D3.1 - Knowledge and Data Exchange Infrastructure

Funded by the European Union under the Grant Agreement 101091464. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or European Health and Digital Executive Agency (HaDEA). Neither the European Union nor the granting authority can be held responsible for them. Sustainable surface protection by glass-like hybrid and biomaterials coatings Deliverable D3.1 Knowledge and data exchange infrastructure specifications Deliverable Information Responsible partner: 7P9-SI Work package No and Title: WP3: Computational Tools for the SSbD of Coating Materials Contributing partner(s): 7P9-DE, PQSAR, CNR Dissemination level1: PU Type: R Due date: 31 December 2023 Submission date: 22 December 2023 Version: V1.1 1 PU = PUBLIC fully open ((warning) automatically posted online on the Project Results platforms) SEN = Sensitive — limited under the conditions of the Grant Agreement EUCl = EU classified under Decision 2015/444 Ref. Ares(2023)8839591 - 22/12/2023 2 of 27 Sustainable surface protection by glass-like hybrid and biomaterials coatings D3.1: Knowledge and data exchange infrastructure specifications Project Profile Programme Horizon Europe Call HORIZON-CL4-2022-RESILIENCE-01 Topic HORIZON-CL4-2022-RESILIENCE-01-23: Safe and sustainable by design chemicals and materials (RIA) Number 101091464 Acronym BIO-SUSHY Name Sustainable surface protection by glass-like hybrid and biomaterials coatings Start Date 1 January 2023 Duration 48 months Type of action HORIZON Research and Innovation Actions Granting authority European Health and Digital Executive Agency Project Coordinator MATERIA NOVA Document History Version Date Entity Remarks 1.0 28 November 2023 7P9 Initial version 1.1 7 December 2023 PQSAR, CNR, MANO, AXIA, RESCOLL, SiKEMIA, ZSI Integration of partner comments 3 of 27 Sustainable surface protection by glass-like hybrid and biomaterials coatings D3.1: Knowledge and data exchange infrastructure specifications Publishable Summary This report describes the data collection, curation, management and sharing infrastructure of the BIO-SUSHY project. The system is supporting storage and FAIRification of all research outputs (sampling plans, study designs, in vitro and in silico method specifications, protocols, SOPs, and the data created, as well as guidelines, reports, training materials and publications), i.e. making them Findable, Accessible, Interoperable and Re-usable, for internal knowledge exchange between BIOSUSHY WP2, WP3 and WP4 partners and finally for long-term storage and public sharing. It is assisting the planning of the preparation of the coatings and the experimental and computational safety and sustainability assessment for the use cases and the organisation of the complex sample and information flow between partners and work packages required during their execution. This is achieved by the combination of four data management tools, the BIO-SUSHY Registry, the instance map tool, the BIO-SUSHY Google Shared Drive and the data collector, together providing the infrastructure for the customised BIO-SUSHY data lake. While the first three are focusing on the F (Findable) and A (Accessible) in the form of a one-stop shop for all information as well as a visual representation of the links between different research outputs, the fourth is fostering the I (Interoperable) and R (Re-usable) by providing automated workflows to translate the (meta)data as provided by the partners into computer-actionable files following the harmonised BIO-SUSHY data schema designed to fulfil requirements from data producers of WP2 (starting material characterisation and production processes), WP3 (functional and toxicity predictions) and WP4 (hazard and exposure estimation) as well as data users from WP4 (safety and life cycle assessment). 4 of 27 Sustainable surface protection by glass-like hybrid and biomaterials coatings D3.1: Knowledge and data exchange infrastructure specifications Table of Contents List of Figures ................................................................................................................................................ 5 Table of Abbreviations ................................................................................................................................. 6 1. Objectives .............................................................................................................................................. 7 2. Data generation in BIO-SUSHY ............................................................................................................ 7 3. Knowledge collection and transfer within and between work packages ......................................... 9 4. Data lifecycle and (meta)data shepherding ..................................................................................... 11 5. Indexing the data lake: the BIO-SUSHY Registry ............................................................................. 14 6. Structuring the data lake: instance maps to design and document complex studies ................. 17 7. Filling the data lake: (meta)data harmonisation and enrichment ................................................. 19 7.1. (Meta)data completeness .......................................................................................................... 19 7.2. Data collector .............................................................................................................................. 20 8. Conclusions ........................................................................................................................................ 25 9. References .......................................................................................................................................... 