From Data Integrity to FAIR Principles

Intro: Integrity to FAIR Planning: The DMP Operations: RDM in Practice Metadata: Serialization Metadata: Semantics Publishing From Data Integrity to FAIR Principles An Interactive Learning Experience for RDM National Engineering School of Sfax, HMC & KIT M.-A. Koubaa 29. December, 2025 | | 1 Intro: Integrity to FAIR Planning: The DMP Operations: RDM in Practice Metadata: Serialization Metadata: Semantics Publishing Our Agenda: A 2-Part Learning Experience How We’ll Work This is an interactive workshop. The slides contain prompts, activities, and discussions. Our goal is not just to list objectives, but to achieve them together. We will use Discussion, Think-Pair-Share, and Workshops. Part 1: Foundations & Operations IGoal 1: From Data Integrity to FAIR IGoal 2: The Planning Phase (DMPs) IGoal 3: RDM in Research Operations Part 2: Metadata in Practice IGoal 4: Metadata Serialisation IGoal 5: Semantics & Vocabularies IGoal 6: Publishing Your Metadata | | 2 Intro: Integrity to FAIR Planning: The DMP Operations: RDM in Practice Metadata: Serialization Metadata: Semantics Publishing Part 1 - Goal 1: From Data Integrity to FAIR Our Goal By the end of this module, we will be able to connect the core ethical duty of Data Integrity to the practical framework of the FAIR Principles. | | 3 Intro: Integrity to FAIR Planning: The DMP Operations: RDM in Practice Metadata: Serialization Metadata: Semantics Publishing Warm-Up: Defining Our Terms Group Discussion (10 min) In your own words... IWhat is Data Integrity? (Hint: Think accuracy, completeness, and consistency) IWhat are the four pillars of the FAIR acronym (F, A, I, R)? IList three Guidelines from the DFG Code of Conduct concerning Data Integrity. | | 4 Intro: Integrity to FAIR Planning: The DMP Operations: RDM in Practice Metadata: Serialization Metadata: Semantics Publishing Connecting the Dots: Integrity →Reusability Think-Pair-Share (10 min) Scenario: A researcher publishes data with poor integrity (e.g., missing labels, un-logged changes). IHow does this break the Reusability (’R’) principle? (Explain the causal relationship.) IExplain how adhering to the FAIR Principles is crucial to reach accordance with the DFG guidelines. Our Goal To explain this causal relationship: No Integrity →No Reusability. | | 5 Intro: Integrity to FAIR Planning: The DMP Operations: RDM in Practice Metadata: Serialization Metadata: Semantics Publishing Activity: The Concordance Checklist Activity: Write a Checklist (15 min) You are helping a new researcher. Task: Draft a 5-point checklist to help them assess their own concordance with the guide lines. Focus: Apply data validation and cleaning techniques (e.g., scripting checks, normalization) to ensure data integrity. IExample: ”Is there a script check for normalization?” IExample: ”Have I checked for consistency across datasets?” Goal: Write a checklist to help researchers assess their concordance. | | 6 Intro: Integrity to FAIR Planning: The DMP Operations: RDM in Practice Metadata: Serialization Metadata: Semantics Publishing Discussion: Authenticity vs. Accessibility Discussion (10 min) A Persistent Identifier (PID) serves both Data Integrity and FAIR. Task: Differentiate between the technical requirements for guaranteeing data Authenticity (Integrity) versus data Accessibility (FAIR). Analyze how PIDs serve both functions. Identify criteria of publication platforms and describe the importance of the find-ability-degree in selecting where to publish. | | 7 Intro: Integrity to FAIR Planning: The DMP Operations: RDM in Practice Metadata: Serialization Metadata: Semantics Publishing Case Study: Data Storage Appraisal Personal Evaluation (10 min) Think about a current data storage system you use. Task: Appraise it against two main criteria: 1. Criteria for long-term Data Security (Integrity). 2. Technical requirements for machine accessibility (’A’ of FAIR). | | 8 Intro: Integrity to FAIR Planning: The DMP Operations: RDM in Practice Metadata: Serialization Metadata: Semantics Publishing Challenge: Developing a Metadata Standard Workshop: Develop a Standard (15 min) Task: Develop a comprehensive, integrity-focused Metadata Standard for your project. Requirement: When implemented, this standard must ensure the resulting data and documentation will meet all four FAIR principles.Distinguish different types of interoperability (The five stars) and explain how your standard addresses them. | | 9 Intro: Integrity to FAIR Planning: The DMP Operations: RDM in Practice Metadata: Serialization Metadata: Semantics Publishing Activity: ELN Documentation Activity: Mandatory Records (15 min) Task 1: Project Closure IList the mandatory data records (e.g., metadata files, raw data, analysis scripts) required for project closure according to institutional RDM policy. Task 2: Acquisition IIdentify the mandatory metadata fields (e.g., sample ID, instrument ID, timestamp) that must be captured and logged in the Electronic Lab Notebook (ELN) upon initial data acquisition. | | 16 Intro: Integrity to FAIR Planning: The DMP Operations: RDM in Practice Metadata: Serialization Metadata: Semantics Publishing Traceability and Automation Discussion (15 min) Access Controls: Summarise the differences in data access controls (e.g., restricted vs. open) and explain how these choices impact the operational security workflow during the research phase. Automation (ELN & Registry): Illustrate how connecting an Instrument Registry (or inventory) to the ELN automatically fulfils the ’F’ (Findable) and ’I’ (Interoperable) principles by linking data to certified instrument calibration records. | | 17 Intro: Integrity to FAIR Planning: The DMP Operations: RDM in Practice Metadata: Serialization Metadata: Semantics Publishing Workshop: Version Control and Data Streams Workshop: Hands-On Traceability (25 min) Task 1: Execution IExecute the process of version control (e.g., using Git) on analysis scripts and associated documentation, ensuring traceability of all research operations. Task 2: Configuration IConfigure amessage broker (e.g., RabbitMQ, Kafka) topic or queue to receive, timestamp, and route data streams originating from a specific laboratory instrument (simulated). | | 18 Intro: Integrity to FAIR Planning: The DMP Operations: RDM in Practice Metadata: Serialization Metadata: Semantics Publishing Troubleshooting the Pipeline Scenario: Data Annotation and Troubleshooting (15 min) Differentiation: Differentiate between data annotation methods suitable for qualitative data (e.g., coding schemas) and those for quantitative data (e.g., controlled vocabularies). Analyze their respective impacts on data quality and interoperability. Troubleshooting: Troubleshoot a data pipeline error by analyzing the message broker’s log files to locate where the data structure was altered between instrument output and ELN ingestion. | | 19 Intro: Integrity to FAIR Planning: The DMP Operations: RDM in Practice Metadata: Serialization Metadata: Semantics Publishing Final Activity: Workflow Design Activity: Compare, Assess, and Design (15 min) Comparison: Compare and evaluate the data integrity of two data collection methods: 1) manual entry into a spreadsheet versus 2) automated capture via a message broker pipeline.Justify the superior method based on verifiability criteria. Design: Design a resilient, end-to-end RDM workflow for data collection that starts with an instrument, passes through a message broker for standardisation, and deposits fully documented raw data directly into the ELN. | | 20 Intro: Integrity to FAIR Planning: The DMP Operations: RDM in Practice Metadata: Serialization Metadata: Semantics Publishing Part 2 - Goal 4: Metadata Serialisation Our Goal We will focus on the *structure* of metadata. It’s not just *what* you record, but *how* you encode it (XML, JSON, etc.). | | 21 Intro: Integrity to FAIR Planning: The DMP Operations: RDM in Practice Metadata: Serialization Metadata: Semantics Publishing Warm-Up: Structural Differences Group Brainstorm (10 min) Recall the core components of a minimal metadata standard such as Dublin Core (e.g., Creator, Date, Title, Keywords). Recall the structural differences between common metadata serialization formats, such as XML,JSON, and CSV. | | 22 Intro: Integrity to FAIR Planning: The DMP Operations: RDM in Practice Metadata: Serialization Metadata: Semantics Publishing Differentiation and Annotation Discussion and Workshop (20 min) Differentiation: IDifferentiate between descriptive metadata (what the data is) and technical metadata (how the data was created). IDifferentiate between the role of a metadata schema (defining structure) and a serialisation format (encoding structure). Annotation: IAnnotate a raw dataset file by applying a selected minimal metadata schema (e.g., using Dublin Core). IExport the result in a specified serialisation format (e.g., JSON). | | 23 Intro: Integrity to FAIR Planning: The DMP Operations: RDM in Practice Metadata: Serialization Metadata: Semantics Publishing Comparison and Transformation Activity (15 min) Comparison: Compare two different serialization formats (e.g., XML vs. JSON) for the same dataset. Analyze their respective efficiencies in terms of machine parsing and storage overhead.Justification: Justify the selection of a specific serialization format for a project based on the constraints of the intended data pipeline or repository (e.g., selecting JSON-LD for web environments). | | 24 Intro: Integrity to FAIR Planning: The DMP Operations: RDM in Practice Metadata: Serialization Metadata: Semantics Publishing Final Activity: Schema Transformation Workshop: Transformation (10 min) Task: Transform a project’s internal, proprietary metadata scheme into a standardized serialization format (e.g., using a dedicated parsing script or XSLT transformation) that complies with repository requirements. | | 25 Intro: Integrity to FAIR Planning: The DMP Operations: RDM in Practice Metadata: Serialization Metadata: Semantics Publishing Workshop: Mock Submission Workshop (15 min) Task 1: KITOpen IUpload a fully documented dataset and its associated metadata file to the KITOpen repository (conceptual), ensuring all required fields are correctly populated. IDifferentiate between the institutional schema used by KITOpen and Dublin Core, analyze where mapping is required. Task 2: OEP IPopulate an OEP metadata submission template using controlled vocabularies relevant to energy systems research. ICompare the required access policy settings between KITOpen and the OEP. | | 32 Intro: Integrity to FAIR Planning: The DMP Operations: RDM in Practice Metadata: Serialization Metadata: Semantics Publishing Final Activity: Publication Strategy Final Activity (15 min) Appraisal and Justification: IAppraise a draft KITOpen metadata record to ensure the selected reuse license (e.g., CC-BY) appropriately balances ’A’ and ’R’ principles. IJustify the decision to cross-reference the OEP metadata entry with a corresponding publication, assessing the benefit to Find-ability. Synthesis: IDraft the final, publicly visible data citation and abstract for a dataset, optimising the text for indexing within the KITOpen platform. ISynthesise a final publication strategy that integrates the institutional requirements of KITOpen with the domain-specific indexing capabilities of the OEP.| | 33 Intro: Integrity to FAIR Planning: The DMP Operations: RDM in Practice Metadata: Serialization Metadata: Semantics Publishing Thank You All Goals Achieved! You can now connect Data Integrity to FAIR, build a DMP in RDMO, integrate RDM into operations, serialize and semantically enrich metadata, and publish on KITOpen and OEP. Questions? | | 34