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‚The Data Arbor‘: Open Citizen Science with Linked Open Storytelling in Unlocking the ‚Garden Arbor‘.

Starting in 1853, ‚Die Gartenlaube‘ from Leipzig successfully turned an illustrated magazine into an early mass medium with serial storytelling… a German-language family newspaper in the 19th century. Digitized, transcribed and made openly accessible, the project ‚Die Datenlaube‘ uses Linked Open Data today for storytelling with metadata in project communication.

Note: Note: This is the English translation (automatically with DeepL). The German original written by Jens Bemme (SLUB Dresden) can be found here.

Starting in 1853, ‚Die Gartenlaube‚ from Leipzig successfully turned an illustrated magazine into an early mass medium with serial storytelling… a German-language family newspaper in the 19th century. Digitized, transcribed and made openly accessible, the project ‚Die Datenlaube‘ uses Linked Open Data today for storytelling with metadata in project communication.

Hyperlinks make up the World Wide Web. Digitized newspaper pages – their texts and images – and the descriptive metadata are the resources for linking indexing work and linking #WissKomm (German for SciComm): digital and social-media (science) communication from the research and development process, linking standards data and other relevant media and cultural datasets. With Linked Open Storytelling (LOST) we bring public project communication to its own term: linking science communication with open cultural (meta)data.

Die Datenlaube

Open Citizen Science with open cultural data

The ‚Datenlaube‚ is a Citizen Science project – run largely by volunteers in Dresden and Vienna. „The project is based on citizen science research, crowdsourcing, and methods consulting in research-oriented, partly informal, citizen science communities and loose collaborations; the boundaries are often fluid,“ we wrote in the first interim report in early 2021. We are opening up Die Gartenlaube ‚open‘. In essence, this is creating an open catalog of hobbyist transcribed Wikisource texts using Wikidata. Travelogues, health and household tips, reviews, reports from the Reichstag, poetry and novels, portraits of places, plants, and people, obituaries – richly illustrated, with sequels, and sometimes told in long-running series of articles with large illustrations – are the foundations for our growing mountain of bibliographic metadata, which is open, structured, and therefore machine-readable, and has been continuously created since 2019 for each newly corrected contribution from ‚Die Gartenlaube‘.

These lines are now a sketch of our work with public project communication in mind. On the left are the connecting brackets between the manual work in Wikisource, Wikidata and Commons and analytical consideration of the inventory: Tweets with thumbnails from the metadata of Wikidata items and Wikisource pages, hashtags, guest posts in weblogs and Pecha Kucha evenings, university seminars and conversations about metadata in volunteering, about ideas, in texts about the potentials of Wikimedia portals. We report linked open social-media from project results and projects or share with links in discussions examples and methods we use to link Wikisource, Wikidata, Wikimedia Commons and Wikiversity (Twitter hashtags: #DieGartenlaube, #DieDatenlaube et al.).

With about 19,000 articles from the volumes from 1853 to 1899, the Gartenlaube is large enough for new research on the basis of our open data, we assume: as a total stock, for the consideration of year slices and decades or individual author:s, subject areas and conjunctions. The arbor offers secondary sources and it is itself, in its own right, a research subject. ‚Die Datenlaube‘ raises primarily methodological questions for us as a now three-person project team: How do we design the data schema for Wikisource texts– and for the structured image data in Wikimedia Commons (the central media repository for Wikisource)? By third party: „Are you indexing the illustrated book with a defined vocabulary?“ (Answer: No.) Or: Couldn’t we wait with all this (e.g. OCR corrections) until text recognition works even better in ten years?

You could. Instead, since 2019, we assign content keywords in Wikidata items of all garden arbor articles and additional statements to enrich the formal metadata with content and make it queryable. Why? Because we can.

This results in lists, maps and diagrams. The so-called #TreeSliceDiagram visualizes the frequency of assigned keywords with the rank ‚Normal‘, for example.

These and other transcriptions have been created in Wikisource on a voluntary basis by the relatively small German-speaking Wikisource community since 2008. Rhetorically asked: Why wait now with Wikidata indexing to refine the repeatedly corrected full texts through metadata, to link them and make them easier to use?

Meanwhile, another motivation is: How can we make Wikisource and Die Gartenlaube better known, to help gain collaboration and generate interest with short messages, blogposts, essays, and talks, so that teachers:inside or the Digital Humanities recognize both the dataset and the whole „wiki“ framework as relevant.

With the 1899 volume, the garden arbor project in Wikisource currently ends. As soon as the editing is advanced, further decades will probably be transcribed, corrected and indexed. In this respect, we see the data arbor not only as a prototype for indexing Wikisource with structured data and Wikidata. The project is an opportunity for Linked Open Storytelling – accompanying scholarly communication with Linked Open Data (LOD): showing what works, how this type of digitization works in the LOD context, what all was printed in it, and what benefits The Arbor could still provide today – in open educational resources (OER) with or without queries, as a mode and resource for standards data maintenance, for the construction of bibliographies and open access corpora of the 19th century literature received in ‚Die Gartenlaube‘, or in image galleries for the development of new media. Century or in image galleries for art history.

The #Bocknetz is a Wikidata query of the Leipzig anatomist Carl Ernst Bock’s own references to health tips already published by him on similar topics in each case in previous Gartenlaube issues: http://w.wiki/HdS. This self-citation network of Prof. Bock’s is basically part of the Wikicite biotope, the overarching Wikimedia initiative for open bibliographic data analysis. Prof. Bock was highly prolific, a critic of homeopathy, an opponent of quackery, and just one example of the science and engineering coverage in the Gartenlaube.

