Dissemination

detection

Timely access to updated invasive alien species (IAS) detection and prioritisation data is crucial for effective management, resource allocation, and strategy planning. OneSTOP ensures these data are available in both human- and machine-readable formats, tailored to user needs. It streamlines open (meta)data flows using domain standards and publishes them in open repositories, aligning with FAIR principles.

Automated data flows to GBIF and GRIIS, using the Darwin Core standard and Ecological Metadata Language (EML), will enhance IAS monitoring and management while allowing integration with European initiatives like EOSC and EASIN. All software developed will be Open Source with a permissive licence, enabling adaptation of OneSTOP workflows for local or national use. 

In collaboration with GuardIAS, OneSTOP will launch an alert system to notify stakeholders of potential IAS introductions, complementing existing systems like EASIN. The project will also support management and awareness by testing methods for EICAT assessments, generating tailored management reports, and developing interactive Shiny apps to explain Species Distribution Models, IAS prioritisation, and management strategies.

Data publishing GRIIS checklists Early warning system Awareness raising

Data publishing

OneSTOP is developing an open-source automated workflow that takes the project’s detection data and publishes it to GBIF. The workflow will automatically map detection data to the Darwin Core standard and harmonise metadata to follow the FAIR Data Principles. The goal is to make data openly accessible and easily usable for quick responses from relevant stakeholders. To ensure long-term use, OneSTOP will offer training and detailed documentation, making the system easy to adopt and maintain even after the project ends.

D4.1 Automated pipelines for data integration - December 2026

GRIIS checklists

OneSTOP is developing an open-source protocol for creating and updating national GRIIS checklists in Cyprus, Belgium, Portugal, and Romania. The protocol will be documented openly on GitHub to ensure transparency and collaboration. It will involve rigorous data collection, verification, and quality control, aligning checklists with the Darwin Core standard for compatibility. Using the Integrated Publishing Toolkit, automated workflows will publish data to GBIF, with species names linked to the GBIF Backbone Taxonomy.

A core goal is the creation and updating of the GRIIS Europe checklist, unifying national lists through automated name matching. This versioned checklist will be published on GBIF, featuring national contact points to encourage ongoing contributions. Collaboration with EASIN will support species data updates for their portal.

To ensure long-term adoption, OneSTOP will offer datathons, training webinars, and guidelines, fostering scalability and continuous updates.

D4.2 Automated pipelines for the Global Register of Invasive Species (GRIIS) - October 2026

Early warning system

OneSTOP is developing a European early-warning system for IAS, complementing the EASIN Notification System (Notsys). It will aggregate IAS data from multiple sources, using the GRIIS Europe checklist as a taxonomic filter. The system will provide real-time alerts, compile data, offer a user-friendly interface, and enable configurable email notifications. This will help decision-makers, researchers, and field managers respond quickly to new IAS detections across Europe. 

D4.3 Results of the alert system - February 2028

Awareness raising

The effective management of IAS requires engaging the public through effective awareness-raising and information transfer. However, complex, jargon-heavy information can hinder understanding.

OneSTOP is assessing readability in EU IAS documents using language-independent metrics and OECD literacy data. The outcome will be the development of pan-European guidelines for preparing information with high readability and impact. Furthermore, we will disseminate species distribution models and IAS prioritisation through Shiny apps which simplify scientific concepts through interactive play and citizen science.

D1.8 Education tools - April 2028

The IAS assessment process is often delayed by the time required to collate literature, extract relevant information, and synthesise findings across multiple sources. To streamline this, OneSTOP is applying LLM methods to the EICAT assessment process, which categorises alien taxa based on their impact magnitude. We will evaluate LLMs' potential to enhance each stage of the EICAT process, assessing their scalability and cost-effectiveness. Additionally, we aim to improve data flow from primary impact sources into EICAT assessments, ensuring more efficient integration with the IUCN Standard.

D4.4 Environmental Impact Classification for Alien Taxa - Large Language Model report - December 2026