RDM & Top 5 Preventable Research Disasters



Next, on this section of the website you will find a carefully curated selection of support and guidance according to each stage of the research and rdm cycle.

What is Research Data Management (RDM)?

In short, RDM is taking good care of your data during and after your research. The importance of good RDM becomes clear when you look at the TOP 5 research disasters that could have been easily be prevented by good RDM:

  1. Legal problems
  2. Money issues
  3. Journals refusing to publish your article
  4. Data loss
  5. Wasting a lot of time & being frustrated

The following info slide deck illustrates how poor RDM can lead to those kind of research disasters and, as a result, how you can prevent such research disasters regarding your own research projects: <info slide deck = under construction>

One aspect of good RDM is be sure that your data will be as "FAIR" as possible. During your research you should already take measures to make your data FAIR. In additon, RDM is also about managing your data during your research project, like proper folder naming and  management of acces rights for these folders (view only/ edit rights), making use of well-known commenly used standards (device settings, annotations, software codes, etc.), well regulated version control of files during your research, and for example documenting your metadata, sharing.

Similar to a research project, RDM also can be visualized as a continuous life-cycle.

research-data-lifecycle

Next, on this page you will find the following RDM specific content:

        1. short and sweet rdm bits
        2. rdm knowledge clips as videos
        3. managing your research project from start to finish


SHORT and SWEET

What is Research Data Management (RDM)?

In short, RDM is taking good care of your data during and after your research. The importance of good RDM becomes clear when you look at the the TOP 5 research disasters that could have been easily be prevented by good RDM:

  1. Legal problems
  2. Money issues
  3. Journals refusing to publish your article
  4. Data loss
  5. Wasting a lot of time & being frustrated

The following info slide deck illustrates how poor RDM can lead to those kind of research disasters and, as a result, how you can prevent such research disasters regarding your own research projects: <info slide deck = under construction>

One aspect of good RDM is be sure that your data will be as "FAIR" as possible. During your research you should already take measures to make your data FAIR. In additon, RDM is also about managing your data during your research project, like proper folder naming and  management of acces rights for these folders (view only/ edit rights), making use of well-known commenly used standards (device settings, annotations, software codes, etc.), well regulated version control of files during your research, and for example documenting your metadata, sharing.

Similar to a research project, RDM also can be visualized as a continuous life-cycle.

On this section of the website you will find a carefully curated selection of support and guidance according to each stage.

kick-starting your research data management

RDM contributes to Open Science, FAIR data, and reproducible data and software. In the following tabs you will find quick help on how to improve your data management, research data exposure, as well as some pointers on legal matters and FAIR data.

How to your data files

1. Create a coherent folder and file system

Step 1: Create a coherent folder and file system

Step 2: Establish version control

Step 3: Write readme files

  1. Creating a logical folder structure with a few top-level folders to divide between research and administrative content, and establishing a number of sub-folders at the beginning of a new project helps with managing, sharing, and saving files over time.

  2. Adding versioning numbers on higher level folders, and all files helps keeping the overview and statuses of their contents independent from time-stamps in the file-directories.

  3. Finally, adding simple text-files with a minimum set of information (aka readme file) about all subordinate folders and files for each top-level folder will increase the comprehensibility for you and your colleagues in the course of the project and beyond.
Example folder structure with naming conventions

click to enlarge

Image reference: https://www.wur.nl/en/Value-Creation-Cooperation/WDCC/Data-Management-WDCC/Doing/Organising-files-and-folders.htm


How to

Sign up for your freely available unique authors ID. In addition to most of the publishers these days requiring this ID-type already, the ORCID-ID helps you being individually identified as creator and will list all outputs that is related to this ID.

Publishing other scientific material such as poster, presentation slides, graphics, software, and videos will also count as publication and will accumulate in your publishing record.

Read more about the ORCID-ID and register: ORCID.org

Image reference: https://orcid.org/




RESEARCH DATA MANAGEMENT KNOWLEDGE CLIPS

a few short introductory videos

In the five tabs below you can watch a knowledge clip in video format that will quickly introduce you to the main topics per category:

      1. data management planning (DMP)
      2. budgeting for research data management (BUDGET)
      3. research data management essentials (RDM)
      4. scientific exposure and impact (EXPOSURE)
      5. GDPR and informed consent (GDPR).



Your research project from start to Finish

the ins and outs of research data management and data stewardship alongside your research project




Consultancy service

For expertise advice on your research and the possibilities UBEC offers to get the most out of your data: request a meeting by emailing us. Experimental design, data management, bioinformatics analysis, results and follow-up experiments are discussed. The facility manager ensures that experts from participating organizations are present during this meeting.

You can request a meeting at bec@umcutrecht.nl.

 
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