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
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)