Teaching Database Skills for Historical Research with nodegoat – Hands on Workshop #dhiha8

When?: June 17, 2019, 14h00-17h45
Where? Institut historique allemand Paris
Registration required: event@dhi-paris.fr
Conference: Teaching History in the Digital Age – international perspectives #dhiha8

nodegoat is a web-based data management, network analysis, and visualisation environment. Since 2011, nodegoat is used in many collaborative and individual research projects (see: nodegoat.net/about and nodegoat.net/usecases). nodegoat is also used in various educational settings. In this workshop, we will explore three ways in which nodegoat can be used to teach database skills for historical research: exploring data, entering data, and modelling data. Workshop participants will receive a hands-on training on how to use these different approaches.

Exploring Data

When you start to teach database skills, it is important to allow students to get a good understanding of what a relational database is. In nodegoat this can be done by browsing through different types of historical data, following relationships, discussing temporal and spatial attributes of objects, filtering data, and visualising data. You can include more advanced approaches by running network analytical calculations or using deep filters and complex scopes.

Entering Data

Once your students have a good understanding of what a relational database is, you can start entering data into a nodegoat environment. On this level you can discuss questions related to ambiguous or incomplete sources, inferring data, and what to do with conflicting source material. On a more advanced level you can connect the decisions taken in this process with the resulting visualisations and network analytical calculations. You can also add multi-level relationships and complex geometrical shapes.

Modelling Data

Now that your students are comfortable with entering data into a preconfigured data model, you can start to teach them how to construct their own data model. Start by drawing out a conceptual data model and create a logical data model based on this. Once the data model is complete, it can be implemented in nodegoat. You can explore which data model works best for historical network analysis, and how levels of uncertainty can be addressed in a data model.

Participants should bring their own laptop with the latest version of either Chrome, Firefox, or Safari installed. No special previous knowledge or programming skills are required.

About the trainers:

LAB1100 is a research and development firm established in 2011 by Pim van Bree and Geert Kessels. LAB1100 brings together skills in new media, history, and software development. Working together with universities, research institutes, and museums, LAB1100 has built the digital research platform nodegoat and produces interactive data visualisations.


Registration required: event@dhi-paris.fr

Conference “Teaching History in the Digital Age – international perspectives #dhiha8”: https://dhdhi.hypotheses.org/5901


Teamaccount der Redaktion. Forschen – Vermitteln – Qualifizieren: Das DHI Paris ist ein zentraler Akteur international ausgerichteter historischer Forschung im Verbund der Max Weber Stiftung, Deutsche Geisteswissenschaftliche Institute im Ausland.

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