27 5 of 27 Sustainable surface protection by glass-like hybrid and biomaterials coatings D3.1: Knowledge and data exchange infrastructure specifications List of Figures Figure 1: Illustrated PERT-chart of the BIO-SUSHY Project structure, individual work packages (WPs) and the workflow and dependencies between them. .............................................................................. 9 Figure 2: Data management concept in which all data from experiment, computational approaches and public resources is integrated to build the data lake used as input for data-driven modelling to guide the SSbD decisions for the development of the new coatings as well as to prepare uploading to public databases. .................................................................................................................................. 10 Figure 3: Five phases of the data management life cycle. In contrast to other depictions where FAIRification is a sixth phase, FAIRification in BIO-SUSHY is starting in the Plan & Design phase and then continues throughout all other phases continuously enhancing the FAIRness of the data (onthe-fly FAIR). ............................................................................................................................................... 12 Figure 4: Screenshot of the BIO-SUSHY Registry showing four resources (1 material, 2 protocols and one data file). ............................................................................................................................................. 15 Figure 5: Screenshot of the high-level description of a BIO-SUSHY material resource for a starting material. ..................................................................................................................................................... 15 Figure 6: Screenshot of the high-level description of a BIO-SUSHY material resource for a RESCOLL formulation. ............................................................................................................................................... 16 Figure 7: Screenshot of an instance map representing the mixing procedure of the starting materials as the first step of creating coatings for the hybrid coatings on glass containers for cosmetic applications use case. ............................................................................................................... 18 Figure 8: Screenshot of an instance map representing the early planning stage of the safety and sustainability evaluation of coatings........................................................................................................ 18 Figure 9: Part of the harmonised BIO-SUSHY (meta)data schema used to describe starting materials. .................................................................................................................................................................... 20 Figure 10: Data sheet for a RESCOLL coating formulation with information on the starting materials and concentrations. .................................................................................................................................. 21 Figure 11: Workflow to extract information on the starting materials from data files on coating formulations provided by RESCOLL as well as public webservices. ...................................................... 22 Figure 12: RESCOLL coating data in JSON format structured according to the harmonised BIOSUSHY (meta)data schema. ...................................................................................................................... 23 Figure 13: Workflow to enrich RESCOLL coating data with process information, physicochemical characterisation and hazard predictions using QSAR models provided by PQSAR. ........................... 24 Figure 14: Comparison of the concentrations of starting materials in two RESCOLL coatings using automated data extraction from the harmonised (meta)data files. ..................................................... 25 Figure 15: BIO-SUSHY infrastructure for experiment planning, data collection, harmonisation, storing and sharing. .................................................................................................................................. 26 6 of 27 Sustainable surface protection by glass-like hybrid and biomaterials coatings D3.1: Knowledge and data exchange infrastructure specifications Table of Abbreviations Abbreviation Definition FAIR Findable, Accessible, Interoperable and Re-usable FAIR4RS FAIR for Research Software PFAS Perand Polyfluoroalkyl Substances SSbD Safe and Sustainable by Design LCA Life Cycle Assessment FIP FAIR Implementation Profiles PARC Partnership for the Assessment of Risks from Chemicals WPx Work Package x KMT Knowledge Management Translators ELN Electronic Lab Notebook LIMS Laboratory Information Management System JSON JavaScript Object Notation SOP Standard Operating Procedure 7 of 27 Sustainable surface protection by glass-like hybrid and biomaterials coatings D3.1: Knowledge and data exchange infrastructure specifications 1. Objectives As a part of its open science philosophy, BIO-SUSHY is implementing high quality knowledge and data management first for internal use and then public sharing. It is using state-of-the-art data sharing concepts, approaches and tools jointly developed together with the MACRAMÉ project. It is improving research output/data documentation towards full implementation of the FAIR1 (findable, accessible, interoperable and re-usable) and FAIR for Research Software2 (FAIR4RS) principles aligned with and extending community standards. This report describes the initial version of this data management system consisting of the BIO-SUSHY Registry as the central information access point, a visualisation tool (instance map) for the planning of information flows, and automated workflows for data harmonisation and enrichment (data collector). These implement the concept of on-the-fly FAIRification enhancing the data management quality at the partner institutions keeping the established experimental workflows intact for easy adoption. New data requirements identified while progressing the use cases is continuously addressed. (Meta)data completeness is improved by enriching the partner-specific (meta)data reporting formats and re-integrating the updated files as new versions of the data in the Registry. 