08Apr2021

nodegoat Workshop series organised by the SNSF SPARK project "Dynamic Data Ingestion"

CORE Admin

LAB1100 has collaborated with Kaspar Gubler of the University of Bern in the SNFS SPARK project "Dynamic Data Ingestion".

As part of the project, nodegoat has been extended with new features that allow you to ingest data from external resources. You can use this to enrich your dataset with contextual data from sources like Wikidata, or load in publications via a library API or SPARQL endpoint. The new feature can be used by any nodegoat user. Because the Ingestion processes can be fully customised, they can be used to query any endpoint that publishes JSON data. This new feature allows you to use nodegoat as a graphical user interface to query, explore, and store Linked Open Data (LOD) from your own environment.

We will organise a series of four virtual workshops to share the results of the project and explore nodegoat's data ingestion capabilities. These workshops will take place on 28-04-2021, 05-05-2021, 12-05-2021, and 26-05-2021.

You will be able to learn more about these workshops here.

data analysis workshop

Latest Blog Posts

18Dec2024

nodegoat Workshops in Barcelona and Zaragoza

CORE Admin

Two opportunities to learn more about using nodegoat for your research projects! [....]

training

09Jul2024

nodegoat Workshop #100

CORE Admin

On Monday 8 July 2024 we gave our 100th nodegoat workshop! We reached this milestone when we ran the workshop 'Historical Network Analysis with nodegoat' during the Historical Network Research Conference at the University of Lausanne.

These workshops brought us to 54 cities, 24 countries, and 3 continents. See the full list on the nodegoat Workshop page.[....]

training

07Jun2024

New nodegoat Data Publication Module

CORE Admin

Publish your project with the new data publication module. nodegoat users can now select any project to generate a data publication that is web-accessible and downloadable as a ZIP-file. By generating a new publication a Project's data model and all of its data are published and archived. The publication remains accessible also when new publications are generated at a later stage. [....]

data publication