Welcome to Issue 17 of the RDM Weekly Newsletter!
The content of this newsletter is divided into 3 categories:
☑️ What’s New in RDM?
These are resources that have come out within the last year or so
☑️ Oldies but Goodies
These are resources that came out over a year ago but continue to be excellent ones to refer to as needed
☑️ Just for Fun
A data management meme or other funny data management content
What’s New in RDM?
Resources from the past year
1. Manage Successful Field Research
This virtual course from the World Bank is designed for professionals responsible for managing field research. It is intended to improve the skills and knowledge of field research practitioners, familiarizing them with best practices, critical issues in research implementation, recurring challenges, and cutting-edge technologies. The course is free and self-paced and a course certificate is available for those who complete all requirements before December 7th.
2. What is a Codebook?
As part of ICPSR’s “No Stupid Questions” Series, this short video provides a brief explanation of codebooks. ICPSR unpacks how codebooks are actually your data’s best guide, helping you decode variables, values, and everything in between. Turns out, reading a codebook might be the smartest first step you can take before diving into your data.
3. Data Management for Collaborations
Kristin Briney has written a lot about the fundamentals of data management, usually from the viewpoint of a single researcher trying to make their data a little easier to deal with. However, a lot of research is collaborative, so in this blog posts she details 7 data management practices that can benefit collaborative research.
4. Data Carpentry for Biologists
This course, from Ethan White, is an introduction to working with data for biologists including: data structure, data manipulation, visualization, basic programming, and databases. Designed to be used as a flipped university course and also for self-guided students. The current version has assignments using SQL, R, and Git, but previous iterations of the course (which can also be accessed on the site) have assignments for Python as well.
5. Information Gathering Toolkit
The Information Gathering Toolkit is a foundational guide developed by Omni to support organizations in collecting meaningful data through ethical, inclusive, and effective methods. It provides practical tools and best practices for engaging communities using three primary approaches: surveys, key informant interviews, and focus groups. The toolkit emphasizes that data collection is not just a technical task but a core component of evaluation and learning that helps organizations understand what’s working, where challenges exist, and how to improve.
6. CODATA Research Data Management Terminology
The goal of the CODATA Research Data Management Terminology is to gather the key terms needed for a common understanding of the research data management domain. The aim of the RDMT Working Group is to create a stable and sustainably-governed standard terminology of community-accepted terms and definitions for concepts relevant to research data management, and to keep this terminology relevant by maintaining it as a ‘living document’ that is updated regularly. Definitions should be clear and unambiguous, and where possible, fit with common usage. Definitions should be apposite across research data management activities of key stakeholders, including but not limited to those working in research, data management, digital curation and preservation, research management, research policy, open data advocacy, computer science, information management, research administration, library, scholarly publishing, digital archiving and research funding roles. Some terms may have more than one definition, in which case the relevant context is specified. The terminology is not an attempt to list every concept, tool and standard relevant to RDM; rather, it focuses on terms without easily found authoritative definitions elsewhere, and offers their definition in the context of contemporary RDM.
Oldies but Goodies
Older resources that are still helpful
1. Data Management for Psychological Science: A Crowdsourced Syllabus
Data management - including data preparation, cleaning, storage, and sharing - is critical to psychological research. Despite its importance, data management is rarely formally taught to students. This open-source syllabus, created during the Data Management Hackathon at SIPS 2021, provides detailed descriptions of data management topics, resources, and activities that can be used to create a course or workshop on data management. The syllabus is formatted as a series of modules that motivate the importance of high-quality data management and provide information on best practices at various stages.
2. Getting Started Creating Data Dictionaries: How to Create a Shareable Data Set
As researchers embrace open and transparent data sharing, they will need to provide information about their data that effectively helps others understand their data sets’ contents. Without proper documentation, data stored in online repositories will often be rendered unfindable and unreadable by other researchers and indexing search engines. Data dictionaries and codebooks provide a wealth of information about variables, data collection, and other important facets of a data set. This information, called metadata, provides key insights into how the data might be further used in research and facilitates search-engine indexing to reach a broader audience of interested parties. This tutorial from 2021 first explains terminology and standards relevant to data dictionaries and codebooks. Accompanying information on OSF presents a guided workflow of the entire process from source data (e.g., survey answers on Qualtrics) to an openly shared data set accompanied by a data dictionary or codebook that follows an agreed-upon standard. Finally, the authors discuss freely available Web applications to assist this process of ensuring that psychology data are findable, accessible, interoperable, and reusable.
3. Research Data Management Resources
Sherry Lake, Scholarly Repository Librarian at the University of Virginia Library, has collected a very thorough list of research data management resources, organized by topic in Zotero. The resources range from general data management, to curation tools, to policies and reproducibility. Definitely a site worth bookmarking!
4. Fallibility in Science: Responding to Errors in the Work of Oneself and Others
In this 2018 article commentary, Dorothy Bishop discusses how there are currently few incentives for honesty, and keeping quiet about an error found in one’s research will often seem the easiest option. In this article she provides several real life examples of how researchers have responded to errors found in their own work, and errors found in other people’s work. She then provides some general principles for responding to fallibility.
Just for Fun
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