2. Data generation in BIO-SUSHY The development of new coatings replacing PFAS components is based and guided by the SSbD methodology considering the entire life cycle and value chain of the new products. To this purpose, 3 use cases have been designed to provide competitive coating solutions with lower toxicities and environmental footprints as PFAS alternatives. Successful execution of the cases requires interdisciplinary research interlinking computational modelling, SSbD methodology and material development, in an iterative carousel approach, with key nodes of innovation. Durable waterand oil-repellent properties of the use case coatings are being achieved by: 1. Bio-based thermoplastic powder coating formulations for food tray application: BIO-SUSHY coatings will be applied onto cellulosic fibre mat, by spray or powder deposition, which will further undergo a curing process (melting of thermoplastic powder or curing of hybrid sol-gel coating). Dry powder application onto cellulosic food trays is done by electrostatic powder spraying or alternative electric field powder application processes. Melting and film formation is carried out by infraredor hot calendering. After cooling, the mat is thermoformed (between 120°C and 180°C for 1 second) to a 3D shape (e.g. food tray) using an innovative “dry moulded fibre method,” instead of using the standard “wet pulp” production method where water acts as the main carrier for fibres to the mould. 2. Hybrid water-based coatings, based on sol-gel with high content of organics to provide highly flexible layers compatible with textile applications: The precursor-synthesised sol-gels, along with functional chemicals, will be deposited onto textile fabrics in one step by padding. This is a dipping procedure where excess formulation is squeezed out by the rollers from the textile fabrics and then cured in an oven or by UV processes. This method allows the liquid formulation to penetrate between the fibre in the fabric. The main governing factors in the pad-coating process are (a) the nature of the textile substrate, (b) substrate speed, (c) surface 8 of 27 Sustainable surface protection by glass-like hybrid and biomaterials coatings D3.1: Knowledge and data exchange infrastructure specifications tension and viscosity of the formulation, (d) dry content and (e) nip pressure and the speed of the roll coater. 3. Hybrid coatings on glass containers for cosmetic applications based on sol-gel with high content in inorganic part to provide improved scratch, thermal and chemical resistance: Inner application of cosmetic glass containers allows to unsure quality, and complete availability of the products and content are protected and made to last longer. Hybrid coatings will be applied by inner spray using long nozzle and small spray head followed by post-curing. Using glass-like sol-gel technology for coating, with an emphasis on mechanical durability and low adhesion of fluids, will help the aspects of reuse as End-of-life scenario. The aim of the project is, besides the development of high-performance coatings described so far, to integrate safety and sustainability considerations following the SSbD framework into every stage of the material development stage to minimise toxicity and environmental impact of the new products. The BIO-SUSHY SSbD approach is, thus, composed of the following tasks: • Production of sol-gel precursors including hydrophobic additives and functional linkers, partly biobased, to serve as starting materials for the coatings or for surface functionalisation (SiKEMIA) • Optimisation of the formulations and corresponding thermoplastic powder coating (WoodK+) and hybrid coatings from sol-gel technologies (MANO, RESCOLL and IFTH). • Physicochemical performance testing (WoodK+, MANO, RESCOLL, IFTH) • Computational optimisation of functionality (CNR, PQSAR) • Occupational exposure evaluation (ITENE) • Human and environmental toxicology testing (UNIVLEEDS, ITENE, RESCOLL, MANO) • Computational data gap filling for physico-chemical characterisation, human and environmental risk assessment (PQSAR, CNR) • Environmental and social life-cycle assessment (MANO, WOODK+, IFTH, RESCOLL) • Up-scaling and validation (MANO, WOODK+, RESCOLL and IFTH) • Performance/SSbD and social acceptance evaluation (ECOZEMA, ZSI) • Stakeholder consultation in the context of the value chain analysis (ZSI). These tasks are not executed sequentially but, at the same time, implement important feedback loops, achieving the transition from safety and sustainability assessment of final products to guaranteeing safety and sustainability of the final product by integrating these criteria into the design process. It is clear that the list above is not describing the complete BIO-SUSHY project, and this was also not the goal. Instead, it is meant to show the many players involved in data production with many dependencies on data provided by other partners used as input for downstream data generation, analysis and decision making. For example, physicochemical data on the starting material either collected by the coating developers or predicted by data-driven or physics-based modelling approaches are needed for selection of the human and ecotox test battery, occupational exposure estimation as well as environmental and social life cycle assessment (LCA). All this information will 9 of 27 Sustainable surface protection by glass-like hybrid and biomaterials coatings D3.1: