Recently, I have more extensively explored serious games for teaching and research communication in the humanities. In a workshop aimed primarily at religious studies scholars, I intended to address analogue board games as well as hybrid and exclusively digital games. And apart from games I myself had used or contributed to, I hoped to present other examples in different languages. Especially in the field of hybrid and digital humanities games, however, my search retrieved few results. This post summarises the vivid discussion with participants that followed my invited talk “Seriously, games?” in the #digitalDonnerstag workshop series hosted by Arbeitskreis Mittelbau und Nachwuchs der Deutschen Vereinigung für Religionswissenschaft e.V. (AKMN). Games for the humanities / religious studies – scarce or simply hard to find? weiterlesen
Ein Workshop zum Forschungsdatenmanagement ist derzeit zwar keine exotische Weiterbildung mehr, aber als fachspezifisches Angebot in der Geschichtswissenschaft weder üblich noch obligatorisch. Die Landschaft der Angebote zeigt trotzdem eine Vielzahl an engagierten Akteur:innen mit ausgewisesener Expertise. In Rahmen eines Expert:innenworkshops haben einige dieser Personen in einem gemeinsamen Erfahrungsaustausch Ideen und Impulse hinsichtlich der Formate, Themen und Zielgruppen entwickelt, nachvollzogen wie das Konzept erfolgreicher Angebote gestaltet ist und wie deren Zusammenführung weiterentwickelt werden könnte. Diese Ideen werden in diesem Beitrag ausgearbeitet und dokumentiert. Differenzieren, Bündeln, Verstetigen – Weiterbildungskonzepte zum Forschungsdatenmanagement in der Geschichtswissenschaft weiterlesen
Before digital humanists can do things with data, they first need to collect them, and web automation (or more specific methods of web scraping) can be a quick way of gathering a large amount of data. While web automation denotes every remotely controlled action performed on the web, web scraping, web mining or web harvesting are focussed on reading and processing information (found on websites). This blog post presents useful Python packages for these tasks and explains the advantages of working with browser profiles. Doing Digital History with Python IV: web automation weiterlesen
Since I started my project on the schism in the Catholic Church in the eighteenth-century Dutch Republic in the summer of 2019, I have been creating a dataset that comprises the information contained in lists of baptisms, burials, and marriages. This information enables me to trace the movement of Catholics to another, competing Catholic Church in the context of the schism. Consider, for example, Henricus Verbruggen and Maria Blomevelt. They baptised their first two children in a mission station that was part of the Church of Utrecht but had their third and last child baptised in the Roman Catholic Church (see Fig. 1).
As can be gleaned from the image above, I express this data in a graph database, which enables me to capture the various relationships between people and their roles at the events in which they participated. Moreover, a graph database allows for a great deal of flexibility. Recently I encountered a fascinating list of Catholics who had “converted” from the Church of Utrecht to the Roman Catholic Church. The list contains extremely valuable information and required me to include a new edge (=relationship), namely ‘converted_at’, and a new node (=event), conversion (see Fig. 2).
Often, these lists are relatively easy to work with, safe from abysmal handwriting or a paucity of information due to the lack of interest (or time) of the serving priest. However, a more frequent and persistent problem is the uncertainty about whether person A in event B was the same person in event C. Countless spelling variants and the common occurrence of particular names render it sometimes near impossible to tell whether we are dealing with the same person or not. In case of great uncertainty, I generally decided to refrain from making a decision. Sometimes, however, in the case of less uncertainty, I did treat these people as if they were actually one and the same. Luckily, it is possible to capture such uncertainty – I have done so in the Excel spreadsheet, which functions as a temporary staging database (from which I import the data into my graph database). It is not a problem to include this data in the graph database, but when visualizing the data, as done above, it becomes much trickier to account for this uncertainty. For example, one could capture the uncertainty as an attribute of an edge. However, only one attribute can be visualised, so either someone’s role at an event (e.g. ‘godparent_at’) can be shown or the attribute that denotes the uncertainty. Hence when dealing with images, the uncertainty in the data easily slips to the background, creating the misleading idea that all the data is of equal certainty.
