Climbing on the shoulders of digital giants: from data to knowledge
On November 27, 2020, the first nodegoat Day in history took place at the Historical Institute of the University of Bern via Zoom. The University’s nodegoat projects provided insights into the implementation of their data models and their methods of data analysis, with a focus on data visualization (maps, networks, time series). Originally, the ‘nodegoat Day 2020’ was planned as a local conference of the University of Bern, but more and more an international audience showed interest: via Zoom and live stream on YouTube people from Switzerland, Italy, France, Germany, the Netherlands, Belgium and Luxembourg participated. The introduction to the conference, organized by Kaspar Gubler, University of Bern:
“In April this year (2020), the virtual research environment nodegoat was put into operation as a pilot project of the Historical Institute at the University of Bern within the framework of the university’s digitisation strategy. This was preceded by two workshops on nodegoat at the Walter Benjamin Kolleg here at the university. The great interest in these workshops made clear the need for digital tools. Supported by the Historical Institute, the pilot project nodegoat GO, a nodegoat installation for the entire faculty of humanities was launched. This means that all members of the faculty can now apply for a personal nodegoat research environment. Details can be found on the website of the Digital Humanities Department here in Bern. Since this month, nodegoat GO is officially supported by the faculty and the Digital Humanities departement within the framework of the university’s digitisation strategy, including a nodegoat support office starting next year. I would like to take this opportunity to thank all those who have supported the nodegoat GO project. Some short remarks on the virtual research environment. What does ‘environment’ actually mean here? Environment means in principle: one software for many things. What once had to be programmed laboriously with individual digital tools is now available to us in a virtual research environment, ready to use: Databases, front-ends for data input as well as analysis and visualisation functions, interfaces for data exchange and a website to present your results to the world. With this and with its sophisticated visualisation possibilities, nodegoat is also an important tool for visual communication.
The origins of nodegoat are in the Netherlands. Nodegoat was developed about 10 years ago at the University of Amsterdam by Pim van Bree (Master in Media Studies) and Geert Kessels (Master in Modern History) for specific research requirements and was transferred to a university spin-off called LAB1100. This spin-off now leads the development of the software, which is available in open source. In the course of time different functional modules were added to nodegoat, so that nodegoat today represents a sophisticated system for data analysis. These modules are, depending on the research needs, financed by different institutes worldwide and integrated into the open source version of the software, making it available to all users. So you finance, but you also profit when others do so.
In simple terms, nodegoat works similar to an Excell table. In contrast to Excell, however, nodegoat has extensive analysis functions with which the entered data can be immediately analysed, visualised and contextualised spatially and chronologically – all this without any programming knowledge. Data analysis and visualisation therefore take place within nodegoat. The data do not have to be exported to another visualisation software first. Nodegoat is not a data prison. All data can be exported at any time from nodegoat into another software, either as CSV file or via JSON interface.
In Nodegoat, users define their own data models without restrictions in terms of structure or depth. Each object can be classified with geographical and temporal attributes and evaluated accordingly. Users are therefore free to implement a completely individual data model or to create a data model that is adapted to existing vocabularies (e.g. Dublin Core or the reference model CIDOC). Nodegoat can therefore also generate and provide standard data and is at the same time a digital tool for networking data sets, thus improving the interoperability of research data in the field of humanities. From the point of view of data modelling, nodegoat follows an object-oriented approach. Following the actor-network theory, this means that persons, events, artefacts and sources are regarded as equivalent objects. Only the linking of objects through relationships forms and hierarchises a network.
But why should one work with data at all in the humanities? Why with a database?
The answer is simple: data can make visible factors, patterns and developments that would otherwise remain hidden in the sources. By changing the aggregate state of the data collected from the sources, we can, thanks to visualisations, for example, identify patterns that can lead to new insights. At the same time, the data visualisations help research to become more visible. The data show us the path that can lead us onto the shoulders of the digital giants. Once we reach the top, new horizons open up for us when data becomes information and knowledge.
The nodegoat projects that give us insights today come from very different fields. Nodegoat is an interdisciplinary tool which, as my personal experience shows, promotes the exchange of information across disciplinary boundaries. The projects that we will see today are at different stages of development. It is not about delivering a glossy brochure, but about giving as concrete an insight as possible into the project work with nodegoat as well as getting to know the possibilities and the basic functions of nodegoat, including data management, visualisations, networks and time series.
Temporally and thematically we will go on a great journey today. It begins in the 20th century, opens up national and transnational perspectives with the academic forced migration to Switzerland and war-torn societies in Southeastern Europe, leads us to festivals in contemporary theatre, then back to melodies and songs of the early modern period, into the European Middle Ages to church account books and academic knowledge spaces, and finally ends up at the cradle of mankind in Mesopotamia. Towards the end, more technical aspects will be presented, such as the data harmonisation of Linked Open Data and the developers of LAB1100 will conclude with an overview of nodegoat projects in other countries and insights into software development.”
Kaspar Gubler (Universität Bern, Historisches Institut): Kaspar Gubler used the REPAC project as an example to show how nodegoat works as a collaborative research platform for international projects that enter and analyze data web-based (and thus independent of location) in nodegoat and publish it on the net in a live environment. REPAC operates a pool of prosopographic data, which contains about 70’000 persons with about 400’000 records about biographical stations and networks. From this data pool the persons and biographical information are automatically assigned to the different projects in nodegoat based on certain criteria (Germanicum / Helvetcium / Bernense).
Stefanie Mahrer (Universität Bern, Historisches Institut): Forced Academic Migration (FAM) is a research project (funded by SNF-PRIMA) at the Department of History of the University of Bern on the history of forced academic migration in Switzerland during the Nazi regime and the post-war period. FAM-online provides insight into research results and enables visitors to access, filter and graphically display research data in the near future.
