Data Management and Standards
Informing best practice will develop guidance and associated training to improve the quantity, quality and usability of AS data collected by citizens. Data standards do exist, such as Darwin Core and ABCD, but their adoption is not universal and these standards need development to make them more appropriate for the breadth of data that are collected on biodiversity by citizen scientists. This includes data terms that are largely specific to IAS, such as management methods and impacts, but also ways to describe methods used by citizens. Data management is fundamental to the success and long-term impact of a CS project, yet it is often not considered until the end of the project, by which time decisions made at the beginning of the project can limit the choices for data reuse. From the outset of the Action we will create a data management plan collaboratively to guide our work recognizing IAS data, and their uses, are not identical to other biodiversity data. The need for rapid and focused data mobilization is particularly important for a response to new species introductions. This is where we will address issues of sensitive data and data sharing.
Task 1: Review structure of data across existing AS CS initiatives within Europe and develop a data management plan for the Action to cover any data and other outputs from the project.
Task 2: Facilitate data mobilization across Europe, particularly of Biodiversity data as that relates to AS, including linking ECIs in short-term scientific missions with experienced data managers to facilitate data publication.
Task 3: Explore creative ways to illustrate the problem of IAS through novel visualizations of data and innovative mash-ups of data from different domains (linking to WG4). Task 4: Work with international data standards organizations to improve their standards for research with CS and IAS.
1. Published data management plan on-line including standards to be used, the terms for data sharing and the long-term preservation of data (Task 1).
2. Map data flow of AS CS data across Europe linking to EASIN (Task 2).
3. Showcase of data visualization approaches through the Action website (Task 3; linking to WG4).
4. Guidance document for best practice on data management for CS specifically related to IAS (Task 4; Linking to WG1).