When presenting this and related problems pertaining to data visualizations with several colleagues from the IEG DH Lab at the recent conference ‘Digital History: Konzepte, Methoden und Kritiken’ (see the video presentation by Monika Barget), a conference attendant, Moritz Feichtinger, if I remember correctly, asked the following intriguing question:
‘How do you consider it operationalisable to identify the unknown/unrecorded, the “unrepresented,” so to speak, in order to prevent statistical distortions or a problematic claim of “total” recording of the past in data? Does this correspond to the “humanistic approach”? I think that the globally and socially unequal (digital) representation of the past should also be included in analyses in the form of a clearly identified "blind spot” or “fuzziness”1
Virtually all the data from the early modern period (or, perhaps better phrased, data based on early modern sources) is incomplete and biased. This incompleteness can be circumstantial, through the accidental loss of sources, or deliberate, through targeted destruction. Biases can result from the mindset, preferences, and outlook of the people and institutions who created the sources. Phrased differently, many sources reflect the hierarchies and power relations of the early modern period, causing things to be underrepresented or portrayed in a negative light. For example, many Catholic priests only mentioned the mother’s name when they baptized an illegitimate child, possibly because the name of the father was unknown to them or because they sought to protect the father’s honour (and hence only recorded his first name in some instances).
Arguably, a one-size-fits-all approach to this vexing issue does not exist. Rather, one must assess whether the information derived from one body of source material can be enriched by information stemming from other (related) sources. This will not always be possible. Moreover, we need to reflect on the implications of our editorial interventions. For instance, I could try to find the names of the fathers of illegitimate children or, to give another example, infer that a couple had married (even if I cannot find any record thereof) because their children were not called illegitimate in the baptismal registers. Doing this, however, would greatly increase the uncertainty regarding some data in my dataset and would only augment the problems described earlier. Hence, my approach to this issue when working with this specific data would be to provide a lengthy introduction about the primary source material as well as my editorial policy and decisions. In addition, I aim to capture all the relevant information where possible (e.g., signifying when a child was deemed illegitimate) but refrain from inferring information and including it in the dataset. In the end, as the questioner already indicated, instead of glossing over gaps, inconsistencies, and biases, pointing at and signalling them is the best way to account for the fact that both the sources and the dataset created by me are the creation of fallible human beings and are a flawed and incomplete representation at best.
- The original question in German: „Wie hielten Sie es für operationalisierbar, Unbekanntes/Unerfassstes, gewissermaßen das ‚Nicht-repräsentierte‘ auszuweisen, etwa um statistische Verzerrungen zu verhindern oder auch ein problematischen Anspruch ‚totaler‘ Erfassung der Vergangenheit in Daten? Entspricht das dem ‚Humanistic approach‘? Ich denke, auch die global und sozial ungleiche (digitale) Repräsentiertheit von Vergangenheit müsste in Form einer deutlich ausgewiesenen ‚Blindstelle‘ oder ‚Unschärfe‘ in Analysen mit aufgenommen werden.“
In times of covid-19, virtual workshops can be quite hard for organizers as well as for participants. On the other hand, they offer a unique opportunity to try unconventional methods to improve the situation for both sides. Dr. Demival Vasques Filho, in cooperation with Anna Aschauer, grasped such an opportunity at the DARIAH-DE-workshop Network Analysis with Python for Beginners, when he decided to simultaneously code and explain the basis on network analysis. Furthermore, he managed to address academics from different research areas with the help of some well-known fictional characters.
Exploring connections: Digital workshop on Network Analysis with Python weiterlesen
In January, the DH Lab launched its series of (online) events “60 Minutes of DH” with a webinar on the automatic transcription tool eScriptorium.
The monthly events, planned as one-hour long afternoon sessions, are mainly intended for academic staff at the IEG and focus on joint discussions of tools, methods and literature from the field of Digital Humanities, as well as insights into the international project landscape. The goal is to encourage and support researchers when it comes to digital solutions supporting their history- and religion-related research. For this kick-off, however, the invitation was extended to a wider audience and was met with overwhelming interest by researchers from all over Europe.
by Sophia Renz and Vanessa Tissen
It all started with the seminar on network analysis in the summer semester of 2020. After learning about the basics of network theory and building networks in Python ourselves, the teachers Aline Deicke and Demival Vasques Filho asked us students to work in groups to develop a project combining our individual humanities backgrounds with network analysis. We are specialists in art history, which we wanted to include in the project. On top of that, the IEG DH Lab provided us with funds and support to further explore the application of network analysis in the field, e.g. whether art history datasets are available and to what extent they are usable or which art historical analyses or topics have already been done. The research project was kept relatively open, so we were able to look at the subject matter first. Tasks and questions developed during the following research. LinkedArt: exploring network analysis in art history weiterlesen
By Alessandro Grazi
My adventure in the world of the Digital Humanities, which started about a year ago in Innsbruck, continued last October and November with a Python course for beginners offered by the Codingschule Düsseldorf.
