Multiple changes in docs and testdata

Author: HendrikBorgelt

catcore_linkml.xlsx

@@ -8,18 +8,21 @@ TA5 is the engine of knowledge transfer and adoption for the NFDI4Cat digital to
 
 ### Core Objectives
 The objectives are highly practical and focused on implementation:
+
 * **Define Use Cases:** Identifying and developing **highly relevant use cases** drawn from both industry needs and cutting-edge academic research.
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 * **Brokering and Consultation:** Serving as the central point for brokering these use cases and consulting with domain partners on the implementation of **Voc4Cat** ontologies and **CatCore** metadata standards.
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 * **Guiding Data Space Population:** Actively guiding partners on how to populate the specific use case data spaces, ensuring data quality and adherence to standardization protocols.
 
 This partnership is designed to foster a continuous feedback loop, ensuring the digital tools are assessed, optimized, and utilized effectively in a real-world, high-stakes environment.
 
 ### Industry Partners and Focus Areas
 The involvement of major industrial players validates the infrastructure's relevance. Key partners include:
-* **BASF SE**
-* **hte**
-* **Evonik**
-* **Linde**
+[* **BASF SE**]: #
+[* **hte**]: #
+[* **Evonik**]: #
+[* **Linde**]: #
 
 Their shared focus is on advancing **sustainable production processes** for key chemical intermediates, such as various alcohols and olefins derived from synthesis gas, guaranteeing that the NFDI4Cat tools address high-impact industrial challenges.
 
@@ -28,7 +31,9 @@ Their shared focus is on advancing **sustainable production processes** for key
 To encourage participation and offset the cost of digitization efforts, **FlexFunds** are made available, but their usage and the rules regarding data contribution are strict.
 
 ### FlexFunds Guidelines
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 * **Purpose:** FlexFunds are strictly intended to support **data collection and digitization activities** directly related to the defined use cases. This can include personnel time for data structuring, metadata capture, and tool implementation.
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 * **Limitation:** These funds **cannot** be used to finance new experimental research or core research expenses.
 
 ### Confidentiality Guarantee
@@ -46,12 +51,14 @@ The digital infrastructure is being designed with the future of catalysis resear
 
 ### Machine Learning and Autonomous Research
 The standardized, high-quality data generated by the system is the perfect fuel for **Machine Learning (ML)** models. The goal is to move towards **autonomous research**, enabling:
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 * Real-time control and optimization of experiments.
 * Prediction of catalyst performance under novel conditions.
 * Automation of routine data curation and analysis tasks.
 
 ### Structured Experimentation
 The infrastructure strongly encourages a **Design of Experiment (DoE)** approach. DoE provides a structured, statistical methodology for planning and analyzing experiments, helping researchers:
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 * Minimize experimental runs needed to gain statistically significant results.
 * Reduce implicit human biases often introduced during traditional trial-and-error methods.
 * Maximize the informational value of every data point collected.

docs/a_heros_journey.md docs/a_heros_journey/a_heros_journey.mddocs/a_heros_journey.md renamed to docs/a_heros_journey/a_heros_journey.md

@@ -11,6 +11,7 @@ Given the participation of industry partners like BASF SE, security is paramount
 
 ### Functional Requirements
 Beyond security, the platform must facilitate efficient research. Key functional requirements include:
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 * **User and Access Management:** Precise control over who can view, upload, or modify specific data sets.
 * **Data Ingestion and Metadata Capture:** Streamlined tools for uploading data while immediately capturing mandatory metadata.
 * **Discoverability and Querying:** Features that allow researchers to easily find relevant data through standardized metadata fields.

docs/collaboration_and_future.md …eros_journey/collaboration_and_future.mddocs/collaboration_and_future.md renamed to docs/a_heros_journey/collaboration_and_future.md docs/collaboration_and_future.md renamed to docs/a_heros_journey/collaboration_and_future.md

@@ -31,6 +31,7 @@ To transition data from the "quickfix" spreadsheets into the machine-readable da
 
 ### The Autofill Tool (Python Script)
 This custom script is the backbone of the current workflow. Its purpose is to overcome institutional formatting differences. The script automatically:
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 1.  **Reads Data:** Ingests data from the varied individual Excel spreadsheets submitted by the partners.
 2.  **Validates:** Checks against the mandatory fields defined by **CatCore**.
 3.  **Transports and Unifies:** Maps and writes the extracted data into a single, standardized, master data template.
@@ -39,6 +40,7 @@ This script ensures that the structural integrity of the final data set is maint
 
 ### The Excel-to-JSON Converter (KIT Quickfix)
 To make the standardized spreadsheet data instantly usable for machine analysis, a converter was developed. This tool transforms the structured spreadsheet data into:
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 * **JSON** (`.json` files): Ideal for object storage and web-based applications.
 * **CSV** (`.csv` files): Essential for use in data science libraries and ML models.