DTU skills trainings
The DTU skills trainings have been organised as part of the so-called “incubation phase” of the Doctoral Training Unit. The aim of this phase, which generally covers the first year of the research project, is to introduce students to various basis skills in the fields of digital humanities and digital history, including text mining, digital source criticism, database structures, programming, data visualisation, GIS analysis, algorithmic critique and tool criticism.
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DTU skills training on ‘Experimental Media Ethnography’ 4-6 July, 2018 (DHH-ST-09)
Prof. Dr. Andreas Fickers (University of Luxembourg), Prof. Dr. Kristen Haring (Standford University), Dr. Jessica Mesman (Maastricht University) and Dr. Stefan Krebs (University of Luxembourg)
(description will follow)
DTU skills training on ‘GIS-analysis, Mapping & Cartography’ 11 & 14 May, 2018 (DHH-ST-08)
Dr. Catherine Jones, Kerry Schiel and Kaarel Sikk (University of Luxembourg)
Today historians, geographers and social scientists and like have at their fingertips a myriad of digital resources (digital borne or digitised). They may be formal or informal datasets open for public use or held behind closed doors but common to all is the implicit or explicit geographical information that they contain. Thus, they are ripe for use in research. The geographic information within has the potential to enrich our knowledge about the relationship between people, places and time, bringing us closer to more meaningful and nuanced representations of place and locale. In this proposed introduction to Geographical information Science (GIS) we will critically discuss the emergence of the spatial methods within the humanities drawing upon a range of Geohumanities projects to illustrate our conceptual framework for spatial modelling and build practical expertise with an Open Source GIS known as QGIS working with a historical dataset.
DTU skills training on ‘Algorithmic Critique’ 18 April, 2018 (DHH-ST-07)
Prof. Dr. Pascal Bouvry, Prof. Dr. Frank Hofmann, Dr. Martin Rosalie (University of Luxembourg)
The objective of this skills trainings is to make students familiar with ‘Algorithmic Critique’ as an important skill in Digital History and Humanities research. Specifically, the training provides an introduction to optimisation, search and decision problem modelling. Various solving techniques based on exact methods (A*, B&B, LP), approximated ones (heuristics, meta-heuristics, problem relaxation) and hybrids will be demonstrated and experimented with. Students are also taught how to validate the proposed solution by having a scientific approach. The practical session involves meta-heuristics and evolutionary computation with the implementation of an Ant Colony Optimization algorithm. An application of Artificial Ants for Natural Language Processing will be presented as well. The training is open to PhD candidates (maximum 20 participants) with an interest in algorithmic critique, data optimisation and search modelling.
DTU skills training on ‘Tool Criticism’ 15 March, 2018 (DHH-ST-06)
Dr. Vincent Koenig and Dr. Carine Lallemand (University of Luxembourg)
The ever-growing trend for digital tools is confronting PhD candidates with new challenges when it comes to designing or evaluating technologies and underlying services. The “tool criticism” training offers a critical and reflexive approach to digital tools, to the interaction with those tools and to the experiences they provide. Methods from the field of Human-Computer-Interaction (HCI) allow for tools and experiences responding to user needs rather than having users adapt and fall for the technology supremacy fallacy. This one-day course is part of a series of courses on user experience design and evaluation methods (“An introduction to user experience design and evaluation methods”). During this precise session, the focus will be on evaluation of tools against intended usability and experiences, based on empirical data, so as to support the process of design & redesign or of choosing among existing tools. While the students joining this one-day course will learn about evaluation aspects as described above, the user research and ideation aspects are dealt with in other sessions that are only covered in the larger series of courses.
