From the outside, it can be a challenge to keep up with all the developments within the ever expanding universe of wiki*/*pedia. So it's good to be reminded now and then of all the structured data that has become available thanks to their efforts:
This looks pretty neat, especially since Wikidata currently has over 947 million triples in their data store. Since battles usually have a place and a date, it would be nice to import this data into a data design in nodegoat and visualise these battles through time and space (diachronic geospatiality ftw).[....]
You can now use nodegoat to query SPARQL endpoints like Wikidata, DBpedia, the Getty Vocabularies (AAT, ULAN, TGN), and the British Museum. Through the nodegoat graphic interface you query linked data resources and store their URIs within your dataset. This means that you can search all people in Wikidata using the string 'Rembrandt' and select the URI of your choice (e.g. 'https://www.wikidata.org/wiki/Q5598'). By doing so, you add external identifiers to your dataset and introduce a form of authority control in your data. This will help to disambiguate objects (like persons/artworks with similar names) and also enhances the interoperability of your dataset. Both these aspects make it easier to share and reuse datasets.
These two advantages (data disambiguation and data interoperability) are useful for researchers who work on small(-ish) but complex datasets. Researchers who feel that 'automated' research processes are unattainable for them as their data may be dispersed, heterogeneous, incomplete, or only available in an analogue format, are more likely to rely on something like the old fashioned card catalogue system in which all relevant objects and their varying attributes and relations are described. Luckily, we can also use digital tools to create and maintain card catalogues (databases). For a historian who is mapping the art market of a seventeenth century Dutch town, a database is a very powerful tool to store and analyse all objects (persons, artworks etc.) and the relations between these objects. Still, if no external identifiers are used, this dataset is nothing but a curated island (even if the data is published!).
Curation & Linked Data
The process we describe here aims to connect the craftsmanship of research in the humanities to the interconnected world of massive repositories, graph databases and authority files. Other useful purposes of linked data resources for the humanities have already been described extensively, like using aggregation queries to analyse large collections, thesaurus comparison/matching, or performing automated metadata reconciliation as described by the Free Your Metadata initiative.[....]