Who needs open metadata? Who is this data blueprint for?

For us – to win the 2019 imagined proverbial ‚honeypot‚ that indwells the digitized arbor; for „fame & glory“ out of curiosity in uncharted territory.

For research – to help and show female scientists how to map the locations of Germany’s strange trees with Wikidata and Open Street Map, for example. To prove how Wikimedia’s open – quasi-public – information infrastructures can be used to create, maintain and share free knowledge; potentially also as a hands on sandbox for Digital Humanities!?

For teachers – presumably the texts and illustrations of the garden arbor are relevant for teaching in various subjects. We hope to arouse curiosity with them. The school theme page is only an exemplary starting point for discovering Die Gartenlaube in detail. There are also elephants.

For libraries – complete indexing of the Garden Arbor in detail offers potential for additional title records in regional bibliographies. Admittedly: The project founders work in librarianship with an affinity for open bibliographic data and Wikidata in particular. Methods and project communication for Die Datenlaubes are ideally linked to knowledge gains for strategy-driven linkages of library Open GLAM strategies, Citizen Science, and Wikimediaportals tools. While Citizen Science is currently being discovered for librarianship in this country, the University of Edinburgh, for example, is developing strategies to increase the visibility of its own collections with Wikimedia tools and to systematically promote open educational resources.

For the Wikiverse (the communities of Wikimedia portals) – curated links between Wikisource text data fields, relevant Wikipedia articles, Wikidata items, and Structured Data on Commons (the pinpoint description of images) potentially increase the data quality of Wikimedia’s sister portals by connecting contexts and increasing visibility in search engines. Wikipedia has simplified access to information and just turned 20 years old. The Data Arbor can enrich this success story with historical sources – and yet is only a small contribution to digital world knowledge. Ideally multilingual, if someone can be found who considers this important.

With the DatenlaubeJam we offer an open format for open exchange every Tuesday morning, 8 am. The response of third parties is limited, we otherwise use the date as a Jour Fixe.

Data Modeling, Maintenance, and Queries for Digital Humanities

Which research questions can Die Datenlaube already answer? And how? We don’t know.

In a narrower sense, the project is an indexing initiative, intended with non-intended side effects. Be it data maintenance of the 2nd and 3rd order in Wikidata items for keywording (main subject, P921), authors (P50) and illustrators (P110) as well as statements describing these keywords in Wikidata (subclass of P279, instance of (P31), GND (P227), …). Or – as 1st order data maintenance – through subject indexing by tagging the list of previously untagged article items: https://w.wiki/43s. Currently, there are still about 4,500 garden arbor articles. We feel close to the Digital Humanities, but: We expect the methodological questions to the dataset in connection with relevant content-related research questions from the subject sciences – in the sense of division of labor. The description of the dataset in a separate data paper is still pending.

Technically, annotation of Wikisource texts with structured data is coming within reach. The new Wikisource template Annotate QID allows machine-readable annotation of entities (persons, places, corporations, terms) in Wikisource source texts with the corresponding Wikidata entities.

Also desirable and very welcome would be an LOD search engine for The Data Arbor: an intuitive query interface that queries linked full texts in Wikisource, structured bibliographic metadata of texts and illustrations in Wikidata, and structured indexed images in Wikimedia Commons.

#LinkedOpenStorytelling

Through serial storytelling, Die Gartenlaube became a great family journal: with series of articles, serial stories, war reports, natural sciences, inventions, recurring guides, and great illustrations – a mass medium of its time. We are gradually using this data to tell what we do with it: open metadata, citation networks, tweets, posters, blogposts, and articles.

Does this Linked Open Storytelling simply stand for communication with hyperlinks, hashtags and open data? Or should we use the concept in a narrower sense and as an alternative to the term digital storytelling especially for stories that can be told linked through open data in the first place? Stories that were previously impossible to tell without digitization and hyperlinks between digital assets, digital objects, and their metadata? #LOST would then be a subset of digital narratives or narrative techniques!?

The arbor offers both: known and forgotten texts, images, digitized œuvre of authors, illustrators – material to relate, link, use and evaluate these details anew with other bodies of knowledge. The Data Arbor has long been a Digital Humanities project as well: visualizing and analyzing intrinsically motivated cataloging of public domain texts and illustrations through crowd-based open software digital tools.

In short, the Data Arbor is a growing data mountain of illustrated civic histories from the 19th century. Today, we can research and tell history with this open data: linked open.

Project information

Linked media, texts, web pages, and data objects are partially documented in the Wikidata item (Q107573009) of this blog post.

Jens Bemme studied transport economics and works in the area of regional studies and citizen science at the Saxon State Library – Dresden State and University Library (Saxonica Department). He does research on historical cycling knowledge around 1900, especially of Upper Lusatia and the Baltic provinces. His other interests are village ovens and ‚Die Datenlaube‘.

This article is licensed under the following license: CC-BY 4.0. When reusing, please include the attribute rel=“canonical“ in the link to the original post!

How to cite this Article: Bemme, Jens (2021): „‚The Data Arbor‘: Open Citizen Science with Linked Open Storytelling in Unlocking the ‚Arbor'“. In: Kolodzie, Lisa, Schumacher, Mareike, Seltmann, Melanie and Brenn, Daniel (eds.): Public Humanities. https://publicdh.hypotheses.org/182.


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