DTU skills training on ‘Data Visualization’ 2 & 5 February, 2018 (DHH-ST-05)
Dr. Marten During (University of Luxembourg), Dr. Robin De Croon and Francisco Gutiérrez Hernández (KU Leuven)
This skills training provides an introduction to data visualisation as an important skill in digital humanities and historical research, analysis and presentation. The first training day focuses specifically on network visualisation and the use of Palladio as a DH tool in social network analysis. Instructor Dr. Marten Düring will also talk about the Histograph, a graph-based exploration and crowd-based indexation for multimedia collections, as a ‘showcase’. This training day investigates how texts can be used for constructing networks, how to visualise social networks and relations, and which computational techniques can be used for that in historical analysis. The second day of the skills training provides an introduction in data visualisation from a computer science and human-computer interaction (HCI) perspective. Instructors Dr. Robin De Croon and Francisco Gutiérrez Hernández give a hands-on introduction to Tableau as a DH tool for data visualisation and analysis. They also explore how data visualisation links to various perception and design principles and provide insights into visualisation and interaction techniques.
DTU skills training on ‘Introduction to Programming’ 4-8 December, 2017 (DHH-ST-04)
Dr. Folgert Karsdorp (Meertens Institute, Amsterdam)
This workshop provides an introduction to computational text analysis with Python for scholars in the Humanities. Computational text analysis has gained popularity across different fields in the humanities, with successful applications such as computational authorship attribution, personality detection, linguistic profiling, and topic modeling. The goal of the workshop is to introduce common technologies used in computational text analysis and to make participants familiar with the dominant programming language taught at universities, Python and its ecosystem.
DTU skills training on ‘Database Structures’ 16-17 November, 2017 (DHH-ST-03)
Prof. Dr. Martin Theobald (University of Luxembourg), Dr. Robert C. Kahlert (KU Leuven)
What are (big) data? What are databases? What are database structures? What can we do with them? This skills training provides an introduction to different database systems and applications, and how to work with them in historical research. The training day offers an introduction to hand-curated data, and the various ways it can be stored: blog entries, text files, presentations, office documents, Wikis, note-taking software, spreadsheets, SQL databases. We will look at what data is, how to gather and encode it, how to link it back to its point of origin, how to normalize it, and what to do if you need more than the software supports. The training’s second day approaches the topic of database structures from the perspective of big data. It provides an overview of current trends in distributed data management. We will have a look at how different data forms (incl. text, XML and JSON) can be handled by open-source libraries and directly be processed in a distributed environment using the Apache Spark platform.
DTU skills training on ‘Digital Source Criticism’ 30-31 October, 2017 (DHH-ST-02)
Prof. Dr. Andreas Fickers, Dr. Stefania Scagliola, Andy O’Dwyer
Historians of the 21st century need to be aware of how the transformation from analogue to digital affects the epistemological value and appearance of a source. The traditional way of questioning the authenticity of a document by finding out who created it, at which time, for which purpose and in which context, has been challenged now that the prefix ‘digital’ has been added to ‘source criticism’. This skills training explores the meanings and practices of ‘Digital Source Criticism’, the critical appraisal of digital sources of knowledge that can be retrieved from the web. It poses the question how the digital turn requires a further reconsideration of the historian’s craft.
DTU skills training on ‘Text Mining’ 17-18 July, 2017 (DHH-ST-01)
Prof. Dr. Christoph Schommer, Prof. Dr. Peter Gilles, Dr. Christoph Purschke (University of Luxembourg)
Modern computer machines and algorithmic intelligence have made it possible that large amounts of texts can be collected, retrieved, and analyzed from heterogenous text sources. This offers a high potential and many challenges, in particular for the application fields like History. But the working with Big Texts raises also questions, for example, how masses of texts can efficiently be managed, processed, and retrieved. Besides, which algorithms can and should be used to extract valuable information? Is the gained information reliable and durable? This skills training on ‘text mining’ tries to give answers to these questions. The training is dedicated for PhD candidates with an interest in Text Mining. It is tangent to the field of Distant reading, which focuses the “understanding of literature, not by studying particular texts, but by aggregating and analyzing massive amounts of data”, as introduced by Moretti (2013).