I did not know what to expect that Autumn Wednesday evening, when at 6 pm I connected to the Zoom link of the Python course I was going to attend. „Hello, World!“: a Python course for beginners with the Codingschule Düsseldorf weiterlesen
von Felix Bach und Cristian Secco
Die Transformation von digitalisierten Druckwerken von einer Bilddatei zur maschinenlesbaren XML-Datei ist für zahlreiche Methoden der Digital Humanities ein wichtiger Schritt in der Datenaufbereitung. In diesem Beitrag präsentieren wir einen Ansatz auf Basis eines Python-Skripts am Beispiel eines Werkes mit einer besonderen Binnenstruktur: Der Bomber’s Baedeker war ein „Reiseführer“, welcher von der Royal Air Force genutzt wurde, um während des 2. Weltkrieges deutsche Industriestandorte anzugreifen. Text zu XML mit Python auf Basis des „Bomber’s Baedeker“ weiterlesen
In April 2020, we started a series of case studies to introduce researchers working with historical sources to data analysis and data visualisation with Python. Today’s blog post covers topic modelling with the Python packages Gensim, spaCy, NLTK and SciKit learn.
Topic modelling is one of the central methods of Natural Language Processing (NLP), the „automatic manipulation of natural language, like speech and text, by software.“ (Jason Brownlee: What Is Natural Language Processing?, in: Deep Learning for Natural Language Processing, 22nd September 2017) In its most basic form, a „topic“ modelled by software displays word co-occurrences in texts, assuming that the frequency of co-occurrences defines certain areas of meaning. Doing Digital History with Python III: topic modelling with Gensim, spaCy, NTLK and SciKit learn weiterlesen
Als Ergänzung zur Einführung in die Erstellung von GeoJSON-Dateien beschäftigt sich der heutige Blogbeitrag mit der Visualisierung dieser Geodaten im Open Source Geoinformationssystem QGIS. Das Tutorial führt Schritt-für-Schritt durch die Erstellung einer einfachen Karte und gibt Hinweise auf weiterführende Lernressourcen. Geohumanities II: Gestaltung und Druck einfacher Karten in QGIS weiterlesen
Große Ziele alleine anzugehen ist ein oftmals unmögliches Unterfangen. Daher war es nicht nur eine, sondern gleich drei Universitäten, die sich der Aufgabe widmeten, den Zweck und die Möglichkeiten von Forschungsdatenmanagement an ein breites Publikum heranzutragen. Die Goethe-Universität Frankfurt am Main, die Johannes Gutenberg-Universität Mainz und die Technische Universität Darmstadt bilden den Verbund der Rhein-Main-Universitäten (RMU) und richteten als solche den ersten virtuellen Forschungsdatentag der RMU am 13. Oktober 2020 in Mainz aus. Hierbei ließen sich die Einladenden auf ein spannendes Experiment ein: Wie kann eine Veranstaltung dieses Formats digital umgesetzt werden?
Über den Umgang mit digitalen Forschungsdaten: Virtueller Forschungsdatentag der RMU 2020 weiterlesen
The IEG is involved in RESILIENCE, a research infrastructure project for Religious Studies and related disciplines, involving twelve partner institutions from ten European countries.
The acronym stands for “REligious Studies Infrastructure: tooLs, Experts, conNections and CEnters in Europe” and the goal is a pan-European research infrastructure (RI) which provides access to sources, research results, expertise and tools for researchers and individuals interested in religion-related topics.
Digital Humanities have been transforming research in Europe and RESILIENCE aims for driving forward the digital turn in Religious Studies by stimulating the applicating of innovative methodological approaches in this field. Digital data and services designed for the needs of transdisciplinary research related to religions will be made available within a single ecosystem accessible for researchers as well as non-academics worldwide. RESILIENCE – A Research Infrastructure for Religious Studies weiterlesen
This September, an online workshop on the publication of research data in the fields of History, which we offered for the first time, exceeded our expectations. The overwhelming interest, the engaging participants and the smooth flow of the event led us to a better understanding and (three) notable thoughts we would like to share. Calling for data publication workshops in historical research weiterlesen
COVID-19 has posed a challenge, to put it mildly, to how most of us go about living our lives. Either in our personal life or work life, most if not all of us had to make significant adaptions in order to deal with a world that still is in the grasp of pandemic. The experience I’d like to focus on in this blog post, is that of doing research at these unprecedented times. Fairly soon after COVID-19 broke out, it became clear that it would have huge implications for researchers and teachers. Due to travel bans and other restrictions, virtually all conferences were either canceled or were held online in some form or another. In a short time span, teachers across the world had to go to extraordinary lengths to move their courses online. As libraries and archives closed their doors and traveling to or from particular countries became severely restricted or even impossible, the access to primary and secondary sources, the very fuel of our research, was hampered to a large degree. Research in times of COVID weiterlesen