Description
Data gathering and management is increasingly driving research and innovation, helping to develop and adapt faster as well as to take decisions related to a complexity of actors, value chains, and economic, legal, sustainable, and social requirements.
Data analysis and its use for predictive modelling, including big data handling and AI algorithms, are a competitive factor, increasingly important to combine results of impact assessments (e.g. as indicated by the Safe and Sustainable by Design framework), and a premium criterion in cooperative research projects.
Despite these advantages, several barriers still hinder their efficient use and exploitation, including:
- Interest and resources of parties to share research data (including failure data) and build unbiased data sets.
- Capacity to build relevant and FAIR (Findable, Accessible, Interoperable, and Reusable) raw data sets.
- Scoping of data analysis (e.g. experimental data, correlations, predictive models) and selection of appropriate methods and tools.
- Use and interpretation of results based on diverse data sets and models.
- Sharing and using data and analytical results within and outside projects’ consortium.
This workshop aims to promote awareness and to share views and experiences on data analysis from both researchers and data management experts and practitioners, based on the experience of running European projects on material research. It is an opportunity for exchanging knowledge and experiences, identifying gaps, good practices, and learnings on the topic.
Agenda
Setting the scene
- Andrea Porcari, Airi- Italian Association for Industrial Research (IT), and Claudia Amabile, PDC- Process Design Center (NL)
- Gap analysis on data management and predictive modelling
Panel discussion on data management & FAIR data and Predictive modelling
- Tassos Papadiamantis, Entelos Institute (CY)
- Barry Hardy, Edelweiss Connect (CH)
- Vince Hop, Process Design Center (NL)
- Álvaro Ojeda, Idener (ES)
Organizers: BIORING, BIOSAFIRE, BioPhenom, DESIDERATA, SuperBark, SurfToGreen, and DATA4CIRC
Info: info@bioring.eu
Organizers
BIORING: Develops bio-based building blocks for novel high-performance UV-cured biocoatings with enhanced thermomechanical performance, providing a viable alternative to existing fossil-based ones for automotive, construction and furniture use cases.
BIOSAFIRE: Develops safe, sustainable flame-retardant materials using a science-based and socially responsible approach. It upscales and broadens available feedstocks to provide flame retardant in powder formats for five applications in naval, railway, household goods, and wood coatings sectors.
BioPhenom: Explores biophenols from industrial biomass side streams as replacement of SVHC in the development of safe & sustainable, bio-based, flame-retardant, and recyclable materials like wood products, CF thermoset composites, and thermoplastics for various industrial applications.
DESIDERATA: Develops safer and sustainable alternatives to substances of concern with flame retardant, plasticiser, and surfactant properties. It enhances interoperability, improving data sharing across the value chain, and promotes market uptake of sustainable alternatives fostering collaboration between industry, research, and society in the construction, 3D printing, industrial manufacturing, and injection molding sectors.
SuperBark: Explores softwood bark to develop new bio-based adhesives and coatings for a range of industrial applications. It improves the sustainability, health and safety profiles of adhesive and coating products compared to fossil-based solutions.
SurfToGreen: Develops new portfolio of fully bio-based surfactants, realized by transforming agricultural and forest residues, and other locally sourced feedstock into new safe, sustainable, and scalable solution for the European bio-based economy.
DATA4CIRC: Develops an innovative data-sharing framework to help European manufacturing prepare for a more sustainable future. It improves access to the information factories need to efficiently and safely recover, recycle, and reuse materials, and move towards a circular economy.
Speakers’ bio & abstract
Álvaro Ojeda Roldán https://www.linkedin.com/in/%C3%A1lvaro-ojeda-rold%C3%A1n-robotics-data-science-machine-learning/
Álvaro Ojeda Roldán (Seville, 1997) graduated in Electronics, Robotic and Mechatronics Engineering from the University of Seville (Spain) with an MSc in Artificial Intelligence at the International University of Valencia (Spain). He is a Project Coordinator within the Energy and Industry 5.0 Division at IDENER.AI, coordinating the DATA4CIRC project. His work has focused on data analysis and programming systems based on machine learning applied to industrial processes, evolving from a technical to a management profile. These systems have been framed in manufacturing and energy-intensive sectors to improve the efficiency of industrial processes. Moreover, he has developed a keen interest in integrating and enhancing the circular economy in those fields to contribute to the fight against climate change.
Barry Hardy https://www.linkedin.com/in/barryhardy/
CEO at Edelweiss Connect
Dr. Barry Hardy is the CEO at Edelweiss Connect, leading its team supporting the development of new integrating solutions in industrial product design and safety assessment and the translation of research methods to industrial practice. He is currently leading the development of risk assessment knowledge infrastructure and solutions, including new approach methods, SaferbyDesign, sustainability and next generation risk assessment solutions.
He coordinated the OpenTox project in predictive toxicology and is currently President of the OpenTox Association. Previously, he led the infrastructure development for the IMI EBiSC stem cell banking project, the eNanoMapper project developing solutions supporting nanotechnology safety assessment, OpenRiskNet infrastructure development supporting risk assessment, and knowledge infrastructure development for ACEnano, NanoCommons and EU-ToxRisk.
Evidence-based approaches to use of data and models in Safe and Sustainable by Design Workflows
An evidence-based approach to Safe and Sustainable by Design (SSbD) requires the structured integration of diverse data streams, models, and mechanistic knowledge within transparent and reproducible decision workflows. We present approaches developed within AI-assisted SSbD and Next Generation Risk Assessment (NGRA) frameworks that combine FAIR data infrastructures, in silico modelling, mechanistic NAMs, exposure and toxicokinetic modelling, and uncertainty analysis to support regulatory-relevant evidence generation. Central to this approach is the transformation of fragmented data into traceable evidence packages aligned to defined contexts of use, enabling more robust, interpretable, and actionable decision-making across innovation, safety assessment, and sustainability evaluation workflows.
Vince Hop https://www.linkedin.com/in/vince-hop-621b01107/
Vince (initials CJW) Hop (born in the Netherlands 1995) finished his applied Batchelor in Chemical Engineering at the Avans Applied University in Breda in 2016. As a follow up, he finished his Pre-Master, Chemical Engineering and Process Technology, at the Technical University of Eindhoven (TU/e) in 2017. He continued his studies at TU/e in the master track, Chemical Engineering, and graduated in 2019. In May 2019 he started a PhD in the Sustainable Process Engineering group (subgroup Chemical Reactor Engineering) with prof.dr.ir. J. van der Schaaf and defended his PhD thesis in 2023. Since June 2023, Vince is employed at Process Design Center where he is involved in many projects, focusing on conceptual process design, techno-economic assessments and data management/analytics.
Why Attend?
This workshop aims to promote awareness and to share views and experiences on data analysis from both researchers and data management experts and practitioners, based on the experience of running European projects on material research. It is an opportunity for exchanging knowledge and experiences, identifying gaps, good practices, and learnings on the topic.
Relevant for
Research and industry experts, partners of EU and national research projects, data providers and end users.