Knowledge and data exchange infrastructure specifications then be integrated into the SSbD evaluation of the products, which then guides new optimisation cycles of the formulations, production techniques, and scale up. This need for intensive and timely knowledge exchange between partners but especially also between WPs was envisioned at proposal stage, visualised by showing WP2, WP3 and WP4 as a highly interlinked, inseparable group in the WP overview (see Figure 1), and acknowledged by bringing in a partner (7P9) specifically for coordinating data harmonisation and sharing and providing new tools for planning of the complex material and data flows, knowledge exchange, and centralised data tracking, management and storage. Figure 1: Illustrated PERT-chart of the BIO-SUSHY Project structure, individual work packages (WPs) and the workflow and dependencies between them. 3. Knowledge collection and transfer within and between work packages As described in the previous chapter, many partners are generating or (re-)using data and information of many different types. These are coming from documentation of formulation and coating processes including important production parameters, chemical data sheets and supply chain information of starting materials (for safety assessment and LCA), information on production sites (for occupational exposure assessments), safety dossiers including data from similar chemicals and materials, life-cycle inventories and then, the computational and safety testing methods developed by and applied in BIO-SUSHY. To be re-usable by other project partners, the shared information needs to include more than the data (numbers) per se but needs to be accompanied by study designs translating needs into actions, method specifications describing the measurement principles, protocols and standard operating procedures (SOP), and clear provenance trails to the origin of the data. Data to be shared includes not only data generated for the final coating of the three use cases but every produced data point with their specific protocols from early development, calibration, and control measurements to document integration of all aspects (functionality, economical validity, safety, sustainability) in the development cycles according to the SSbD Framework. To enable such a very intense multi-way exchange of information and knowledge, a customised data infrastructure is needed, which puts WP3 with its task to coordinate data harmonisation, central data storage and support of the partners in preparing data for re-use in the centre of the project. At the moment, there is no out-of-the-box data system available providing the functionality and flexibility 16 of 27 Sustainable surface protection by glass-like hybrid and biomaterials coatings D3.1: Knowledge and data exchange infrastructure specifications Figure 6: Screenshot of the high-level description of a BIO-SUSHY material resource for a RESCOLL formulation. Formats, in which the actual resources are prepared, vary from one partner to another. For example, method descriptions and protocols/SOPs are often available as text documents (Microsoft Word, Google docs or pdf) while data is provided as spreadsheets (Microsoft Excel). However, some partners also use electronic lab notebooks (ELN) and automatic data capturing workflows or proprietary file formats. As explained above, at this early stage of the project, it is most important to not cause time delays by not sharing (meta)data between partners and work packages. Therefore, instead of forcing all resources into a predefined template, the Registry supports all these different reporting styles. Use cases can start discussing results on this basis with missing technical interoperability replaced by human interactions and discussions. To provide the needed flexibility, a resource is just specified by an URL, which in many cases links to a folder in the BIO-SUSHY Google Shared Drive but could also redirect to e.g. a page of an ELN. Using the paid Google service instead of the free version provides higher data security and access restrictions including enforcing the hosting of the data on European servers. BIO-SUSHY WP2, WP3 and WP4 partners have started populating the Registry with information specifically on starting materials, formulations, safety information extracted from chemical data sheets as well as on previous / preliminary experiments. In this way, the status of data management at each partner, used management tools, file formats and data completeness are documented in these examples. This is now being used to identify commonalities in data documentation, to define minimal data and metadata to be reported for each type of research output and find (meta)data gaps hindering the reuse of the data internally and later public sharing. Based on this analysis, recommendations for improvements of data management at each partner to fill the identified gaps are being suggested, harmonised (meta)data schemas and data transfer formats are proposed and aligned to community standards, still allowing flexibility to adapt to specific data types. Mappings between the data schemas used internally by a partner to these harmonised transfer formats and semi-automatic data transformation procedure are being created and are described in Section 7. This improvement of the data management practices will continue throughout the project and will finally generate data of highest FAIRness levels for public sharing. Even if this represents a major shift 17 of 27 Sustainable surface protection by glass-like hybrid and biomaterials coatings D3.1: Knowledge and data exchange infrastructure specifications in the way data of large project consortia is managed, high quality and computer actionability will be achieved with little changes in the partner-internal workflows with respect to used data management tools and formats and with manual data transformation limited to the absolute minimum. 