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https://github.com/ec-jrc/citsci-explorer

CitSci-X
https://github.com/ec-jrc/citsci-explorer

citizen-science

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CitSci-X

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README 

          
# Welcome to the Citizen Science Project Explorer!



The Citizen Science Project Explorer (CitSci-X) is an exercise to provide an integrated view of existing citizen science projects, and to derive statistical data from them.



Project records are collected from voluntarily contributed data sources (e.g., surveys, catalogs, datasets, etc.), which are harmonised into a common data schema - nothing complicated, just a flat list of attributes, as the name and description of the project, the geographic area covered, its social and policy uptake - if any.



If you are interested in contributing, please follow the instructions outlined in the following section.



# How to contribute



Contributions must be submitted via pull requests (PR) to this repository. The data must be submitted as a CSV (Comma-Separated Values) files, whose columns must have specific names and values.



The submission steps are the following ones:



## Creating an issue describing your contribution



As a first step, you are recommended to [open an issue](https://github.com/ec-jrc/citsci-explorer/issues) providing a description of the data source and the projects you would like to contribute. This would help understand whether your contribution is in scope with this work, and to verify which information has been collected for the projects to be contributed.



## Preparing the files to be submitted



The submission consists of 2 CSV files:

- one describing the data source

- one describing the project records



The columns and values of these files must correspond to the ones defined in the data schema. Please note that all columns not matching the defined names will be ignored.



The [`examples` folder](https://github.com/ec-jrc/citsci-explorer/tree/master/examples) in this repository includes two empy CSV files with the standard column names. You can copy-paste the data there, and modify the column values (if needed) to match the allowed values.



## Creating a pull request



Once the two CSV files are ready, you can create a pull request to [the `src` folder](https://github.com/ec-jrc/citsci-explorer/tree/master/src).



The title and/or description of the pull request must include a reference to the issue you have previously created.



The two files to be submitted should ideally encoded in UTF-8, and they must have a file name following the pattern:

- `[N]-catalog-[name].csv`

- `[N]-projects-[name].csv`



where "N" is an integer, and "name" is the abbreviation of your data source. 



Note that "N" and "name" should correspond to the same values in both files - e.g.:

- `1-catalog-citsci.csv`

- `1-projects-citsci.csv`



The value of "N" must be incremental to the ones used in the already contributed data sources in folder `src`.



# Data schema



The following sections illustrate the fields to be used in the CSV files to be submitted.



> :information_source: Whenever possible, the field name links to the corresponding term in the [Citizen Science Ontology](https://ec-jrc.github.io/citsci-ontology/prj/) (under development).



## Data source



Code

Values

Description



c_name

free text

The name/title of the data source



c_description

free text

A brief description of the data source



c_contact

email or URL

A contact email / URL for the data source



c_url

URL

The URL of the page of the data source



c_publisher

free text

The name of the organization who published / released the data source



c_type

Desk research, Online survey

The way project records have been collected



## Project



Code

Values

Description



id

integer

The identifier for the project in the data source, expressed an an integer (starting from 1). In case of multiple submission of the same data source (in case there was an error, or because it has been updated), the identifier MUST NOT CHANGE across the different versions of the data source



name

free text

Name of the project/activity



description

free text

A brief description of the project



contact

email or URL

A contact email / URL for the project



url

URL

The URL of the page of the project (if any). Preferably, this should be a persistent URL. E.g., for projects funded by the EU Framework Program (FP7, H2020, Horizon Europe), it is recommended to point to the relevant page on CORDIS.



lead_organization_name

free text

Name of the lead partner. Local name, in native language.



lead_organization_category

One of these values: Academic, Consortium, Governmental, Non-governmental

The category of the organization who led the project



geoextent

One of these values: Global, Macro-regional, National, Sub-national, Regional, City, Neighborhood

The spatial scale at which the project is implemented. Subnational is used as generic category for projects for which the sub-national scale is not known (i.e. regional, or city, or neighborhood). All regional, city and neighborhood projects are also sub-national projects.



geocoverage

Comma-separated list of ISO 3166 country names

The areas covered by the project (typically corresponding to the countries involved in the project team/consortium), specified as a comma-separated list of country names. Country names MUST correspond to those defined in ISO 3166



start_date

Date in the ISO 8601 format YYYY-MM-DD (e.g., 2019-03-04)

The start date of the project



end_date

Date in the ISO 8601 format YYYY-MM-DD (e.g., 2019-03-04)

The end date of the project



active

Yes|No

Whether the project was or not still active at the moment when it was added to the data source



environmental_domain

One of these values: Atmospheric, Cross-cutting, Freshwater, Marine, Terrestrial

The dominant environmental domain of research for this project.



environmental_field

One of these values: Air quality, Animal welfare, Biodiversity, nature and landscapes, Climate, Cross-cutting, Efficient use of resources, Environmental health, Environmental risks, Land, Noise, Sustainable consumption and production, Waste, Water

The dominant environmental field tackled by the project activities.



category

One of these values: Civic science, Crowd-sourcing, DIY engineering, Monitoring, Occasional reporting, Passive sensing, Volunteer computing

The primary category of the project. The current categories have been derived from the study Citizen Science and Policy: A European Perspective.



social_uptake

One of these values: Considerable, Large, Very large



The level of social uptake of the project. It basically corresponds to the index of number of participants or followers. Based on expert

knowledge:




Very large


Large number of users, tradition, excellent projects with high numbers of users (above 1,000)


Large


Projects that we would say good in review and with medium number of users (below 1,000)


Considerable


All others





policy_uptake

Yes|No

Whether the project results have been or have been not used for policy making



policy_uptake_explanation

free text

Brief explanation of why there is a policy uptake or no policy uptake, and which policies are impacted and how. Especially to be filled for cases where there is a policy uptake.



policy_relevance

One of these values: Compliance assurance, Early-warning, Policy evaluation, Policy implementation or monitoring, Problem definition

Main phase of the policy cycle potentially impacted by the project actions.



sdg1, ..., sdg17

One of these values: 0 (No impact), 1 (Indirect impact), 2 (Direct impact)

Level of impact on each of the 17 UN Sustainable Development Goals.