House of Apps: Create great apps for citizens

Objective
To provide immediate feedback to a citizen scientist whether his/her observation is common or not.

Possible functionality and needs
An app that explores whether an observation is unusual (out of the normal range of measurement) or common. Provide an immediate feedback that should reinforce participation.
Phenomenon: for example, a plant that is flowering, a fish dying in a river, (unusual) heavy rain shower… Should be described by a participant in as many details as possible. Some should be parameters

Parameters:

• Optional: Intensity of the phenomenon (ex., fish size, fish number, rain high mm)
• Compulsory: time stamp (date in the year); (automatic)
• Compulsory: location, space (geographic); (automatic)
• Optional: some space attributes (e.g., land use)

The app would gather data from social networks (Twitter, Instagram, Google analytic (?)) and calculate the frequency of occurrence of similar phenomenon, and normal range in space and time, and score the observation on a 0-1 likelihood scale (i.e., is it common or uncommon, for example: a plant flowering in December when the normal period is spring; a species outside of its normal distribution – outside its usual habitat; a fish larger than the largest known, etc.).

Intended users
People interested in their natural environment and its variation / participants in citizen science project

Background and problem
Volunteer motivation in citizen science project is driven by a desire to make tangible impact on science. Unfortunately, feedback on how, where, and whether the data is used in a specific science project, or whether it supported specific scientific findings, is often lacking. Inability to trace one’s data collection contributions is one of the main reasons for this lack of feedback, and consequently the lack of acknowledgment and the sense of inclusion for the volunteer.

Objective
TRYCSO enables automatic tagging of data volunteered in a citizen science project. Each data point is appended with a quasi-unique token, calculated via a hash function, that allows users to identify their contribution in a broader dataset. One component of the project will be implemented as a mobile programming library that streamlines the process of collecting and tagging the data. The other component resides on a server and searches for possible uses of the data, so that a user can be notified whenever her data are used.

Possible functionality needs

• Hashing data; ideally, hash functions should be tailored to a particular data type (e.g. photo, sound, etc.)
• Save data locally on a device and append with the metadata (including the calculated hash)
• Export the data locally to a SD card and remotely via a network
• Interface with different data repositories (where APIs are available) and efficiently search through them for the given hashes. Search space should be reduced by other metadata parameters (e.g. time of creation, location, data type, etc.)
• Notify the user when their data is used
• OPTIONALLY: ensure that the hash is not lost in the process of data transfer/processing

Intended users
Citizen scientists who would like to trace the impact of the data they have collected

Software guidelines
As a proof of concept, we focus on mobile device camera photos:

• Construct a hash function that summarizes a photo; the function should be tailored to “disperse” hashes in the hash space as much as possible and maximise uniqueness.
• Build a mobile (Android/iOS) library that allows:
  • A developer to request a camera photo and that returns a photo appended with the metadata, including the calculated hash.
  • Stores the calculated hash (optionally with a photo thumbnail) on a user device (or in a cloud storage assigned to this user)
  • Connection with a server component for tracing the data
• Build a server component that periodically searches for the hashes provided by the mobile app and notifies the user where and when their data was used.
• OPTIONALLY: embed the calculated hash in the data, so to ensure it is not lost in the processing (e.g. embed it in the photo).

Background and problema
In many cases there is a lack of adequate mobilization of scientists (and of citizens), and doing it cross-borders. One of the major threats of Citizen Science is that Scientists are often isolated from the public (Ivory tower problem). This prevents the addressing of multidisciplinary scientific knowledge and the broad diffusion of Citizen Science.

Objective
Develop an app to help scientists and citizens find each other. Amongst other things this will enable the formulation of competent teams and facilitate the distribution of workload. As a secondary result, it can lead to the generation of new ideas.

Possible functionality and needs
Provision of:

• profiles of citizens and scientists (expertise, interests)
• Calendar for availability
• Task distribution system
• Matchmaking system
• Workload balancing system
• Statistics, analytics of participants, matches, etc.

Intended users

• Citizens, scientists and Citizen Scientists
• Citizens asking questions to scientists.
• Scientists and citizens trying to find each other (crowdsourcing, niche-sourcing).

Short description
A software application that will inform citizens on the air quality levels they are exposed to and complement it with discomfort index value calculated on the basis of personalized measurements.

Background and problem
Air pollution (AP) levels affect quality of life especially if taking also into account local weather conditions and parameters like the discomfort index that presents the mean levels of discomfort as a function of air temperature and relative humidity. AP information is now available for the whole of Europe via the Copernicus atmospheric monitoring services-CAMS (link) in urban areas, while temperature and relative humidity readings are commonly available via sensors integrated to smart phones (the Android example). Combining this information taking into account personal profile of health status and preferences, while also incorporating green routing (routes with minimum environmental burden) will be of interest for many EU citizens.

