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diff --git a/README.md b/README.md
@@ -8,7 +8,7 @@ This knowledge base is a collection of documents and references important to the
 
 ## Contributing to the Knowledge Base
 
-If you want to contribtute to the Knowledge base, please see the [CONTRIBUTING.md](CONTRIBUTING.md) file, and be sure to add yourself to the [CONTRIBUTORS.md](CONTRIBUTORS.md) file.
+If you want to contribtute to the Knowledge base, please see the [02-contributing.md](https://github.com/NFDI4Microbiota/nfdi4microbiota-knowledge-base/blob/main/docs/_Getting-Started/02-contributing.md) file, and be sure to add yourself to the [03-contributors.md](https://github.com/NFDI4Microbiota/nfdi4microbiota-knowledge-base/blob/main/docs/_Getting-Started/03-contributors.md) file.
 
 ## License
 

diff --git a/_includes/navbar.html b/_includes/navbar.html
@@ -171,4 +171,4 @@ <h5 class="offcanvas-title text-white" id="bdNavbarOffcanvasLabel">NFDI4Microbio
       </div>
     </div>
   </nav>
-</header>
+</header>
diff --git a/_includes/sidebar.html b/_includes/sidebar.html
@@ -25,11 +25,13 @@
                         <ul class="btn-toggle-nav list-unstyled fw-normal pb-1 small">
                             <!-- Docs = document object with font matter info -->
                             {% for doc in collection.docs %}
-                            <!-- list-group-flush list-group-item-action needed for the full size pill with no borders-->
-                            <!-- list-group-item-secondary needed for gray highlight -->
-                            <li><a href="{{ doc.url | relative_url }}" id="sidebar-link"
-                                    class="link-dark rounded list-group-flush list-group-item-action {% if doc.empty %} text-muted {% endif %} {% if doc.url == page.url %} list-group-item-secondary {% endif %}">{{
-                                    doc.title }}</a></li>
+                                <!-- list-group-flush list-group-item-action needed for the full size pill with no borders-->
+                                <!-- list-group-item-secondary needed for gray highlight -->
+                                {% unless doc.hide %}
+                                <li><a href="{{ doc.url | relative_url }}" id="sidebar-link"
+                                        class="link-dark rounded list-group-flush list-group-item-action {% if doc.empty %} text-muted {% endif %} {% if doc.url == page.url %} list-group-item-secondary {% endif %}">{{
+                                        doc.title }}</a></li>
+                                {% endunless %}
                             {% endfor %}
                         </ul>
                     </div>

diff --git a/docs/_Getting-Started/01-introduction.md b/docs/_Getting-Started/01-introduction.md
@@ -34,8 +34,8 @@ are collected.
 ## How to use this resource
 
 The available resources are shown in the left navigation. Clicking on
-the link will toggle the visibility of sub-content. This resources is
-puslished under the Creative Commons Attribution
+the link will toggle the visibility of sub-content. This resource is
+published under the Creative Commons Attribution
 ([CC-BY](https://creativecommons.org/licenses/by/4.0/)).
 
 ## How to find a resource

diff --git a/docs/_Reproducible-Data-Analysis/02-workflows.md b/docs/_Reproducible-Data-Analysis/02-workflows.md
@@ -12,7 +12,7 @@ This page should give an overview of suggested standards for workflows. Not all
 
 ## FAIR Principles for Data management
 
-In NFDI4Microbiota, we aim to follow the FAIR principles for data management (see [here](https://nfdi4microbiota.github.io/nfdi4microbiota-knowledge-base/RDM/03-fair) for more details).
+In NFDI4Microbiota, we aim to follow the FAIR principles for data management (see [here](https://nfdi4microbiota.github.io/nfdi4microbiota-knowledge-base/Research-Data-Management/04-fair) for more details).
 In essence, data should be Findable, Accessible, Interoperable, and Reusable.
 For workflows this means, data and/or results in the form of processed data should (if possible):
 

