Research Data Service

Research data training and skills

A range of training programmes on research data and research data management (RDM) in the form of online courses, and classroom-based workshops and seminars to help you with managing your research data effectively and efficiently.

Online training

Research Data Management and Sharing - MOOC

This free five-week Coursera MOOC - created by the Universities of Edinburgh and North Carolina - is designed to reach learners across disciplines and continents.

Subjects covered in the 5-week course follow the stages of any research project. They are:

  • Understanding Research Data
  • Data Management Planning
  • Working with Data
  • Sharing Data
  • Archiving Data

The MOOC (The Massive Open Online Course) uses the Coursera on-demand format to provide short, video-based lessons and assessments across a five-week period, but learners can proceed at their own pace. Although no formal credit is assigned for the MOOC, Statements of Accomplishment will be available to any learner who completes a course for a small fee.

https://www.coursera.org/learn/data-management

Research Data MANTRA

MANTRA is a free, non-credit, self-paced course designed for postgraduate students and early career researchers which provides guidelines for good practice in research data management.

Find out how well you manage your data. Learn how to create a data management plan, securely store and share your data. MANTRA also includes practical exercises on using SPSS, NVivo, R, or ArcGIS for data handling.

Workshops and courses

In semester 1 of the 2020/21 academic year all courses will be delivered virtually using Collaborate virtual classroom.  Once you have booked onto a course you will be registered on the appropriate Collaborate session and should receive an email with details of how to join the session at least 2 days before it starts. If you don't receive this information please let us know using the Contact Us options above.

We will make a decision about the delivery of semester 2 courses later in the year.

Realising the Benefits of Good Research Data Management (RDS001)

Interactive Workshop - Attendees need to bring a smart phone, tablet, or laptop, preferably a laptop. No prior knowledge is required for this course.

This course has been split into two 90 minute sessions which will take part at the same time on consecutive days, if booking please ensure you can attend both days.

This in-depth course will provide researchers at all stages of their career with an accessible and practical guide to Research Data Management (RDM) and how it can benefit their research. It covers the entire research data life cycle from Data Management Planning through to Improving the Visibility and Impact of research data in order to increase a researcher’s profile. With practical hints and tips throughout this course is ideal for those just setting out on a career in research as well as anyone looking to update or refresh their skills.

Upon completion of this course, attendees will be able to:

  1. recognize the importance of RDM and Data Management Planning
  2. understand the difference between sensitive and non-sensitive data and how that will impact on their research and RDM
  3. apply basic RDM skills to their daily research practices
  4. determine the extent to which their research data is Findable, Accessible, Interoperable, and Reusable (FAIR)
Audience Date Time Booking link
Research Staff 29-30 September 2020 09:30 - 11:00 https://www.events.ed.ac.uk/index.cfm?event=book&scheduleID=42690
All Staff & PGR's 13-14 October 2020 10:30 - 12:00

Part 1 - https://www.events.ed.ac.uk/index.cfm?event=book&scheduleID=42496,

Part 2 - https://www.events.ed.ac.uk/index.cfm?event=book&scheduleID=42637

Research Staff 11-12 November 2020 13:30 - 15:00 https://www.events.ed.ac.uk/index.cfm?event=book&scheduleID=42794
PhD Students 01-02 December 2020 09:30 - 11:00 https://www.events.ed.ac.uk/index.cfm?event=book&scheduleID=42795

Writing a Data Management Plan for your Research (RDS002)

Interactive workshop - Attendees should bring a laptop or tablet to write their DMP on either using DMPonline, or the basic template the tutor will provide. It would also be helpful if you could bring your project outline to base the draft DMP on.

At the end of this practical workshop you will have produced a 1st draft Data Management Plan (DMP) for your research project. You will understand the basic components of good DMP.

Upon completion of this course, attendees will:

  1. understand the necessity/benefits of producing a DMP;
  2. know how to register for and use DMPonline;
  3. have drafted a basic DMP that they can complete after the course.
Audience Date Time Booking Link
Research Staff 8th September 2020 09:30-11:30 https://www.events.ed.ac.uk/index.cfm?event=book&scheduleID=42689
All Staff & PGR's 23rd September 2020 10:00 - 12:00 https://www.events.ed.ac.uk/index.cfm?event=book&scheduleID=42494

Working with Personal and Sensitive Data (RDS003)

Presentation - Before attending you should complete the mandatory online Data Protection Training https://www.ed.ac.uk/records-management/training/data-protection

Researchers today are pressured to share their research data and make it accessible to other researchers. But what if you have collected sensitive or confidential data?