Objective
To develop a small software component that guides a citizen scientist to record temperature and relative humidity via a smart phone, access AP forecasts from CAMS, take into account personal health profile data if possible, and provide with “color coded” quality of life information and advice.

Possible functionality needs

• GPS awareness
• Run an already available app to collect temperature and relative humidity readings
• Web-based access to CAMS data downloads

Intended users
Citizens with respiratory or cardiovascular problems, elderly, those taking care of children, etc.

Software guidelines

• Trigger by a button click
• Download local AP forecast
• Get a set of measurements
• Combine data to show a simple color message to the user.

Background and problem
Planning efficient “green” transportation network can promote people for moving from using vehicle to more environmental friendly means of transport (e.g., walking and cycling). While much effort is currently directed to monitor and plan road networks in cites, less effort is directed to improve sustainable network of pedestrian and cyclist. Pedestrians and cyclists often encounter obstacles that reduce the comfort and efficiency of their journey and this may influence their willingness to use more sustainable means of transport.          

Objective
To develop an app that collects data about pedestrian and cyclist usage of roads, sidewalks and trails, with emphasis on understanding which elements disturb the flow along the path. The aim of this app is to provide data for planners to help design and manage sustainable transportation network for pedestrians and cyclists.

Possible functionality and needs:

• Path used (GPS location, elevation) and time
• Number of stops
• Number of accidents for bikes and pedestrians (if known)
• Subjective feeling of security and path efficiency
• Active reporting of obstacles, hazards
• Measuring of light conditions
• Parking places
• Time of years and weather
• Uploading photos of obstacles and nice places, views…
• Noise

Intended users
Citizen scientists interested in helping the city to create a more efficient sustainable transport network. The end users (who will get the data) will be planners and engineers that are responsible for the transport network in the city. Sharing the data with citizen scientists and others can help them to better plan their routes and share live info about obstacles. The app could also have a social element that could create a reporting community for sustainable transport network.   

Software guidelines

• Trigger by record bottom
• Easy to activate and easy to report obstacles and other elements
• Can take photos of obstacles and other elements
• Create database for the use of planners
• Collect live secondary data from other resources (e.g., traffic info, weather info…)
• Ask participants questions about their experience during and after the use (e.g. when you have an unexpected stop).

Background and problem
Particulate matter (PM, suspended particles) in air, resulting from traffic, industries, heating, cause huge health problems and costs for the society. There are huge spatial variations in PM levels, and the quality of air can be an important factor for instance when choosing the residence area.

Objective
To engage citizens across Europe in the collection of data regarding the PM deposition. Procedure: Windows are washed and left for three weeks and wiped with a standardized tissue. Tissues (and a clean control tissue) are photographed using the mobile application, under standard conditions. Location (coordinates), orientation of the window and date of the measurement are recorded. The application will provide a map and a position of the submitted sample data on an indicative scale for PM levels as a direct feedback to the user. The application should also provide an interactive map for air quality in different regions.

Possible functionality needs

• camera usage
• GPS awareness
• resolution awareness
• orientation of the window
• frequency of the events
• map service

Intended users
Citizens, decision/policy makers, environmental agencies, scientists, urban planners, health care.

Software guidelines:

• Creating a user profile (location)
• Get a photograph
• Show and save the photo
• Detecting the grey level of two images (comparison of the clean and used tissue)
• Visual augmentation of the map service to describe the pollution level

Short description
A software library that will handle the smartphone’s camera for Land Use/Land Cover (LU/LC) apps.

Background and problem
A lot of the LU/LC apps are taking advantage of the smartphone camera since they are based on the visual examination of geo-tagged photos. While in-situ and timely data is a great advantage for such applications, many times the photographs taken are not fit-for-purpose. Close-ups, too much sky, not enough land or misleading zoom levels of the photographs can hinder the photo-interpretation. 

Objective
To develop a small software component that guides a citizen scientist to collect a geo-tagged photo with a smartphone. The software should help the user during the picture taking to align the picture to the horizon, indicate the amount of sky, remind the user that there should be no zoom in, that the gps should be active and there should not be any other obstacles in the view, etc.

Possible functionality needs

• GPS awareness
• Show the line of the horizon in a proper position
• Zoom level awareness
• Calculate sky percentage
• Flash awareness
• Provide Info/tips to the user before the photo capturing
• Panorama mode
• Resolution awareness