diff --git a/...earch-Data-Management/01-research-data.md → docs/_Research-Data-Management/01-rd.md b/...earch-Data-Management/01-research-data.md → docs/_Research-Data-Management/01-rd.md
diff --git a/docs/_Research-Data-Management/02-rdm.md b/docs/_Research-Data-Management/02-rdm.md
@@ -4,35 +4,39 @@ category: Research-Data-Management
 layout: default
 docs_css: markdown
 ---
-# Definition of Research Data Management (RDM)
-Research Data Management (RDM) is the process that includes all methods and procedures that aim to make research data usable over the long-term. RDM usually includes the following steps:
-* Planning
-* Data Collection
-* Data Processing & Analysis
-* Data Sharing & Publishing
-* Digital Preservation
-* Data Discovery & Reuse
-
-# Research data life cycle
-The RDM steps can be represented as a cycle called the research data life cycle: 
+## Definition of Research Data Management (RDM)
+Research Data Management (RDM) is a series of measures that need to be taken during a research project in order to (1) obtain high-quality data (whether produced or reused), (2) make data avaialbe and usable over the long-term and (3) make research findings reproducible beyond the research project {% cite RfII_RD bres_2022 voigt_2022 %}.
+
+## Research data life cycle
+The research data life cycle is a model that illustrates the steps of RDM and describes how data should ideally flow through a research project to ensure successful data curation and preservation {% cite NTU_LibGuides_RD_life_cycle bobrov_2021 %}. The research data life cycle can be illustrated as follow: 
 
 ![Research data life cycle](/nfdi4microbiota-knowledge-base/assets/img/research_data_life_cycle.png)
 
-# Benefits of RDM
-* **Researchers' own interests**
-    * Good Scientific Practice (GSP)
-    * Knowledge management / transfer
+## Benefits of RDM
+
+Benefits of RDM are numerous, some of them are listed below {% cite assmann_2022 bobrov_2021 bres_2022 engelhardt_2022 jacob_2022 lindstädt_2019 voigt_2022 %}:
+
+* **For researchers**
+    * Visibility
+    * Reputation (ensures research quality)
+    * Data ownership
+    * Eligibility for funding
+    * Saves time, money and resources
     * Preventing data loss
-    * Saving yourself time in the future 
-* **External interests**
-    * Research funders
-    * Publishers
-    * Researchers' own institution
 
-# Consequences of poor RDM
+* **Additional benefits**
+    * Helps keep track of the project
+    * Helps meet formal and legal requirements
+    * Enhances teamwork and collaborations
+    * Guaranteeing transparency, verifiability and reproducibility
+
+## Consequences of poor RDM
 Consequences of poor RDM include paper retraction (e.g. [González Amorós & de Puit](https://doi.org/10.1016/j.scijus.2015.04.005)).
 
-# Further resources
-* A [Brief Guide - Research Data Management](https://doi.org/10.5281/zenodo.4000989) for busy people
-* [bio.tools](https://bio.tools/)
-* [Coscine - The research data management platform](https://coscine.de/)
+## Further resources
+* Brief Guide - Research Data Management: [Training Expert Group 2020](https://doi.org/10.5281/zenodo.4000989)
+* Essential scientific and technical information about software tools, databases and services for bioinformatics and the life sciences: [bio.tools](https://bio.tools/)
+* Research data management platform: [Coscine](https://coscine.de/)
+
+## References
+{% bibliography --cited_in_order %}
diff --git a/docs/_Research-Data-Management/03-md.md b/docs/_Research-Data-Management/03-md.md
@@ -0,0 +1,21 @@
+---
+title: Metadata and Metadata Standards
+category: Research-Data-Management
+layout: default
+docs_css: markdown
+redirect_from: /Research-Data-Management
+empty: true
+hide: true
+---
+
+# Metadata
+
+# Metadata standards
+
+# Metadata management
+
+# Metadata quality control
+
+# Further resources
+
+# References
diff --git a/docs/_Research-Data-Management/03-fair.md → docs/_Research-Data-Management/04-fair.md b/docs/_Research-Data-Management/03-fair.md → docs/_Research-Data-Management/04-fair.md
@@ -45,27 +45,24 @@ Data interoperability is the ability of a dataset to work with other datasets or
 * (Meta)data are associated with detailed provenance.
 
 # Further resources
-
-* [Introducing the FAIR Principles for research software](https://doi.org/10.1038/s41597-022-01710-x)
+* Introducing the FAIR Principles for research software: [Barker *et al.* 2022](https://doi.org/10.1038/s41597-022-01710-x)
 
 ## Learning resources
-
-* [FAIR Cookbook](https://faircookbook.elixir-europe.org/content/home.html)
-* [FAIR in (biological) practice](https://carpentries-incubator.github.io/fair-bio-practice/index.html)
-* [FAIR sharing and access](https://mantra.ed.ac.uk/fairsharingandaccess/)
-* [D7.4 How to be FAIR with your data. A teaching and training handbook for higher education institutions](https://doi.org/10.5281/zenodo.6425568)
+* Course on FAIR in (biological) practice: [The Carpentries Incubator](https://carpentries-incubator.github.io/fair-bio-practice/)
+* How to be FAIR with your data. A teaching and training handbook for higher education institutions: [Engelhardt *et al.* 2022](https://doi.org/10.5281/zenodo.6674301)
+* Unit on the benefits and challenges associated with sharing research data openly: [The University of Edinburgh](https://mantra.ed.ac.uk/fairsharingandaccess/)
 
