Linked data strategies for conserving digital research outputs

Kräutli, Florian; Chen, Esther; Valleriani, Matteo

doi:10.4324/9781003131816-10

Cited by 5 publications

(5 citation statements)

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“…The SÓRC Project also highlighted a number of issues that lie at the heart of the current interface design in the humanities. For example, scholars such as Borgman (2010), Drucker (2011) and Kräutli (2016) have reiterated that we currently lack the suitable tools to make sense of humanities data. Kräutli (2016) has augmented this argument by developing suitable digital tools that address the problem.…”

Section: Discussionmentioning

confidence: 99%

“…For example, scholars such as Borgman (2010), Drucker (2011) and Kräutli (2016) have reiterated that we currently lack the suitable tools to make sense of humanities data. Kräutli (2016) has augmented this argument by developing suitable digital tools that address the problem. More recently, Vane (2018) has also expanded on ways to explore the development of timeline visualizations to assess archival data.…”

Section: Discussionmentioning

confidence: 99%

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Insider or outsider? Exploring some digital challenges in ethnomusicology

Egan

2021

Interdisciplinary Science Reviews

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This paper considers debates that have taken place in ethnomusicology as a result of engagement with the classification of data. Landmark projects over the past century introduced various classification systems and initiated important debates within the field. From the author's perspective, classification of data is understood as a necessary precursor to computation in these projects. Classificatory thinking is used here as a theme to explore debates that have arisen when abstractions of musical practice have been suggested for use with ethnomusicology. The paper proposes that a recent approach to research practice for embedding computation adds to ongoing interdisciplinary work, demonstrating novel ways of contextualizing archival materials with ethnography alongside computation. The approach attempted to strike a balance for engaging large amounts of data in ethnomusicology. The paper argues that some resulting tensions arising from classification lead to insights, which cannot be drawn by ethnomusicological methods alone.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Insider or outsider? Exploring some digital challenges in ethnomusicology

Egan

2021

Interdisciplinary Science Reviews

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“…Once a project is completed, publications may remain, but the datasets that were originally generated, together with their external web presentations and possibly even the electronic copies of the analyzed material are often no longer available online. This phenomenon is due to the lack of a sustained perspective: Because projects are usually funded for a limited period of time, it is highly uncommon for the institution that hosted the project to take over its maintenance and preservation (Kräutli et al 2021). A record of lost datasets has so far not been compiled, but the problem is widely recognized.…”

Section: Sustainability: Data Models and Ontologiesmentioning

confidence: 99%

Digital Perspectives in History

Siebold

Valleriani

2022

Histories

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This article outlines the state of digital perspectives in historical research, some of the methods and tools in use by digital historians, and the possible or even necessary steps in the future development of the digital approach. We begin by describing three main computational approaches: digital databases and repositories, network analysis, and Machine Learning. We also address data models and ontologies in the larger context of the demand for sustainability and linked research data. The section is followed by a discussion of the (much needed) standards and policies concerning data quality and transparency. We conclude with a consideration of future scenarios and challenges for computational research.

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“…This article illustrates the visualization of an extensive image collection through digital means. Following a growing interest in the digital mapping of images-proved by the various scientific articles published on the subject (Bludau et al, 2021;Crockett, 2019;Seguin, 2018), Ph.D. theses (Kräutli, 2016;Vane, 2019), software (American Museum of Natural History, 2020/2022; Diagne et al, 2018;Pietsch, 2018Pietsch, /2022, and presentations (Benedetti, 2022;Klinke, 2021)-this text describes an interdisciplinary experiment at the intersection of information design, experimental museology, and cultural analytics.…”

Section: Introductionmentioning

confidence: 99%

Surprise machines

Rodighiero

Derry

Duhaime

et al. 2022

IDJ

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Surprise Machines is a project of experimental museology that sets out to visualize the entire image collection of the Harvard Art Museums, with a view to opening up unexpected vistas on more than 200,000 objects usually inaccessible to visitors. The project is part of the exhibition organized by metaLAB (at) Harvard entitled Curatorial A(i)gents and explores the limits of artificial intelligence to display a large set of images and create surprise among visitors. To achieve this feeling of surprise, a choreographic interface was designed to connect the audience’s movement with several unique views of the collection.

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Linked data strategies for conserving digital research outputs

Cited by 5 publications

References 0 publications

Insider or outsider? Exploring some digital challenges in ethnomusicology

Insider or outsider? Exploring some digital challenges in ethnomusicology

Digital Perspectives in History

Surprise machines

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