This webinar was co-organized by three European projects; MAELSTROM; InNoPlastic and RELIANCE. The event aimed to provide operational tools for collaborative scientific works on ML pollution investigation at different scales and disciplines rolling out in the upcoming months. The Projects MAELSTROM and InNoPlastic were founded with the same mission on the removal of ML and circular economy. RELIANCE is a project supporting the fostering of a European Science Club with new services. However, within Reliance there is a community working with ML, and thus, there is a belief that the three projects can work together as a unified team, opening also the opportunity to partners that would like to be part of these inter project connections.

Webinar Objective:

This capacity-building event aimed to gather research that has never worked before in Open Science Cloud Environment through a RELIANCE Service Portfolio made of 3 basic services: Research Object Hub (ROHub), Data Cubes and Text mining. The main webinar focus was the development of Research Objects (ROs), where stakeholders can encapsulate data from any part of the research, such as methodology, results, people involved in the investigation, web services used or any kind of annotations and encapsulate it to be shared privately or publicly.

Webinar Outcomes:
This webinar provided a preliminary overview of Open Science tools such as Research Objects, as effective methods for making Open Science more accessible, reusable, and transparent. These tools can be especially beneficial for European projects, such as MAELSTROM, because the data must be updated on a regular basis, therefore people from many communities must be involved. The webinar represented the first step for a coordinated, transnational, and multidisciplinary approach that was further presented to the European Commission through Research Objects in December of the same year, demonstrating a strong and powerful workflow among different initiatives. The webinar addressed the scientific ML community and presented operational tools to produce collaborative scientific work on ML pollution using the European Open Science Cloud (EOSC) digital services. The webinar highlighted the need for more international collaborative work, sharing scientific data through bigger datasets, and making Open Science more accessible, reusable and transparent.