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The following results are related to Digital Humanities and Cultural Heritage. Are you interested to view more results? Visit OpenAIRE - Explore.
3 Research products, page 1 of 1

  • Digital Humanities and Cultural Heritage
  • Research data
  • NO
  • DataverseNO
  • The Tromsø Repository of Language and Linguistics (TROLLing)
  • Digital Humanities and Cultural Heritage

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  • Open Access
    Authors: 
    Rettberg, Jill Walker; Kronman, Linda; Solberg, Ragnhild; Gunderson, Marianne; Bjørklund, Stein Magne; Stokkedal, Linn Heidi; De Seta, Gabriele; Jacob, Kurdin; Markham, Annette;
    Publisher: DataverseNO
    Project: EC | Machine Vision (771800)

    This dataset captures cultural attitudes towards machine vision technologies as they are expressed in art, games and narratives. The dataset includes records of 500 creative works (including 77 digital games, 191 digital artworks and 236 movies, novels and other narratives) that use or represent machine vision technologies like facial recognition, deepfakes, and augmented reality. The dataset is divided into three main tables, relating to the works, to specific situations in each work involving machine vision technologies, and to the characters that interact with the technologies. Data about each work includes title, author, year and country of publication; types of machine vision technologies featured; topics the work addresses, and sentiments associated with that machine vision usage in the work. In the various works we identified 884 specific situations where machine vision is central. The dataset includes detailed data about each of these situations that describes the actions of human and non-human agents, including machine vision technologies. The dataset is the product of a digital humanities project and can be also viewed as a database at http://machine-vision.no. Data was collected by a team of topic experts who followed an analytical model developed to explore relationships between humans and technologies, inspired by posthumanist and feminist new materialist theories. The project team identified relevant works by searching databases, visiting exhibitions and conferences, reading scholarship, and consulting other experts. The inclusion criteria were creative works( art, games, narratives (movies, novels, etc)) where one of the following machine vision technologies was used in or represented by the work: 3D scans, AI, Augmented reality, Biometrics, Body scans, Camera, Cameraphone, Deepfake, Drones, Emotion recognition, Facial recognition, Filtering, Holograms, Image generation, Interactive panoramas Machine learning, MicroscopeOrTelescope Motion tracking, Non-Visible Spectrum Object recognition, Ocular implant, Satellite images, Surveillance cameras, UGV, Virtual reality, and Webcams. The dataset as well as the more detailed database can be viewed, searched, extracted, or otherwise used or reused and is considered particularly useful for humanities and social science scholars interested in the relationship between technology and culture, and by designers, artists, and scientists developing machine vision technologies.

  • Open Access
    Authors: 
    Glomb, Tomas;
    Publisher: DataverseNO
    Project: EC | AscNet (892604)

    Dataset of variables and results for spatial network analysis of shortest distances on Roman roads between the proxies for the positions of Roman soldiers and the worship of Asclepius, Apollo, Minerva, and Jupiter, and the positions of Roman physicians in the selected provinces of the Roman Empire. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 892604.

  • Open Access
    Authors: 
    Leivada, Evelina; Westergaard, Marit;
    Publisher: DataverseNO
    Project: EC | DIVA (746652)

    This research put the nature and rigidity of linguistic hierarchies to test, taking multiple adjective placement as a case study. We developed an on-line forced choice experiment that measured (i) acceptability judgment ratings and (ii) reaction times, in a big sample of neurotypical, adult speakers of Standard Greek (n=140) and Cypriot Greek (n=30). The task compares what happens when people are asked to process sentences that either comply with or violate allegedly universal ordering constraints that have been described as the outcome of innately wired hierarchies. Our findings do not provide any evidence for a universal hierarchy for adjective ordering that imposes one rigid, unmarked order. We argue that the obtained results are effectively reducing the amount of primitives that are cast as innate, eventually offering a deflationist approach to human linguistic cognition.