Wednesday 16 September
10:00-13:00 | 14-00-17:00
Pim van Bree. Researcher & Developer, LAB1100.
Geert Kessels. Researcher & Developer, LAB1100.
nodegoat (http://nodegoat.net/) is a web-based data management, network analysis and visualisation environment. nodegoat allows scholars to build datasets based on their own data model and offers relational modes of analysis with spatial and diachronic contextualisation. By combining these elements within one environment, scholars are able to instantly process, analyse and visualise complex datasets relationally, diachronically and spatially; trailblazing. nodegoat follows an objectoriented approach throughout its core functionalities. Borrowing from actornetwork theory this means that people, events, artefacts, and sources are treated as equal: objects, and hierarchy depends solely on the composition of the network: relations. This object-oriented approach advocates the self-identification of individual objects and maps the correlation of objects within the collective.
- No prior knowledge is required to attend this workshop.
- Participants are required to bring their own laptop to the workshop.
- Watch the nodegoat video tutorials:https://www.youtube.com/watch?v=eLDRNiJrRUc&list=PLXc6y7l7xxxIwd64QppyAA0G2ECsNGJCx
- Read the blog post ‘Enter, Curate & Explore Data’: http://nodegoat.net/blog.s/3/entercurateexploredata.
- [Optional, Read the nodegoat FAQ: http://historicalnetworkresearch.org/?topic=nodegoatfaq. ]
- Introduction of participants & discussion of research questions proposed by participants.
- Introduction to nodegoat (see:https://www.youtube.com/watch?v=eLDRNiJrRUc&list=PLXc6y7l7xxxIwd64QppyAA0G2ECsNGJCx).
- Discussion of two exemplary projects in nodegoat: Epistolary Networks; Networks of historical artifacts.
- Collectively: enter and visualise data in nodegoat.
- Discussion of first results.
- Discussion and inventorisation of research projects
- In groups: conceptualisation of a new data model for a specific research project.
- Collectively: add a new data model in nodegoat.
- In groups: add the conceptualised data model in nodegoat.
- Discussion of the results.
- Enter data in the new data model.
- Visualisation & discussion of the results.