Research data management training modules in Social Anthropology (Cambridge)

Key Info
Description - a brief synopsis, abstract or summary of what the learning resource is about: 

Looking after digital data is central to good research. We all know of horror stories of people losing or deleting their entire dissertation just weeks prior to a deadline. Even before this happens, good practice in looking after research data from the beginning to the end of a project makes work and life a lot less stressful. Defined in the widest sense, digital data includes all files created or manipulated on a computer (text, images, spreadsheets, databases, etc). With publishing and archiving of research increasingly being online, we all have a responsibility to ensure the long-term preservation of our research data, while at same time being aware of issues of sensitive data, intellectual property rights, open access, and freedom of information. The DataTrain teaching materials have been designed to familiarise post-graduate students in good practice in looking after their research data. A central tenet is the importance of thinking about this in conjunction with the projected outputs and publication of research projects. This teaching package is focussed on data management for Social Anthropology.
For each of three modules of the course, notes and powerpoint presentations are available as well a a survey model, a list of useful sofwrae, and a list os references and web-based resources as handouts.  Topics include the process of fieldwork, the kinds of data collected, and the methods for their collection.  Other topics relate to the organisation of data including basic information on file management, some practical demonstration of software tools and back-up techniques.  
Course materials are available in a downloadable zip file.

Authoring Person(s) Name: 
Irene Peano
Authoring Organization(s) Name: 
University of Cambridge
License - link to legal statement specifying the copyright status of the learning resource: 
Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported - CC BY-NC-SA 3.0
Access Cost: 
No fee
Citation - format of the preferred citation for the learning resource: 
Peano, I. (2013, July). Research data management training modules in Social Anthropology (Cambridge). Zenodo. http://doi.org/10.5281/zenodo.28523
Primary language(s) in which the learning resource was originally published or made available: 
English
More info about
Keywords - short phrases describing what the learning resource is about: 
Copyright of data
Data backup
Data curation
Data ethics
Data management
Data management planning
Data management planning tools
File naming
Social anthropology data
Social science data
Subject Discipline - subject domain(s) toward which the learning resource is targeted: 
Social and Behavioral Sciences
Published / Broadcast: 
Thursday, July 4, 2013
Created: 
Saturday, October 1, 2011
ID - identifier that provides the means to locate the learning resource or its citation: 
10.5281/zenodo.28523
Type - namespace prefix for the citable locator, if any: 
DOI
Publisher - organization credited with publishing or broadcasting the learning resource: 
University of Cambridge
Media Type - designation of the form in which the content of the learning resource is represented, e.g., moving image: 
Dataset - collection of information organized in logical record and block structures for use by a computer.
Contributor Organization(s): 
Name: 
JISC Data Train
Type: 
Funding and sponsorship
Contact Person(s): 
Irene Peano
Contact Organization(s): 
University of Cambridge
Educational Info
Purpose - primary educational reason for which the learning resource was created: 
Instruction - detailed information about aspects or processes related to data management or data skills.
Learning Resource Type - category of the learning resource from the point of view of a professional educator: 
Course - series of units and lessons used to teach the skills and knowledge required by its curriculum.
Target Audience - intended audience for which the learning resource was created: 
Early-career research scientist
Graduate student
Research faculty
Intended time to complete - approximate amount of time the average student will take to complete the learning resource: 
More than 1 hour (but less than 1 day)