6. Structuring the data lake: instance maps to design and document complex studies Besides high-level data documentation and easy access via the BIO-SUSHY Registry, the complex design of the use cases and the related experimental workflows puts additional demands on the knowledge transfer with respect to showing the links between resources and the (virtual) flow of data but also physical transfer of materials and samples between work packages and partners. Instance maps have been successfully applied for such purposes and are now interfaced with the BIO-SUSHY Registry to not only visualise the workflows but also give direct access to the data. Instance maps were first used as organisational structure in the data curation efforts for the NIKC (NanoInformatics Knowledge Commons); they enable users to follow nanomaterial transformations, while capturing necessary metadata. An instance is defined as the nanomaterial in a medium at a specific moment in time. An instance map then represents a flow chart of the nanomaterial fate represented as a directed, often tree-like graph built out of nodes connected by edges represented as arrows to show the directionality. To support the quick generation of such maps, a specific software tool was developed in the NanoCommons project and integrated into the data management infrastructure7. The tool introduced a couple of modifications and new features: 1. Besides the five node categories (instance, material, medium, property, and supplementary) of the original approach, transformation protocol nodes explicitly describing the processes leading from one instance to the next, protocols/SOP nodes for experimental details and data nodes were added. 2. Information resources can be associated with each node. These new features make instance maps an optimal planning and monitoring tool for the experimental work by visualising the BIO-SUSHY use cases or parts of them like mixing the starting materials (Figure 7) or information integrated in the SSbD assessment (Figure 8) by showing material flows and dependencies of experiments. Nodes can be linked to the resources in the Registry providing structure to the many resources e.g. associated with a use case, giving easy access to all information needed to start the next phase of the study, and in this way, supporting the management of the studies and of the overall project. Planning of the experimental work and workflows using the tool has been started as a series of co-creative training sessions resulting in partial instance maps as show in the examples, which are now further refined and filled with / linked to the generated Registry resources. 18 of 27 Sustainable surface protection by glass-like hybrid and biomaterials coatings D3.1: Knowledge and data exchange infrastructure specifications Figure 7: Screenshot of an instance map representing the mixing procedure of the starting materials as the first step of creating coatings for the hybrid coatings on glass containers for cosmetic applications use case. Figure 8: Screenshot of an instance map representing the early planning stage of the safety and sustainability evaluation of coatings. 19 of 27 Sustainable surface protection by glass-like hybrid and biomaterials coatings D3.1: Knowledge and data exchange infrastructure specifications 7. Filling the data lake: (meta)data harmonisation and enrichment As described in Section 4, FAIR data sharing requires harmonisation of data to achieve interoperability, but current lab workflows are not developed around standardised data exchange formats. Instead, they use customised files or ELNs / laboratory information management systems (LIMS) with customised data models. BIO-SUSHY is not different with e.g. RESCOLL using an internal LIMS while other partners use Excel-based data analysis and storage. Completely changing the data storage formats within partner organisations to be based on a common standard is not feasible and, even more important, not sensible since it would require retraining personnel just for this project and would remove the flexibility from the lab workflows to report all important parameters, without making the data model unmanageably complex. Data reporting templates were proposed for (nano)materials in the past7, which expected some standard metadata to be filled in together with the data. However, one could argue that harmonisation and interoperability require in principle only that the (meta)data is reported in a digital form but not which specific structure is used. The FAIR principle accordingly only requires that the data is reported according to domain-agreed community standards. As these standards are well documented, translating from one to another is possible similarly to translating languages. BIO-SUSHY is taking the idea even further and accepts customised partner-specific files. To achieve harmonisation and interoperability, these files have in most cases still to be improved to 1) guarantee that all required metadata is available to make the data understandable for others (either as part of the modified (meta)data file or as accompanying metadata files) and 2) the data structure in the (meta)data file is documented to allow mapping of data between different metadata schemas (the original partner-specific schema and a harmonised BIO-SUSHY schema). 