MICS contributes to the interoperability of citizen science. Interoperability is essential for efficient and effective information sharing and data aggregation about citizen science projects, datasets, and observations. Below we list a few examples of why it is so essential to make information sharing and data aggregation efficient and effective through well-crafted and well-documented metadata standards. These examples have been adapted from initial ideas by Greg Newman, director of CitSci.org.
People might want to know which citizen-science projects are happening in their region. They might want to know which projects are available for them to participant in that are nearby and that are of interest to them and then to decide which projects to join. Having information about which projects exist where makes it easy for directories of projects to remain current, up-to-date, and informative for those seeking to join these citizen-science projects or initiatives.
Project managers need efficient means to share information about their projects with prospective participants. These people are busy. They need efficient ways to keep information about their projects up-to-date regardless of where this information is being shared and who is sharing it. For example, the project managers of the Cos4Cloud project may wish to advertise being listed in MICS (where the impact of the project can be visualised) and may also use the EOSC Portal or CitSci.org to host their project. They may also want to be listed in SciStarter as well as in the EU-Citizen.Science platform. Having these directories all synchronise the information about the project automatically makes it easy for the project managers to change essential details about, for example, who to contact to learn more. Imagine the reaction of the project managers when they realise they can change their project contact email-address in one places and it updates in all places automatically!
People might want to know what datasets exist where and about which topics. They might want to efficiently search for all available datasets about a topic, discover all available relevant datasets, access them, and then be able to discern whether they can use the datasets for their decision making or research needs. For example, imagine a scientist in Australia hoping to find all data available on invasive species to support policymakers to make decisions about how to prioritise available funding to manage the worst invasions. Imagine the reaction when this scientist finds out she can search for open datasets (perhaps on Google Dataset Search) and find datasets generated by active citizen-science projects currently addressing invasive species hosted by the Atlas of Living Australia’s Biocollect platform as well as historic citizen science projects conducted in Australia by Earthwatch participants that had mapped invasive species populations several years earlier.
Scientists and platform managers might want to share scientific observations about the world. They might want to do so to advance science and decision making. And they may also want to do so to leverage the unique strengths of various platforms to improve data quality. For example, a project on CitSci.org might ask its participants to collect species occurrence observations of a rare butterfly. But they also need to crowdsource the identification of this specific rare butterfly. Imagine their reaction when they learn they can automatically share observations submitted to their CitSci project and have these appear on iNaturalist and then have this online community verify the taxonomic identity of a butterfly observation to make this observation deemed as “research grade.” Then, their delighted reaction grows when they learn that all research-grade observations are automatically shared with the Global Biodiversity Information Facility (GBIF). Now we have observations submitted to one platform becoming verified on another, sent back to the original platform so they can be represented as “research grade”, and also sent to the go-to source for global biodiversity data worldwide.
This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 824711.