The aim is to collect biographical data of the academics who fled to Switzerland, data of the academic refugee assistance organizations and their helpers, data of the universities concerning forced migrants as well as relevant decrees and laws as completely as possible. The data is published continuously, taking into account legal regulations.
FAM-online links projects and refers to publications with similar topics and thus also sees itself as a platform for scientific research into the history of academic forced migration in the context of National Socialism. The project uses nodegoat to visualize escape routes on maps and to analyze networks of academics, escape helpers and involved organizations.
Franziska Zaugg / Mevlane Sejdiji (Universität Bern, Historisches Institut): “A longue durée of violence? War-disabled societies in Southeastern Europe” is a postdoctoral project (SNSF Ambizione), based on the concept of “long duration” developed by Fernand Braudel, which leads the historian’s focus away from the history of events towards more long-term social, cultural and economic structures. The project examines war-disabled societies in Southeastern Europe from the Balkan wars of 1912/1913 to the Balkan conflicts of the late 20th century. The project asks about possible connections between the violence experienced, the nature of memory and its relevance for future conflicts. The projects uses nodegoat to identify and visualize violence clusters on maps and within actor networks.
Alexandra Portmann, Anna Barmettler, Dominik Kilchmann (Universität Bern, Institut für Theaterwissenschaften): International theater festivals shape the contemporary theater landscape, although the variety of festival formats is difficult to categorize. The spectrum ranges from festivals that focus on a specific theme or author (e.g. Shakespeare), to festivals of the independent scene (e.g. Impulse Festival) and festivals such as the Manchester International Festival, which explicitly only shows premieres of international co-productions. These transnational co-productions of festivals with globally operating artists and independent production houses seem to increasingly shape the festival repertoire. This research project asks the question of how transnational working methods from the festival sector have a lasting effect on local theater systems. This SNSF Ambizione project uses nodegoat for visualizing the processes of festival productions on maps and within networks.
Elie Jolliet (Universität Bern, Institut für Musikwissenschaft): Studied music (organ, historical keyboard instruments, choral conducting and church music) in Bern (B.A.) and Lausanne (M.A.). Church musician in Köniz and concert activity as soloist, ensemble musician and choir director. Winner of the Migros Culture Percentage Instrumental Competition 2016. Member of the board of the International Association for Hymnology. Dissertation project: The Bernese Songbooks 1606 to 1853. Corpus analysis of the songs outside the Geneva Psalter. Elie Jolliet uses nodegoat, for the difficult analysis of songs, which he examines and visualizes separately for melodies and texts. More about Elie Jolliet as a professional musician on his website: https://www.eliejolliet.ch/
Corina Liebi (Universität Bern, Historisches Institut): Corina Liebi studies history with a focus on the Middle Ages and is an assistant at the Historical Institute in Bern. In her master’s thesis she deals with the finances of the Hochstift Bamberg and evaluates a chamber office account from 1478. She visualizes the entries of these books on maps, which gives her insights into the quantitative and spatial distribution of financial transactions. With a network analysis she also investigates connections between officials.
Sebastian Borkowski (Universität Bern, Institut für Archäologische Wissenschaften): Sebastian Borkowski, Master in Near Eastern Archaeology at the University of Bern, currently a PhD student at the Unité d’Études Mésopotamiennes of the University of Geneva and assistant in the Department of Ancient Oriental Philology in the RIMES project (The Rivers of Mesopotamia) presented the project that Dr. Susanne Ruthishauser is leading at the Department of Near Eastern Archaeology at the University of Bern. For the area in the south of present-day Iraq, the project will evaluate satellite image data combined with archaeological, written and geomorphological sources in order to reconstruct the position of rivers and channels of the Mesopotamian alluvial plain during different epochs. This project uses very many functions of nodegoat. Among others, Sebastian Borkowski evaluates about 10’000 written sources in nodegoat.
Kaspar Gubler (Universität Bern, Historisches Institut): SNFS SPARK Projekt ‘Dynamic Data Ingestion’ for server-side data harmonisation. The principle of data ingestion in the so-called DDI module of nodegoat is that nodegoat pulls together data centrally on the server from any data sources available via interface. The DDI Module has two important strengths. Firstly, this software module is integrated into a fixed structure. It is therefore not a script which is stored and executed somewhere on a server and, as so often, at some point is no longer updated. Secondly, the DDI module has a graphical interface (Linked Data Module) in which the database fields of the data source can be assigned to the database fields of the nodegoat database, the mapping of the data. A great benefit of the DDI module is therefore the linking of data sets, for example Linked Open Data.
Pim van Bree / Geert Kessels (The Hague, LAB1100): nodegoat on the globe. Overview of nodegoat projects running at other institutes and insights into new and planned features of nodegoat. Pim van Bree received his Master in New Media Studies at the University of Amsterdam. Geert Kessels his Master in History as a research master at the same University. Pim van Bree and Geert Kessels bring together skills in new media, history, humanities and software development. They work with universities, research institutes, museums to conceptualise and develop dynamic applications. Their most important application is certainly nodegoat. Pim van Bree and Geert Kessels have extensive project experience in the field of Digital Humanities, and are engaged worldwide as consultants for digital projects and workshops sharing. On Nodegoat Day, they presented an overview of nodegoat projects in other countries, gave insights into the principles of nodegoat as well as in latest software developments and answered users’ questions.
Fig. Overview on nodegoat projects running and a sample visualisation out of the project ‘Encyclopedia of Romantic Nationalism in Europe’ (https://ernie.uva.nl/)