model of chemical compound made of wool and knitting needles

Training

 

It's been another year of growth for our training programme. As well as increasing the size of our team of training fellows, we expanded the list of experts with whom we collaborate on courses in copyright, text analysis, GIS, 3D data, and digitisation. Delivering over 60 training sessions, we maintained a balance between in-person and online training to ensure that we offer courses that are accessible for everyone within our community. We also built on the success of our first summer school, delivering an in-person week-long intensive course in summer 2022 and then doubling in size in 2023 by adding a second stream of teaching. 

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Our Programme

 

This year we had the highest attendance to date with over 1000  staff and students upskilling with us this year and participating in over 60 courses on topics ranging from structured and unstructured data analysis, introduction to programming, GIS, to digital drawing and 3D data. We were able to achieve this by drawing on the expertise of our Training Fellows and colleagues from EDINA, Library, LLC, ECA, University Collections, and uCreate Studio. 

 

3D Data Pathway

New Training Pathways

We are committed to helping researchers orient themselves and learn new methods, that's why we develop our Training Pathways which lay out the steps involved in learning new skills and point towards relevant courses and resources. Recent additions cover the topics of Statistical Analysis and Text Analysis, as well as Managing Digitised Documents and Working with 3D Data. Another pathway on Geographical Data is currently under development. 

Sculpture Git

reusable materials

We support the reuse of training material and create open educational resources that can benefit others. In 2021 we created our GitHub organisational page for hosting all the material we produced during the year. We now have 42 repositories and 20 people have contributed to the growth of our project.

Training Breakdown: Our Core Topics

  • Digitised documents & text analysis: training on the processes of working with unstructured data from the extraction of information from digitised documents to advance language models.
  • Intro to programming: introductory classes that help attendees to familiarise themselves with the main programming languages.
  • Data wrangling & data visualisation: training on the practicalities of exploring datasets from cleaning messy data to producing effective visualisations.
  • Structured data analysis: from descriptive statistics to regression and null-hypothesis testing.
  • Geographical data: training on working with spatial data from introducing GIS to bridging data analysis and geographical data.
  • Digital drawing & 3D data: from technical drawing in AutoCAD to acquiring, processing and printing 3D data.
  • Good practices of digital research: exploring the practicalities of doing digital research from working with pre-prints to data ethics. 
Number of courses offered per training topic

We ran 64 courses this year, which can be grouped as follows: 12 focused on good practices of digital research, 3 on introduction to programming, 8 on data wrangling and data visualisation, 7 on digital drawing and 3D, 8 on geographical data, 14 on digitised documents and text analysis, and 12 on structured data analysis.

Number of registrations per training topic

So which topics were the most popular? Structured data analysis attracted more than 230 people. More than 200 people signed up for courses on good practice in digital research. Data wrangling and data visualisation attracted more than 170 people. Beginners' coding courses attracted 73, while over 191 people wanted to learn about working with textual documents. Finally, drawing and 3D data attracted 86 registrations, while 113 people signed up for courses on geographical data.

Summer Schools 2022 & 2023

Summer School Keynote

After the success of our online summer school in 2021, we ran our first  in-person summer schools.  With support from the Scottish Graduate School for Social Sciences and EFI we were able to offer the course for free to academic researchers and professionals from across Scotland and beyond. Participants benefitted from presentations and hands-on coding activities in R on the topics of OCR, text analysis, web scraping, sentiment analysis, descriptive statistics, null hypothesis testing, regression, mixed effects modelling, and data visualisation.  We ended each day with a BYOD (bring your own data) activity where attendees had the opportunity to work on their own data and get support and feedback from others. 

Graphic mashup - Calton Hill, Edinburgh-8002418 [Chris Close]

This year we expanded and developed the summer school to cater to a wider array of skill levels, we hosted two streams, one for researchers with no prior knowledge of coding and data analysis, and another designed to help researchers with coding experience understand how data and text analysis projects are performed in a research environment. With a packed schedule covering all things data analysis and a variety of socials events, attendees told us that the week was both invaluable and enjoyable.  

Probably the most interesting and useful training course I have been on in my career. An incredible opportunity.