 ## How to make data FAIR?
-
-* [PARTHENOS Guidelines to FAIRify data management and make data reusable](https://doi.org/10.5281/zenodo.2668479)
-* [Preparing data for sharing: The FAIR Principles](https://www.slideshare.net/lshtm/preparing-data-for-sharing-the-fair-principles)
-* [Top 10 FAIR Data & Software Things](https://doi.org/10.5281/zenodo.3409968)
-
-## How to assess the FAIRness of your dataset(s)?
-
-* [How FAIR are your data?](https://doi.org/10.5281/zenodo.1065991)
-* Self-Assessment Tool to Improve the FAIRness of Your Dataset ([SATIFYD](https://satifyd.dans.knaw.nl/))
-* [The FAIR Data Maturity Model: An Approach to Harmonise FAIR Assessments](http://doi.org/10.5334/dsj-2020-041)
+* Guidelines to FAIRify data management and make data reusable: [PARTHENOS](https://doi.org/10.5281/zenodo.2668479)
+* Preparing data for sharing: [Knight 2015](https://www.slideshare.net/lshtm/preparing-data-for-sharing-the-fair-principles)
+* Recipes that help you to make and keep data FAIR: [FAIR Cookbook](https://faircookbook.elixir-europe.org/content/home.html)
+* Top 10 FAIR Data & Software Things: [Martinez *et al.* 2019](https://doi.org/10.5281/zenodo.3409968)
+
+## How to assess the FAIRness of your datasets?
+* FAIR data maturity model indicators: [Bahim *et al.* 2020](https://doi.org/10.5334/dsj-2020-041), Table 1
+* FAIR evaluator service: [Fraunhofer FIT](https://gitlab.fit.fraunhofer.de/abu.ibne.bayazid/fairevaluator)
+* How FAIR are your data? [Jones and Grootveld 2017](https://doi.org/10.5281/zenodo.5111307)
+* Self-Assessment Tool to Improve the FAIRness of Your Dataset ([SATIFYD](https://satifyd.dans.knaw.nl/)) 
 
