General Data Management
Data organization in spreadsheets. Absolute must-read in case you have to use Excel in your research.
Abstract (Broman and Woo, 2017)
Spreadsheets are widely used software tools for data
entry, storage, analysis, and
visualization. Focusing on the data entry and
storage aspects, this paper offers practical
recommendations for organizing spreadsheet data to
reduce errors and ease later analyses. The basic
principles are: be consistent, write dates like
YYYY-MM-DD, don't leave any cells empty, put just
one thing in a cell, organize the data as a single
rectangle (with subjects as rows and variables as
columns, and with a single header row), create a
data dictionary, don't include calculations in the
raw data files, don't use font color or highlighting
as data, choose good names for things, make backups,
use data validation to avoid data entry errors, and
save the data in plain text file.
Rules of Thumb
- Avoid proprietary formats (prefer standardized ones)
- Avoid pseudo-standards, such as xlsx, docx, which you can recognize by the fact that there do not exist multiple implementations across different applications and platforms.
- Anything "plain text" that is not pure ASCII should be UTF-8 encoded.
- Simpler is better (as long as no info is lost).
- If your original data comes in a "low-quality" format (e.g. MP3, GIF, ...) just keep it like that.
Open Science, Open Data, Open Source:
21st century research skills for the life sciences. An excellent resource, not only for life sciences, that covers a lot of ground.
R for Data Science. Online. Really not "Science" but an excellent tutorial and reference for data handling in R.
Managing and Sharing Data; a best practice guide for researchers. UK Data Archive. Contains many practical hints.
Legal aspects for research data
This is a long overdue guide to the legal aspects of Open Science, which also covers research data specific questions in detail. Written in German, targeting the German legal situation, it will be applicable in large parts also for other jurisdictions.
- Rechtsfragen bei Open Science - landing page
- Download book as PDF
- Download book as EPUB
- Download book as MOBI
- Gedruckte Ausgabe:
ISBN 978-3-943423-67-9, 156 S., 1 Abb. farbig sowie farbige grafische Elemente, Softcover, 13,5 x 21 cm, 19.80 EUR.
Data Analysis
Research Software Engineering
Presentation: Managing Research Software Projects: How to set up, manage, and share your work in less time and with less pain. Greg Wilson, 2020.
A very concise overview that touches the most important points.
Online Book: Research Software Engineering with Python: Building software that makes research possible.
Targeting researchers, the book walks the reader through a worked example project and covers all required tools, techniques and best practices from the ground up. For example UNIX shell, Git, make, testing, continuous integration and python package creation are covered.
- Damien Irving, Kate Hertweck, Luke Johnston, Joel
Ostblom, Charlotte Wickham, and Greg Wilson
(2020).
Research Software Engineering with Python - GitHub repository
Data Management Plans
- Software: DMPRoadmap. The joint codebase from DMPTool (University of California Curation Center, UC3) and DMPonline (Digital Curation Centre, DCC). Probably the most established tool today. Open source / Ruby.
- Software: RDMO. A DMP web application by the Research Data Management Organiser (RDMO) project, which is funded by the DFG and supported and used by a large number of German institutions. This software is pretty new and still a bit rough around the edges but has a great number of advanced features. Open source / Python.
- Service: DMPTool Public service by UC3.
- Service: DMPonline Public service by DCC.
- Examples: Public plans: 100s of public DMPs from DMPTool.
Metadata Standards
Resources for RDM professionals
The 4TU. Centre for Research Data and in particular the Research Data Services of the TU Delft Library have long-term experience and impressing know-how.
Presentation
with interesting numbers by Alastair Dunning
(PDF version from the
original
Powerpoint file)
Science Europe represents the the national funding agencies of 28 European countries. "Research Data" is one of their top-priorities and their publications indicate where the community is moving towards. Of particular interest are the RDM-related evaluation criteria put forward by Science Europe.
The Practical Guide to Sustainable Research Data provides matrices that help to assess the maturity of research data management practices for
- funding organisations,
- research performing institutions, and
- research data infrastructures.
Other interesting publications can be found on their Research Data pages.
Book: Johnston, Lisa R. (2017). Curating Research Data Volume Two: A Handbook of Current Practice. Association of College & Research Libraries.
A very extensive checklist for people who establish an institutional research data repository.
Survey: TU Delft and EPFL have published an RDM-Survey among their researchers. n = 659 (both Institutions). Although it covers exclusively engineering + CS faculties, it is a good start for providing some sort of empirical status-quo.
It would be nice if other institutions used a compatible survey.
The Data Curation Network is a Sloan-funded project that aims to conceptualize and develop a “network of expertise” model for U.S. academic libraries to collectively provide data curation services to support digital research data deposit into repositories for open access and reuse.
Next to the down-to-earth conceptual model, they provide a wealth of recent empirical information, advice, checklists & workflows.
The first DCN report:
Data
Curation Network: A Cross-Institutional Staffing
Model for Curating Research Data
Download PDF (1.7 MB)
#activeDMPs is a pointer-webpage to the community that drives forward concepts and tools for active and machine-actionable data management plans.
The ELN-Wegweiser about Electronic Lab Notebooks (ELNs) (in German) gives practical advice for the establishment of ELNs in the life-sciences but should also provide a lot of help for similar projects in other felds.
ZB MED (Hrsg.) 2019. Elektronische Laborbücher im
Kontext von Forschungsdatenmanagement und guter
wissenschaftlicher Praxis - ein Wegweiser für die
Lebenswissenschaften, Köln.
https://doi.org/10.4126/FRL01-006415715
Download PDF (3.0 MB)