For many researchers, the sensitivity of research data is one of the main barriers to data sharing. Fear of violating ethical or legal obligations, lack of knowledge about disclosure control and the time required to anonymise data to a suitable standard often prevent valuable datasets from seeing the light of day.

In this two-hour awareness raising course, we introduce how to collect, share, store, and protect the sensitive data you may encounter as part of your work.

Upon completion of this course, attendees will:

  1. understand the principles of good research data management;
  2. have knowledge of GDPR and data protection regulations, and what these mean for research and research data;
  3. be aware of relevant services and resources available to researchers at the university.
Audience Date Time Booking Link
Research Staff 28th October 2020 09:30 - 11:30 https://www.events.ed.ac.uk/index.cfm?event=book&scheduleID=42791
All Staff & PGR's 7th December 2020 10:30 - 12:30 https://www.events.ed.ac.uk/index.cfm?event=book&scheduleID=42498

Edinburgh DataVault: supporting users archiving their research data (RDS008)

How can my users and my School use the Edinburgh DataVault to save money and improve the longevity of research data?

How can I use the School Data Manager role or School Support Officer role to support my users, and how do I get that?

In what circumstances should I recommend to my users that they use Edinburgh DataVault?

To find out the answers to these questions, sign up for this course today! This course is designed for support staff working with researchers. 

Audience Date Time Booking link
Professional Service Staff / Research Support Staff 25/09/2020 14:00 - 16:00 https://www.events.ed.ac.uk/index.cfm?event=book&scheduleID=42495
The following courses are not being run remotely in semester 1 of 2020/21

If you need any support with any of these please contact the team using the Contact Us option above and we will provide support or training on a 1-2-1 or small group basis.

 

Data Cleaning with OpenRefine (RDS004)

Computer-based, hands on workshop - No prior experience required. Participants must bring a laptop with a Mac, Linux, or Windows operating system (not a tablet, Chromebook, etc.) that they have administrative privileges on.  Attendees are encouraged to bring their own data for a data workshop session at the end.

OpenRefine is a powerful tool for working with messy data: cleaning it; organizing it and transforming it from one format into another.  It is extremely useful for anyone who works regularly with any kind of tabular data.

At its simplest, OpenRefine helps you explore your data, identify and easily correct errors and globally reformat columns. For more advanced users it can be used to extend your data and link it with web services and external data. Most importantly, OpenRefine edits are reproducible and you can create a record of your data cleaning steps so you can automatically run them again on a new dataset.

This is an introductory course aimed at complete beginners covering the essential functionality of OpenRefine.

Upon completion of this course, attendees will:

  1. gain skills to use essential OpenRefine functionality;
  2. gain knowledge of advanced OpenRefine functions;
  3. be pointed towards reference resources for further learning.
School/ College Audience Date Time Venue Booking Link
Not running in semester 1          

Handling Data Using SPSS (RDS005)

Computer Lab-based, hands on workshop - No prior experience or preparation required

The aim of this half-day course is to show you how the facilities provided by SPSS can help with the management of your research data, demonstrating the benefits of using SPSS syntax-driven commands to keep a record of data preparation, management and analysis steps. This includes getting data out of SPSS, whether for long-term preservation or for further analysis in other software.

Upon completion of this course, attendees will:

  1. understand the importance of data management for research;
  2. gain hands-on experience undertaking common data management steps in SPSS;
  3. become confident in using syntax-driven commands to work with research data.
School/ College Audience Date Time Venue Booking Link
Not running in semester 1          

Assessing Disclosure Risk in Quantitative Data (RDS006)

Interactive Workshop / Computer-based. Due to the hands-on nature of this session, attendees MUST bring a laptop with R and R-Studio installed prior to attending the session (instructions for installation will be sent prior to the session).