 # References
 

diff --git a/docs/_Research-Data-Management/05-os.md b/docs/_Research-Data-Management/05-os.md
@@ -0,0 +1,9 @@
+---
+title: Open Science
+category: Research-Data-Management
+layout: default
+docs_css: markdown
+redirect_from: /Research-Data-Management
+empty: true
+hide: true
+---
diff --git a/docs/_Research-Data-Management/06-eln.md b/docs/_Research-Data-Management/06-eln.md
diff --git a/docs/_Research-Data-Management/06-gsp.md b/docs/_Research-Data-Management/06-gsp.md
@@ -0,0 +1,9 @@
+---
+title: Good Scientific Practice
+category: Research-Data-Management
+layout: default
+docs_css: markdown
+redirect_from: /Research-Data-Management
+empty: true
+hide: true
+---
diff --git a/docs/_Research-Data-Management/07-policies.md b/docs/_Research-Data-Management/07-policies.md
@@ -0,0 +1,9 @@
+---
+title: Policies and Guidelines on Managing Research Data
+category: Research-Data-Management
+layout: default
+docs_css: markdown
+redirect_from: /Research-Data-Management
+empty: true
+hide: true
+---
diff --git a/docs/_Research-Data-Management/08-data-organization.md b/docs/_Research-Data-Management/08-data-organization.md
diff --git a/docs/_Research-Data-Management/04-dmp.md → docs/_Research-Data-Management/08-dmp.md b/docs/_Research-Data-Management/04-dmp.md → docs/_Research-Data-Management/08-dmp.md
diff --git a/docs/_Research-Data-Management/09-preregistration.md b/docs/_Research-Data-Management/09-preregistration.md
@@ -0,0 +1,9 @@
+---
+title: Preregistration
+category: Research-Data-Management
+layout: default
+docs_css: markdown
+redirect_from: /Research-Data-Management
+empty: true
+hide: true
+---
diff --git a/docs/_Research-Data-Management/10-data-creation.md b/docs/_Research-Data-Management/10-data-creation.md
@@ -0,0 +1,9 @@
+---
+title: Data Creation
+category: Research-Data-Management
+layout: default
+docs_css: markdown
+redirect_from: /Research-Data-Management
+empty: true
+hide: true
+---
diff --git a/docs/_Research-Data-Management/11-informed-consent.md b/docs/_Research-Data-Management/11-informed-consent.md
@@ -0,0 +1,9 @@
+---
+title: Informed Consent
+category: Research-Data-Management
+layout: default
+docs_css: markdown
+redirect_from: /Research-Data-Management
+empty: true
+hide: true
+---
diff --git a/docs/_Research-Data-Management/12-eln.md b/docs/_Research-Data-Management/12-eln.md
@@ -0,0 +1,30 @@
+---
+title: Electronic Lab Notebooks (ELNs)
+category: Research-Data-Management
+layout: default
+docs_css: markdown
+---
+# Definition of Electronic Lab Notebooks (ELNs)
+An Electronic Lab Notebook (ELN) is a software meant for documenting experiments, resulting research data and processes. In its most basic form, an ELN replicates an interface similar to a page in a physical lab notebook. More advanced forms often offer features such as protocol templates, collaboration tools, support for electronic signatures and the ability to manage the lab inventory. Ultimately, ELNs will replace physical lab notebooks as part of the digital transformation {% cite kwok_2018 lindstädt_2019 lma_rdmwg vandendorpe_nd vieten_2023 %}.
+
+# Uses of lab notebooks
+
+## Physical lab notebooks
+As well as documenting your experiments, resulting research data and processes, a physical lab notebook is also intended to communicate your work (e.g. why experiments were initiated?). It also serves as a legal document to prove patents and defend your data against accusations of misconduct. Finally, it is your scientific legacy in the laboratory {% cite n4m_wc_elns_2023 %}.
+
+## Additional uses of ELNs
+ELNs offer features and functions that can pave the way for significant time savings and knowledge transfer in daily laboratory work. For example, ELNs support the annotation of raw data (e.g. with tags or metadata {% cite rathmann_2021 vandendorpe_nd %} without having to switch between different media formats. Annotating data makes it searchable, discoverable, traceable and reusable {% cite vandendorpe_nd %}. ELNs also bring data and their description closer together through embedded multimedia files (e.g. videos of experimental setups), links to shared resources (e.g. chemical databases or analysis software), links to other experiments, and direct links to (raw) data sets and analysis workflows {% cite rehwald_2022 %}. ELNs also allow for the versioning of experiment descriptions  {% cite rehwald_2022 %} and the structuring and visualisation of workflows and processes {% cite rathmann_2021 %}. ELNs also have the ability to manage inventories of samples, reagents and other supplies, and track equipment and equipment maintenance schedules {% cite lma_rdmwg %}. ELNs also provide for collaboration {% cite lma_rdmwg %} through a common medium  {% cite rehwald_2022 %}. Last but not least, ELNs provide for auditing {% cite lma_rdmwg %}, security and safety. Indeed, ELNs are fireproof, waterproof and cannot be lost, misplaced or stolen. ELNs can also be automatically backed up. They allow timestamping (RFC 3161 using DFN-PKI) and finalisation to prevent further changes  {% cite rehwald_2022 %}. They also support electronic signatures {% cite cozatl_2021 %} and require access management {% cite rehwald_2022 %}.
+
+## What ELNs should not be used for
+ELNs are not data publishing platforms and are not suitable for storing large files. Large files require special technology for secure storage (e.g. Object Store, Nextcloud), but can still be linked in the ELN {% cite rehwald_2022 %}.
+
+# Further resources
+* [ELN Finder - Demo](https://eln-finder.ulb.tu-darmstadt.de/home) -  Tool to help researchers searching and selecting a suitable ELN thanks to more than 40 filter criteria.
+* ELN Filter - Selection of ELNs that are suitable for the life sciences and that can be filtered out according to criteria ([English](https://www.publisso.de/fileadmin/user_upload/PUBLISSO/PUBLISSO_ELN-Filter_2021-06_english.xlsx), [German](https://www.publisso.de/fileadmin/user_upload/PUBLISSO/PUBLISSO_ELN-Filter_2020-12-01.xlsx)).
+* ELN Guide - ELNs in the context of research data management and good research practice – a guide for the life sciences ([English](https://dx.doi.org/10.4126/FRL01-006425772), [German](https://dx.doi.org/10.4126/FRL01-006422868)).
+* Free consultation sessions to get advice on the selection and introduction of an ELN (<[email protected]>).
+* [Video tutorial series](https://www.youtube.com/playlist?list=PLJYlS0FDTMq17tvYMeuI2Ct5XtykRFy0K) (only in German).
+* Working groups on ELNs (e.g. in [North Rhine-Westphalia](https://www.fdm.nrw/index.php/fdm-nrw/elb/), Germany).
+
+# References
+{% bibliography --cited_in_order %}
diff --git a/docs/_Research-Data-Management/07-data-qc.md → docs/_Research-Data-Management/13-data-qc.md b/docs/_Research-Data-Management/07-data-qc.md → docs/_Research-Data-Management/13-data-qc.md
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