Archives today are publishing their cultural heritage data on the Web for exploration. However, for archive novices the traditional archival structures often are not intuitive and di cult to understand, and thus challenges data access and consumption. To tackle this problem, Linked Stage Graph was developed, a knowledge graph (KG) on the foundation of historical data about the Stuttgart State Theater. The data was made available by the Baden-Wurttemberg State Archives for the Coding da Vinci hackathon. This demo paper contributes the KG, a SPARQL endpoint, named entity extraction and linking to existing authoritative KGs as well as a dedicated user interface for exploration.
Digitizing cultural heritage has been a major task for galleries, libraries, archives
and museums (GLAM) for many years now. As a result, a number of Web based
platforms have been developed with the goal to enable researchers to access and
analyze the data scienti cally as well as to allow the general public to explore the
data. However, many archival web platforms present their content organized in
a way familiar only to archive experts but users who are unfamiliar with archival
practise to structure information often nd it challenging to access and explore
the provided content [
The Baden-Wurttemberg State Archives in Germany recognized this issue and opened up their data to the Coding da Vinci initiative, the rst German open cultural heritage hackathon. The initiative organizes several hack events a year, bringing together GLAM institutions as data providers and computer scientists, designers, digital humanists to develop creative and interesting applications on the foundation of these cultural heritage data. The Baden-Wurttemberg State Archives published a dataset about the Stuttgart State Theatres containing
XML (EAD-DDB)
XML2RDF
RDF EAD2RDF RDF
VIRTUOSO
EXPLORATION: LINKsElDodS.TfiAzG-kEaGrlRsAruPhHeV.dIeEWER
SPARQL ENDPOINT
VIKUS VIEWER
7.000 historical black and white photographs along with EAD-XML metadata
to be 'hacked' by the creatives. The photographs and metadata cover the
period from the 1890s to the 1940s. Especially in Germany, this time period was
marked by social and political upheavals in which democracy, freedom of speech
and creativity in particular were challenged. For this reason, the data provided
are still of enormous relevance today. For instance, the data reveal which theater
performances were allowed to be played in these di cult times and how certain
characters were displayed [
In this demo paper Linked Stage Graph6 is presented, a KG developed during the Coding da Vinci Sud 2019 hackathon7 on the foundation of the aforementioned archival data about the Stuttgart State Theaters. The goal of Linked Stage Graph is to enable researchers as well as the general public to access, analyze and explore the data in intuitive, interesting and useful ways. Along with the KG, the presented prototype demo contributes a publicly available SPARQL endpoint8 to enable sophisticated queries for expert users, the extraction and linking of named entities mentioned in the metadata to the Wikidata KG and the German Integrated Authority File (GND)9, a timeline interface for data exploration and lessons learned. As an additional feature, all 7.000 black and white photographs were colorized using open source tools based on machine learning (ML). All code of this demo is published and freely available on GitHub10. 2
This section presents the main contributions of the demo, Linked Stage Graph. 6 http://slod.fiz-karlsruhe.de/ 7 https://codingdavinci.de/events/sued/ 8 http://slod.fiz-karlsruhe.de/sparql 9 https://www.dnb.de/EN/Standardisierung/GND/gnd_node.html 10 https://github.com/ISE-FIZKarlsruhe/LinkedStageGraph
The project is based on an archival fonds of around 7.000 historical photographs
from the Stuttgart State Theaters. The photographs depict scenes and characters
from a wide range of productions from opera to childrens theater dating from the
1890s to the 1940s. In 2009, the Ludwigsburg State Archives took the fonds into
their custody. It consisted of 572 sleeves containing prints, photographic plates,
nitrate lms, photographic negatives and positive images. The archival
description captures (where possible) the title and author of the play, the directors,
choreographers and designers of each production. The provided dataset consists
of JPEGs and an EAD-XML le (cf. Fig.1 left). The Encoded Archival
Description11 (EAD) is a documentary XML standard for the description of archival
nding aids maintained by the Technical Subcommittee for Encoded Archival
Description of the Society of American Archivists together with the Library of
Congress. For users unfamiliar with an archives content structure it is di cult
interacting with EAD encoded nding aids, because often the archive's hierarchy
has to be navigated to extract meaningful information [
Fig. 1 presents the work ow. Before further processing the input XML le, some adaptions were necessary like adapting the XML name spaces, adding repository code and language code attributes to the EAD unitid XML-tags and replacing the lb tag with XML entity . The actual XML to RDF conversion was performed with two di erent approaches. First, the generic ReDeFer XML2RDF12 converter was used. The second approach applied the EAD2RDF13 XSLT stylesheet to transform the provided XML to RDF. As expected, both methods produced di erent results. While the EAD2RDF stylesheet result were incomplete (e.g. did not manage to transform the information about the image les), the XML2RDF converter produced a vast amount of blank nodes, which are di cult to query and to navigate, but, the results were more complete. Both methods created di erent IRIs to identify the actual subject of interest: the archival unit. While XML2RDF preferred the archival identi er14 the EAD2RDF transformation created the IRIs from the EAD unitid15. From a computer science 11 https://www.loc.gov/ead/ 12 http://rhizomik.net/html/redefer/ 13 http://data.archiveshub.ac.uk/ead2rdf/ 14 E.g. http://slod.fiz-karlsruhe.de/labw-2-2599382 15 E.g. from 'Abt. Staatsarchiv Ludwigsburg, E 18 III Nr 6' http://slod. fiz-karlsruhe.de/id/archivalresource/abt.staatsarchivludwigsburg, e18iiibu161 perspective the rst type of IRI was considered more stable, and that's why it was chosen as identi er. The results were merged through mapping the archival unit titles and the archival identi ers. Finally, the unwanted IRIs were removed. Many literals in the dataset contained unstructured information, i.e. the titles included also a play's author name and the abstracts contained further information about involved persons and roles. To extract this information a script was created. This also involved to de ne the vocabulary to model the persons types of contribution and roles. The aim was to reuse existing vocabularies as best as possible. Due to the clear de nition of the domain the ambiguity in the data was rather low. This enabled to map plays, person, and location names to Wikidata and GND very quickly. Therefore, a dictionary of potentially relevant resources form the vocabularies was extracted and an exact string matching was performed. Finally, all information was deployed to an instance of the Virtuoso triple store also providing a SPARQL endpoint. 2.3
A variety of visual means was implemented and utilized to explore the archive
data. To bring the historical black and white images to life, they were
automatically colorized using an open source tool based on ML [
In this paper Linked Stage Graph is presented, a KG based on historical data about the Stuttgart State Theater. Next to the KG, a SPARQL endpoint was released, named entities mentioned in the metadata were extracted and linked to existing KGs and a user interface was developed. The demo was created during 16 http://slod.fiz-karlsruhe.de/#Viewer 17 http://slod.fiz-karlsruhe.de/vikus/ the Coding da Vinci Sud hackathon and was awarded the prize for the "most useful" application. Even though the presented demo implements a use case on theater data only, it is generalizable to a broad range of archive domains since the EAD-XML format is widely used in archives. Future work will involve the improvement of the underlying ontology, a more exhaustive entity linking and further means of visual exploration beyond timelines.
Acknowledgement. We would like to thank Coding da Vinci for connecting cultural institutions with creatives to develop innovative applications.