Attendee, Summer School 2022

Our Training Fellows

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Lucy Havens

Lucy Havens is based in the School of Informatics where she is researching bias in cultural heritage metadata. Combining natural language processing and data visualization technologies, she seeks to identify and classify bias present in the language of cultural heritage catalogues. She conducts this research through case studies with cultural heritage collections, such as the Archives at the University of Edinburgh.

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Andrew Mclean

Andrew McLean is based in the School of History, Classics and Archaeology. Andrew is an archaeologist with research interests currently focused on the economy of the Roman Adriatic. His methodological approaches include GIS and statistical analysis, particularly expanding on traditional Least Cost Path (LCP) analysis by using circuit theory to model maritime movement. Through this, he is familiar with QGIS, R, Circuitscape, shell scripting and programming languages such as Julia and Python.

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Stefano Bordoni

Since 2017, Stefano has been a PhD candidate in Archaeology. His research explores the potential of medieval Umbria, in central Italy, under the lens of Architectural Archaeology. One of his major research aims is to turn building materials into quantitative data in order to identify patterns. In doing so, IT resources have been essential. In particular, he takes advantage of photogrammetric surveying, AutoCAD vector drawing, QGIS geoprocessing and RStudio data management and visualisation.

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James Besse

James Besse is a PhD student in Science, Technology and Innovation Studies. James’ research is on the implementation of e-ID systems, specifically looking at the EU Settlement Scheme. He uses text mining alongside social surveys and interviews to understand user experience with the EUSS. Broadly, James is interested in the social impacts of new technologies, and how digital methods can help to understand them. He is happy to provide assistance with R, statistics, web scraping, data visualization, and research design.

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Daniel Wheeldon

Daniel has recently completed his Ph.D. in musicology. He worked with museum and private collections in the UK, Germany, and USA  using traditional and digital technologies to extract information from original art objects and then to make working copies. While he was a Chester Dale fellow at the Metropolitan Museum of Art, NY, he participated in a project investigating the efficacy of photogrammetry in studying museum objects. He has training and over ten years of experience making and restoring musical instruments and has an ongoing interest in the intersection of traditional craft with emerging technologies.

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Fang Jackson-Yang

Fang Jackson-Yang is based in the School of Philosophy, Psychology, and Language Sciences. Fang researches how people communicate prominent information in transitive events (e.g., “Jerry kicked the oil lamp”). She uses eye-tracking techniques to investigate when and how listeners make predictions of the endpoints of such events (e.g., the lamp fell on the floor). She also uses laboratory and digital corpus data to investigate how speakers use various sentence structures and other linguistic means to describe such events in different settings and what factors influence their choices.

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Bonan Zhao

Bonan Zhao is a PhD student in cognitive psychology. She studies the twists and turns of how people generalize causal concepts to novel situations. In her research, she builds computational models to simulate human cognition and runs large online experiments to evaluate model predictions with people's judgments. She used to teach programming and web development to refugees in Amsterdam, and has been an enthusiastic advocate of open research practices.

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James Page

James is an archaeologist whose research focuses on the economy of Northern Italy in the Roman period. His work uses a combination of network modelling and statistical analyses to look at the dynamics behind inland trade and test the validity of prior modelling. He is familiar with QGIS, R, and OpenRefine. 

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Bhargavi Ganesh

Bhargavi is a PhD student at the University of Edinburgh, doing interdisciplinary research at the intersection of philosophy, computer science, and public policy. She is affiliated with the Center for Technomoral Futures and the UKRI Research Node on Trustworthy Autonomous Systems Governance and Regulation. She has worked at non-profit research organizations and government institutions, where she studied the impact of housing policies on marginalized groups. In her doctoral research, Bhargavi is developing frameworks to guide the governance and regulation of autonomous systems and decision-making algorithms in various fields including health, robotics, and finance. 

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Pedro Jacobetty

Pedro Jacobetty is a sociologist whose research interests intersect include technology, digital culture, knowledge production and circulation, media and communication. He is also interested in innovative ways of using digital methods for social sciences and art.

The patience and step-by-step guides from both of the instructors are what makes this course so different from other coding courses I have taken previously. For new coding learners, the greatest fear is to be in a class where everyone has prior knowledge and they keep getting ignored in class and never catch up. For this Python class, which I will highly recommend to my network, everyone's needs are catered to.

 

Participant, Training Programme 2022-23