Describing research products and their inter-relationships, providing access to meet the needs of their providers, users, and other stakeholders, in order to maintain or enhance their value and comply with ethical, FAIR and research integrity principles and policies.

Chemotion Electronic Laboratory Notebook

Chemotion is an Open Source Electronic Laboratory Notebook for chemical researchers. The Chemotion ELN is equipped with the basic functionalities necessary for the acquisition and processing of chemical data, in particular the work with molecular structures and calculations based on molecular properties. The ELN allows the search for molecules and reactions not only within the user’s data but also in conventional external sources as provided by SciFinder and PubChem. The ELN provides tools to share data in the Chemotion Data Repository. More information available at: Tremouilhac, P., Nguyen, A., Huang, Y. et al. Chemotion ELN: an Open Source electronic lab notebook for chemists in academia. J Cheminform 9, 54 (2017). https://doi.org/10.1186/s13321-017-0240-0

GeoDatabase (.gdb) Data Curation Primer

The Data Curation primers are documents used as a reference to curate research data within a specific discipline area or when using certain software or data types. They are developed during a series of workshops were attendees get input from a mentor of the Data Curator Network. The results are published in GitHub repositories. The GeoDatabase Data Curation Primer provides guidelines to manage and organize geographic data in geodatabases, to describe such data using geospatial metadata standards and which actions can be undertaken to preserve geospatial data in the long term.

Managing Qualitative Social Science Data An interactive online course

This interactive on-line course prepared by the Social Science Research Council and the Qualitative Data Repository contains four modules about different aspects of RDM of qualitative data in Social Sciences. Each module is composed by multiple lessons and can also function as a stand-alone resource to be completed individually. Most lessons include associated readings, resources, exercises, and activities.

DataWiz Knowledge Base

The knowledge base’s of the DataWiz is a complete RDM guideline for Psychology research to support or complement the use of the DataWiz data management tool. The content is structured in three sections: before, during and after data collection & analysis. The first section covers data management planning as well as the various legal and ethical aspects related to data management. The second section focuses on best practices and tips for handling and documenting data during research. Finally, the last section focuses on how to share and preserve data at the end of the project.

DataWiz Research Data Management system

DataWiz is an automated assistant for data management in Psychology, developed by the Leibniz Institute for Psychology Information. It is a web-based application that supports researchers in planning their data management before the project starts and in managing their research data during the project. It provides functions to cover the entire research data lifecycle: data preparation, documentation and archiving. It also provides a digital collaborative working environment for you and your team. With DataWiz researchers can reduce the time spent on RDM, increase the quality and ensure the long-term reusability of research data.

A quick guide for using Microsoft OneNote as an electronic laboratory notebook

This guideline helps researchers to use OneNote as an Electronic Laboratory Notebook (ELN). It provides tips to adapt OneNote to an ELN workflow with a focus on the biomedical sciences, which can be adjusted to other nonscientific ELNs. It covers several topics such as how to structure and label experiments, data acquisition and representation. It also provides relevant recommendations on how to approach data storage and security to comply with applicable legislation.

Persistent Identifiers ANDS guides

The Australian National Data Service has developed three guides about Persistent Identifiers for three different types of users. The basic guide focus on awareness level and explains the basics about PIDs. The working level guide expands on the basic, going into technical and policy details. The expert level guide is intended to provide in-depth understanding for research administrator and technical staff on how to set up a PID infrastructure.

Data repository finder

Utrecht University has created a simple decision-tree tool that helps researchers to choose a generic repository that best fits their needs. To do so, criteria such as restriction of access and cost of the repository are taken into account.

Publishing and sharing sensitive data: guidelines and decision tree

ANDS has published a comprehensive guide about best practice for the publication and sharing of research data (in the Australian context). The guide helps researchers with the publishing phase of senstitive data with a step-by-step approach which covers several phases of the research data lifecycle. These steps are summarized in a decision tree.

Making a research project understandable - Guide for data documentation

The University of Helsinki created, upon request, a compact guide for researchers to help with research data documentation. It first introduces the basic elements of documentation, and then provides practical instructions and strategies to proceed with documentation during the research project, but also for the publishing phase.

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