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Research Data Service Training, Advice and Contacts: Training Sessions

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Doctoral students can book course places through the Doctoral College and staff can book on the course through Academic Staff Development. A full list of training sessions offered by the Library for researchers is available here.

The '4Ps' of research data management: Plan, Protect, Publish & Promote

This is an introductory course on research data management that is suitable for all researchers. The session will introduce you to a set of strategies and practices that will help you generate your datasets in the most helpful form, keep them secure and well organised, and archive, publish and promote them so that they can support your work and increase it's potential impact.  

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2019/2020 Academic Year Dates: 

  • Wednesday 9 October 2019; 10:15 - 11:45.
  • Friday 6 December 2019; 10:15 - 11:45.
  • Friday 13 March 2020; 10:15 - 11:45.
  • Friday 5 June 2020; 10:15 - 11:45.

Writing a data management plan for sensitive data

In this workshop you will write the first draft of your doctoral Data Management Plan using the University of Bath Doctoral DMP template. This course is suitable for researchers using sensitive data (human participant data). If you are using non-sensitive data or commercially sensitive data that is not collected from human participants then you should register on the 'non-sensitive data' version of this workshop. 

calendar icon2019/2020 Academic Year Dates:

  • Tuesday 10 September 2019; 10:15 - 12:05.
  • Friday 4 October 2019; 10:15 - 12:05. 
  • Friday 25 October 2019; 10:15 - 12:05.
  • Wednesday 11 December 2019; 10:15 - 12:05.
  • Monday 2 March 2020; 10:15 - 12:05.
  • Tuesday 28 April 2020; 10:15 - 12:05.
  • Thursday 18 June 2020; 10:15 - 12:05.

Introduction to using SQL for data manipulation

Databases are using for both storing and using your data effectively. Relational databases are made up of a number of tables of data that are linked using unique identifiers. For example, you might have study data in several tables that all contain a unique participant identifier. In this course you will learn about using relational databases for your research data and manipulating the data using SQL (Standard Query Language) on DB Browser for SQLLite.  This is a more efficient way to manage tables that you might usually manage in Access and using SQL means that you can keep track of changes you have made, and re-run those changes again if you need to. 

 

calendar icon2019/2020 Academic Year Dates: 

  • Friday 29 November 2019; 10:00 - 14:15 (lunch break included but lunch is not provided)
  • Monday 8 June 2020; 10:00 - 14:15 (lunch break included but lunch is not provided)

R and RStudio for data cleaning and visualisation

Description: The workshop will introduce you to some popular R functions and packages for data cleaning and visualisation. Using a sample dataset, we will show how to shape and manipulate your data for visualisation purposes. Topics will include how to wrangle your data for creating different types of plots (such as scatter plot, bar chart, box plot), labelling, and exporting plots.

Prerequisites: you must have attended the ‘Getting started with R: Descriptive Statistics’ workshop or be confident in importing data into R and writing a basic R script. You should also be familiar with commonly used plots for data visualisation and their application to different types of data.

 

calendar icon2019/2020 Academic Year Date: 

  • Wednesday 22 January 2020; 10:00 - 13:00

Archiving, publishing and sharing your research data: human participant data

In this workshop we will work through the preparation of human participant research data for publishing and sharing, talk about different ways of preserving and sharing your data including using a data archive or publishing your data as supplemental material, and think about ways in which you can maximise the potential impact of data sharing. If you are not using human participant data you should book onto the 'non-sensitive data' version of this workshop (see above). 

 

calendar icon2019/2020 Academic Year Dates: 

  • Monday 4 November 2019; 10:15 - 12:05
  • Monday 22 June 2020: 10:15 - 12:05

Writing a data management plan for non-sensitive data

In this workshop you will write the first draft of your doctoral Data Management Plan using the University of Bath Doctoral DMP template. This course is suitable for researchers using non-sensitive data but will cover the management of commercially sensitive data. If you are using or collecting data from human participants you should book onto the 'sensitive data' version of this course (see below)

calendar icon2019/2020 Academic Year Dates:

  • Monday 9 September 2019; 10:15 - 12:05.
  • Wednesday 2 October 2019; 10:15 - 12:05. 
  • Thursday 24 October 2019; 10:15 - 12:05.
  • Tuesday 10 December 2019; 10:15 - 12:05.
  • Friday 28 February 2020; 10:15 - 12:05.
  • Monday 27 April 2020; 10:15 - 12:05.
  • Wednesday 17 June 2020; 10:15 - 12:05.

Managing human participant data

This session will help you meet the particular legal and ethical challenges of working with data from human participants: obtaining informed consent, keeping data confidential, meeting legal, ethical and contractual requirements, and setting up restricted data sharing both during and after your project.

calendar iconcalendar icon2019/2020 Academic Year Dates: 

  • Monday 16 September 2019; 10:15 - 12:05
  • Thursday 16 January 2020; 10:15 - 12:05.
  • Wednesday 3 June 2020; 10:15 - 12:05.

Data organisation in spreadsheets: making your data work for you

Good data organisation is the foundation of any research project and many researchers have data in spreadsheets at some point during the research process.

We organise data in spreadsheets in the way that we as humans want to work with the data, but computers require that data be organised in particular ways. In order to use the tools that make computation more efficient, such as programming languages like R or Python, or to conduct statistical analyses in SPSS, R or using Stata, we need to structure our data the way that the computers need the data.

 

calendar icon2019/2020 Academic Year Dates: 

  • Tuesday 15 October 2019; 10:00 - 12:30
  • Monday 9 March 2020; 10:00 - 12:30

 

Introduction to R and RStudio for descriptive statistics

Description: This workshop will introduce you to the open-source R language and RStudio platform for descriptive statistical analysis. We will start with explaining the basics of importing data into R and writing an R script and then use the functionalities to undertake some basic descriptive statistics such as calculating means, medians, standard deviation, and apply hypothesis testing methods (t-test and chi-square).

Prerequisites: No prior programming knowledge or use of RStudio is required for this course, but you do need to be familiar with commonly used descriptive and summary statistics. The workshop aims to familiarize you with the application of R for basic statistics. However, it is not designed to teach the background, theory, or application of the statistics themselves.

calendar icon2019/2020 Academic Year Date: 

  • Wednesday 15 January 2020; 10:00 - 13:00

Archiving, publishing and sharing your research data: non-sensitive data

In this workshop we will work through the preparation of research data for publishing and sharing, talk about different ways of preserving and sharing your data including using a data archive or publishing your data as supplemental material, and think about ways in which you can maximise the potential impact of data sharing. We will discuss sharing of commercially sensitive data. However, if you are using human participant data then please book onto the 'human participant' version of this workshop. 

calendar icon2019/2020 Academic Year Dates: 

  • Monday 4 November 2019; 14:15 - 16:05
  • Monday 22 June 2020; 14:15 - 16:05

Bespoke Courses

If you are a member of staff and you would like to request a departmental seminar on any aspect of research data management, or course to be delivered to your department or research group, please contact us: research-data@bath.ac.uk.