, crowdsourcing is expanding its reach and establishing itself as a cheap and viable alternative for scientific work that was previously restricted to the limited capacity of professional teams (12). With more than half of the planet’s population residing in urban areas (38) and adapting to a lifestyle that demands more than meeting the basic needs of water, food and shelter, the promotion of an environmentally sustainable manner of living is becoming an important priority for policy makers and governments on a worldwide scale. Our everyday practices and interactions as city residents have consequences that reach beyond the quality of conditions in our immediate surroundings and furthermore, via complex processes, contribute, to some extent, to the environmental crisis (39).

This study classified the identified (108) observatories into two categories according to their purpose: environmental and non-environmental (Figure 12). Remarkably, 69% of the identified world observatories have an environmental goal which involves species, water, streams, snow, sea, biodiversity, air, spectrum and global monitoring. Consequently, there is a 31% of observatories that are classified as non-environmental and involve city management observatories, disaster monitoring and tools for building/integrating citizen observatories.

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Figure 12: Citizen Observatories Environmental Focus

The geographic reach of an environmentally focus citizen observatories as for the non- environmental can go from local (in a specific country and city) to worldwide (with features that adapt for global needs). The (Figure 13) resumes the distribution of citizen observatories by location and type. The 5% of the total observatories has a global reach and has been defined under the location of “worldwide” with strong focus on species monitoring. While 7% of the total environmental observatories has a European reach and has been defined under the location of “Europe” with strong focus on air, spectrum and biodiversity monitoring. On the other hand, the three most active countries hosting environmental citizen observatories are:

1. United States: Hosting 37%, with a special wide number of observatories for water quality and species monitoring.

2. United Kingdom: Having the 23% of the total observatories, where the most common types of observatories are for species monitoring and biodiversity monitoring.

3. Canada: With 11% of the total identified observatories, having special focus for:

water, streams, snow, sea observatories, species and biodiversity monitoring.

Collecting environmental data using observatories has been done since 1900 (Figure 14), and has grown rapidly since 1960s. While, non-environmental observatories have appeared only on the 2000s decade. However, both types of observatories are on the rise, though apparently environmental focused observatories have a faster growing rate. Then again, the participatory model (which involves actively people) is the most used by environmental citizen observatories (Figure 15).

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Figure 13: Environmental Citizen Observatories by Location

Figure 14: Environmental Citizen Observatories by Year

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Figure 15: Environmental Citizen Observatories by Participation Model

Who are running citizen observatories around the world?

A citizen observatory can be used for multiple fields and involve several types of stakeholders but, also it can be run by various types of organizations from universities, charities, companies, consortiums, government institutions, private pioneers (initiatives), NGOs to research institutes (Figure 16).

The most common runner of citizen observatories was private pioneers (citizens, consortiums, societies, foundations, networks) through initiatives (31%) that have as main focus a particular type of observatory. Followed by: Universities (26%) which operate with their research units handling COs, consortiums (12%) that refer to multidisciplinary joint initiatives started by different types of organizations which are supported by regional grants and networks, government (12%) through local authorities, national commissions/institutions, research units and initiatives, companies (11%) that run business or research units around the COs topic, research institutes (4%) that are highly focused on observations of different fields, NGOs(2%) which run a particular citizen observatory as their cause (and generate revenues), and charities (2%) that are sustained by multidisciplinary institutions through consortiums.

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Figure 16: Institutions Running Citizen Observatories Worldwide

Challenges, Opportunities, Best Practices and Recommendations

Given the ubiquity of mobile devices and the high density of people in the world, citizen science can achieve an unprecedented level of coverage in both space and time for observing events of interest(31). Although, there are differences in the monitoring across different parts of the world, there is a large number of observatories which share features, practices, and challenges within the two aspects of citizen science: community- based monitoring and community-based management (25).

This study classified the reported problems and limitations from the identified citizen observatories (108) in 11 categories (Figure 17), which are the following:

1. User Practices (38%): The target stakeholders, are not always ready for start contributing with a citizen observatory, this challenge involves all the possible issues that constraint the observatory operation due to stakeholder practices or lack of practices. The (Figure 18) brings an overview of the reported issues in this category, more detailed information can be find in the appendix III.

2. Data Aggregation Issues (17%): This problem, is faced by the observatories that have multiple data formats and data structures which have to be used to extract joint information.

3. Technology (13%): This challenge refers to: issues with devices size, weight and reliability, power consumption limitations, calibration and configuration constraints, lack of systematic methods to reject false and spam observations.

4. Standardization (10%): This challenge involves: the lack of reusable methods or frameworks for creating new observatories, the lack of standards for inter- communication among observatories, semantic discrepancies, and lack of systematic evaluations.

Charity 2 %

Company 11 %

Consortium 12 %

Government 12 %

Initiative 31 % NGO

2 % Research Institute

4 % University

26 %

Institutions Running Citizen Observatories

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