Researchers face a number of technical, ethical and legal challenges in creating, analysing and managing research data, including pressure to increase transparency and conduct their research more openly. But for those who have collected or are re-using sensitive or confidential data, such challenges can be particularly taxing. Tools and services can help to alleviate some of the problems of using sensitive data in research.

Statistical Disclosure Control (SDC) is a methodology used to evaluate and minimise the risk of a statistical unit (e.g. an individual, household, etc) being identified within a dataset. This workshop will provide an introduction to SDC, covering the following:

• Types of Identifiers

• De-identification and Anonymisation

• Types of Disclosure

• SDC Approaches

• k-anonymity and l-diversity

The workshop introduces sdcMicro, a practical R package for measuring disclosure risk in numeric data through examining combinations of key variables. The hands-on session will demonstrate applying SDC methods to anonymize numeric data, while evaluating the balance between disclosure risk and data loss.

Upon completion of this course, attendees will:

  1. understand the principles of statistical disclosure control (SDC);
  2. be aware how SDC may be applied in practice (i.e. anonymising their own data);
  3. gain hands-on experience using the sdcMicro package to evaluate disclosure risk in a test dataset.
School/College Audience Date Time Venue Booking Link
Not running in semester 1          

Assessing Data Quality in Quantitative Data (RDS007)

Interactive Workshop / Computer-based. Due to the hands-on nature of this session, attendees MUST bring their own laptop to the session

Quality control of data is an integral part of all research and takes place at various stages, during data collection, data entry, and data checking. Discovering errors in quantitative data commonly involves a combination of manual checks (e.g. eye-balling the data) and more automated checks (e.g. running descriptive commands) but these can be time consuming and may not pick up all issues in the data.

This workshop introduces the key elements of data quality assessment, including file, data and metadata checks. The session introduces a purpose-built data quality assessment tool, QAMyData, which is used to detect some of the most common problems (e.g. missingness, labelling errors, outliers and direct identifiers) in quantitative data (SPSS, STATA, SAS & csv files).

Upon completion of this course, attendees will:

1. understand the principles of assessing data quality in quantitative data;

2. have hands-on experience using the QAMyData tool to check the quality of quantitative datasets;

3. be able to use QAMyData to check the quality of their own research data.

School/College Audience Date Time Venue Booking Link
Not running in semester 1          

Data Mindfulness: Making the Most of your Dissertation (RDS009)

This is an 8-part introductory online course created especially for undergraduate & PGT students.

The course is structured following the journey you will go through, from thinking of a research question, to conducting a literature search, to managing data (whichever form this takes), to writing up, and dealing with your dissertation data after submission.

Data Mindfulness: Making the most of your dissertation (YouTube playlist)

These videos are designed to work well alongside the 'Data Mindfulness: Making the most of your dissertation' handbook.

This course can also be delivered in a face-to-face format if desired, please contact us on data-support@ed.ac.uk to discuss this.

Introduction to Visualising Data in ArcGIS (RDS011)

Practical Workshop - Familiarity with spatial data useful, PC with ArcGIS 10.x installed required

The course provides an introduction to some of the basic functionality in ArcGIS and covers some simple methods of visualising data appropriately. The course will show you how to create a map in ArcGIS. We will cover spatially referencing data and plotting it on a basemap; making raw spatial information look like a map; making a choropleth map; creating a print quality map.

Upon completion of this course, attendees will have knowledge of spatial data and basic GIS functionality for visualising data

School/ College Audience Date Time Venue Booking Link
Not running in semester 1          

Introduction to Visualising Data in QGIS (RDS012)

Practical workshop - Familiarity with spatial data useful, PC/Mac with QGIS 3.4.x installed required

The course provides an introduction to some of the basic functionality in QGIS and covers some simple methods of visualising data appropriately. The course will show you how to create a map in QGIS. We will cover spatially referencing data and plotting it on a basemap; making raw spatial information look like a map; making a choropleth map; creating a print quality map.

Upon completion of this course, attendees will have knowledge of spatial data and basic GIS functionality for visualising data.

School/ College Audience Date Time Venue Booking Link
Not running in semester 1          

Contact

If you would like to have a tailored training session on any aspect of RDM within your discipline, school, institute or research group, please contact Kerry Miller.