Datafizierung unterstreicht den fundamentalen epistemischen und konzeptionellen Wandel von einer Welt, in der Daten ein eng definierter Teil der Ergebnisse von Forschungsprozessen waren, hin zu einem neuen Status Quo, in dem alle Forschungsprozesse immer bereits durch Informations- und Kommunikationstechnologien (ICT) computationell mediiert sind.

We think of the ‘digital’ as a previous historic movement when computation as digitality was understood in opposition to the analogue, rather than complementary […]

Berry und Fagerjord (Digital Humanities 2017), 2

Today, algorithms are such an intrinsic and fundamental part of how daily life is experienced that some scholars even argue that we live in “algorithmic cultures” […]. This evocative notion points to the increasing difficulty of separating algorithms from the activities that make up culture. It also evinces the complex ways in which human agency and algorithmic actions are intertwined […]

Siles (Living with Algorithms 2023), 1

It is our position that the “digital” cannot be understood as a separate domain of culture. If we actually examine the digital […] we see that today digital information processing is present in every aspect of our lives.

(Centre for Postdigital Cultures „About Us“ 2018)

Data are forms of information, a larger concept that is even more difficult to define. Epistemological and ontological problems abound, resulting in many books devoted to explicating information and knowledge

Borgman (Big Data, Little Data, No Data 2015), 18

[Datafication/modeling] is the work of abstracting discrete values from a phenomenon or artifact. These values may be expressed in numbers or texts and are necessarily a reduction of complex materials into a form for computation.

Drucker (DH Coursebook 2021), 3

Data need to be imagined as data to exist and function as such, and the imagination of data entails an interpretive base.

Gitelman („Introduction“ 2013), 3

To use […] tools well, we must, in some real sense, understand them better than the tool makers. […] The best kind of tools are therefore the ones that we make ourselves.

(Tenen „Blunt Instrumentalism“ 2016, 85)

Without access to the code, whether because it is proprietary or generated on the fly, as in the case of some machine-learning algorithms, analysts can only comment on the apparent operations of the code based on its effects. The operations of the code are left in the hands of those who can access it, usually those who have made or maintain it, and those who can read it.

(Marino Critical Code Studies 2020, 4)

Der Grundgedanke von Makerspaces ist das Teilen von Räumen, Ressourcen und Wissen innerhalb einer Gemeinschaft, welche Einzelpersonen sonst nicht zur Verfügung stünden

(Späth, Seidl, und Heinzel „Verbreitung und Ausgestaltung von Makerspaces an Universitäten in Deutschland“ 2019, 41)

I also remind DH is an imposter syndrome house of mirrors. You look around and see experts in GIS, TEI, dataviz, etc.; it’s hard to remember that people tend to be good at one of those things when the collective appears to be good at all of them. We all suck at most of DH.

(Weingart „Tweet“ 2021)

Unfortunately, I’m not particularly handy. On every new project, the tools require blood.

(Graham „Toot“ 2023)

Generous Thinking [begins] by proposing that rooting the humanities in generosity, and in particular in the practices of thinking with rather than reflexively against both the people and the materials with which we work, might invite more productive relationships and conversations not just among scholars but between scholars and the surrounding community.

(Fitzpatrick „Generous Thinking“ 2016)

Das Haus ist gebaut aus den Steinen, die vorhanden waren

(Brecht „Schlechte Zeiten“ 1967)

minimal computing connotes digital humanities work undertaken in the context of some set of constraints. This could include lack of access to hardware or software, network capacity, technical education, or even a reliable power grid

(Risam und Gil „Introduction“ 2022, Abschn. 3)

this implies learning how to produce, disseminate, and preserve digital scholarship ourselves, without the help we can’t get, even as we fight to build the infrastructures we need at the intersection of, with, and beyond institutional libraries and schools.

(Gil und Ortega „Global Outlooks in Digital Humanities“ 2016, 29)

Kollaboratives Projekt von Faculty, Bibliothekar_innen, Entwickler_innen an der University of Victoria, Kanada

• Problem:
  • Mit enormen Funding haben die DH vor allem viele tote Projekte hervor gebracht, von denen nur noch URLs in Publikationen existieren
• Hauptziele
  • Belange von Forscher_innen und Archivar_innen bei der langfristigen Kuratierung und Erhaltung von DH-Projekten in Einklang zu bringen
  • Entwicklung praktischer Werkzeuge.

Sustainable und FAI …

• Setzen alles auf Wikidata auf
  • (Linked) Open Data, CC0, quelloffene Software
  • Community und User Management
  • Multilingualität von Interface und Daten
  • hohe Sichtbarkeit: Suchmaschinen, Integration in Normdateien (VIAF)
• minimales, domänenspezifisch erweiterbares Datenmodell

… R

• (Nach)-nutzung bestehender Datensätze
  • Mapping nach Wikidata
    • Registries: TAPoR, SSH Open Marketplace
    • Taxonomien: TaDiRAH
    • Literatur: DHQ, DHd Konferenzen …
• Versionierte Publikation des Graphen als RDF
  • GitLab und Zenodo