7.1. (Meta)data completeness (Meta)data completeness in BIO-SUSHY is, on one hand, defined by the data requirements of the project-internal data users. However, for final public sharing of the data without additional manual effort, i.e. on-the-fly FAIRification, cross-discipline and community specific (meta)data requirements (minimal reporting checklists and standards) have also to be considered from the start. The latter is achieved by consulting metadata standards endorsed by the FAIR community and relevant scientific communities and selection of the most appropriate ones guided by the data shepherd. For example, bibliographic and data provenance metadata requirements can be taken from different web standards and data services (e.g. DataCite, schema.org and bioschemas.org, DDI). Again, it is important that the BIO-SUSHY solution provides the information requested by the (minimal) information standards, but it does not necessarily need to follow the exact same format or even data structure. In this way, multiple standards can be combined, e.g. if they are missing some but not the same metadata fields considered essential by BIO-SUSHY. Additionally, standards can also be reused only partly if only substructures of the complete data schema are relevant (e.g. the fields related to authors, origin and supporting citation of the DataCite schema but not necessarily funding). Completeness with respect to all the data usages in BIO-SUSHY is currently established by collecting the data requirements from WP3 with respect to input generation for modelling and simulations and WP4 with respect to toxicity testing, occupational exposure estimation and (social) LCA and mapping them onto data provision from WP2 and WP3. Since much of the metadata is needed for multiple 20 of 27 Sustainable surface protection by glass-like hybrid and biomaterials coatings D3.1: Knowledge and data exchange infrastructure specifications applications and can come from multiple sources (experimental vs. computational, specific partners for the different use cases), data exchange needs are first discussed in the use cases or even between individual pairs or groups of partners. However, the results of this metadata scoping exercise are then combined into one central and global data model so that data users can check if a specific (meta)data field is already planned to be collected, by whom and using which method and data producers do not have to send the same data multiple times to different data users and potentially in different formats. A part of an early version of this harmonised BIO-SUSHY data schema is shown in Figure 9, using the visualisation capacity of the instance map tool to demonstrate the structure between different (meta)data points. In addition, a JSON file showing exactly the same structure is maintained, which builds the basis for the computer-actionable documentation of the BIO-SUSHY data model. JSON has the advantage that the structure can easily be amended and locally restructured to integrate new requirements that show up during further progression of the use cases. Additionally, the data model documentation can be further enriched by including information on the expected data type, relationships between data entries, and even annotation with ontology terms essential for integrating BIO-SUSHY data into the semantic framework of the materials data ecosystem. Combined with the data collector described in the next subsection, which is used for extracting data from partner-specific files, this setup provided the flexibility to generate the first versions of the datasets now and can be used to update these automatically, when improvements in data completeness and/or data documentation/annotation are requested by the data providers or users. Figure 9: Part of the harmonised BIO-SUSHY (meta)data schema used to describe starting materials. 7.2. Data collector To reduce the time invested into data management and harmonisation by the data providers, the data collector software library is being developed by 7P9. This library is used to extract data from partner-specific data files, translate the data according to the harmonised BIO-SUSHY data schema, and enrich the data by querying public services. The process is described below with the example of a coating formulation from partner RESCOLL. Starting point is the data file, which is generated by the LIMS used by RESCOLL, that holds information on the starting materials, mixing information and basic characterisation of the coating (see Figure 10). 21 of 27 Sustainable surface protection by glass-like hybrid and biomaterials coatings D3.1: Knowledge and data exchange infrastructure specifications Figure 10: Data sheet for a RESCOLL coating formulation with information on the starting materials and concentrations. After the data producer has uploaded a data file to the BIO-SUSHY Google Shared Drive, the semiautomated workflow visualised in Figure 11 is started. Since the content of Excel worksheets cannot be directly accessed on the drive, the files are downloaded and stored locally for data extraction. A customised script based on the data collector is used to fill the harmonised BIO-SUSHY data schema for coatings with all information available in the file by accessing individual cells or blocks of cells in the spreadsheets. At the same time, the script performs basic checks on the content, like expected data type, to guarantee the consistency of the integrated data. In principle, the data collector could also directly access RESCOLL’s LIMS without the need for EXCEL files for data exchange. However, this would need establishing a secure exchange between the two systems and exchange policies, which is out of scope of the BIO-SUSHY project. Additional information, needed for complete documentation and (meta)data completeness not provided in the RESCOLL data files, can be provided in additional files of different formats. This is shown in Figure 11 as the second input in the form of the RESCOLL material information sheet, which provides CAS registry numbers as well as supplier and batch information for the starting materials. For each starting material, a parallel workflow is started. This extracts, if not already available from previous executions of the workflow, additional chemical identifiers (InChI, InChI key, SMILES) and basic physicochemical properties from web services like the Chemical Abstract Services Common Chemistry and PubChem. This information is then stored according to the (meta)data schema for starting materials as individual material entries in the BIO-SUSHY Registry. Unique identifiers assigned by the Registry and a subset of the starting material information are then stored as part of the coating data. In this way, the starting materials are chemically defined in the coating data and additional data is accessible by following the link to the starting material Registry entries. Finally, information on the mixture (mixing order, concentrations, masses) and basic characteristics are added and new material entities for the mixture and coating are created on the Registry. The Registry entities are linked to the Google Drive that stores the (meta)data files in both the original RESCOLL format and the harmonised format. 22 of 27 Sustainable surface protection by glass-like hybrid and biomaterials coatings D3.1: Knowledge and data exchange infrastructure specifications Figure 11: Workflow to extract information on the starting materials from data files on coating formulations provided by RESCOLL as well as public webservices. 23 of 27 Sustainable surface protection by glass-like hybrid and biomaterials coatings D3.1: Knowledge and data exchange infrastructure specifications Figure 12: RESCOLL coating data in JSON format structured according to the harmonised BIO-SUSHY (meta)data schema. 24 of 27 Sustainable surface protection by glass-like hybrid and biomaterials coatings D3.1: Knowledge and data exchange infrastructure specifications Parts of the resulting harmonised coating (meta)data file are shown in Figure 12. It has to be noted here that the file format was chosen for computer actionability not human readability. Due to its welldefined structure, data can be either directly used as input for the different modelling approaches or further transformed to fit the need of data users (computational, safety and exposure assessment, LCA) with respect to content and format. Following the study plan documented and visualised in the instance maps (see Figure 8) the information on the coatings is then further enriched by advanced characterisation. This includes data from the production of the coating (e.g. information on the substrates, production parameters) and up-scaling from WP2, from modelling in WP3 and risk and sustainability assessment from WP4 with all related protocols, SOPs and documentation of results and conclusion. These are stored as updated versions of the coating Registry entries linked to additional methods, protocols, SOPs, and data Registry entries. This data enrichment with information coming from different partners and the workflow to integrate the data into the Registry are visualised in Figure 13. Figure 13: Workflow to enrich RESCOLL coating data with process information, physicochemical characterisation and hazard predictions using QSAR models provided by PQSAR. As mentioned above, the harmonised, highly structured (meta)data files can then be further transformed to provide for the data needs of downstream tasks. Figure 14 shows a simple example of such further analysis performed automatically using the harmonised coating (meta)data. Concentrations of the starting materials in two different RESCOLL coatings are extracted from the Registry and then visualised. The differences can then be correlated with the functional and SSbD properties for further optimisation of the coatings. 25 of 27 Sustainable surface protection by glass-like hybrid and biomaterials coatings D3.1: Knowledge and data exchange infrastructure specifications Figure 14: Comparison of the concentrations of starting materials in two RESCOLL coatings using automated data extraction from the harmonised (meta)data files. As a conclusion of this section, we want to highlight a critical feature of the automatic procedure that profits from features of the Registry, instance maps and data collector presented here. As described in the previous subsection, the harmonised BIO-SUSHY (meta)data schema is not completely defined yet, since data requirements from safety and sustainability assessment will be refined alongside the progress in the use cases. This is not only related to additional data needs but also to metadata completeness to fully document the production and testing for reuse by other partners and finally open sharing. This additional (meta)data could be directly added to the Registry entries and the linked data files. However, the improvement would then apply only to these entries, while data providers would still generate incomplete (meta)data for new coatings, which would then need to be amended later. Instead, updating the partner-specific files to integrate the additional information is improving the data management of the partners, and new data is already complying with the higher quality standards. (Re)running the automatic harmonisation workflow then integrates all data into new versions of the harmonised files of existing Registry entries or the first versions of new coating candidates. In that way, data harmonisation and on-the-fly FAIRification can be implemented and continuously enhanced with only minor modifications in the established experimental workflows at the partner institutions. 8. Conclusions At this stage in the project, the knowledge management and sharing system is focusing on assisting the planning of the experiments supporting the use cases and organising the complex sample and information flow between partners and work packages required during their execution. This is achieved by the combination of four data management tools, the BIO-SUSHY Registry, the instance map tool, the BIO-SUSHY Google Shared Drive and the data collector, together providing the infrastructure for the customised BIO-SUSHY data lake. The interplay of the tools is shown in Figure 15.