Powered by OpenAIRE graph
Found an issue? Give us feedback
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ ZENODOarrow_drop_down
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Other literature type . 2023
License: CC BY
Data sources: Datacite
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Other literature type . 2023
License: CC BY
Data sources: ZENODO
versions View all 1 versions
addClaim

Datasheets for Digital Cultural Heritage Datasets

Authors: Alkemade, Henk; Claeyssens, Steven; Colavizza, Giovanni; Freire, Nuno; Irollo, Alba; Lehmann, Jörg; Neudecker, Clemens; +2 Authors

Datasheets for Digital Cultural Heritage Datasets

Abstract

As the collections as data paradigm is gaining momentum, fueled by powerful advancements in machine learning and data mining technologies, the institutions managing digital cultural heritage collections urgently need to learn how to provide meaningful information about their collections as data, i.e. not on the item level, but on the collection level. Datasheets just do that. Similar to instruction leaflets, they document the context and content of datasets needed for re-using such datasets and enable transparency and accountability. They can mitigate unwanted biases in machine learning models, facilitate reproducibility of machine learning results, and help researchers to choose the right dataset. They open up a space for negotiation and facilitate interdisciplinary communication between cultural heritage practitioners, researchers and technical experts. While the concept of datasheets was introduced to the machine learning community by Gebru et al (Datasheets for Datasets, https://doi.org/10.1145/3458723) and Pushkarna et al (Data Cards, https://doi.org/10.1145/3531146.3533231), it still lacks adaptation to the requirements of the European cultural heritage field. Cultural heritage datasets differ from contemporary, industrial datasets in many ways: they are heterogeneous with respect to the time period covered, the place or regions incorporated in them, or the cultural contexts in which they have to be located. They may contain sensitive content, e.g. in the case of a collection of sources from former colonies, and thus may require ethical questioning. Metrics—highly estimated by machine learners—often are not helpful to describe such datasets. Because cultural heritage datasets grow over time, the data sheets need to be adaptable, taking enlarged datasets and changing uses into perspective. The complexity of such data is often underestimated by computer scientists, which impedes the kind of scientific negotiations of meaning and interpretive transfers which datasheets aim to facilitate. Resulting out of a Europeana Working Group, we present here a datasheet template for digital cultural heritage datasets. We explicitly understand this template as a proposal, intended for gaining experience and to collect feedback. It is important to stress that the template should be thought of as modular: it is up to those filling in the form to decide which questions should be answered and which questions could be ignored.

Keywords

transparency, datasheets, responsible AI, dataset documentation, data cards, reproducibility, model cards

  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    0
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
    OpenAIRE UsageCounts
    Usage byUsageCounts
    visibility views 106
    download downloads 91
  • 106
    views
    91
    downloads
    Powered byOpenAIRE UsageCounts
Powered by OpenAIRE graph
Found an issue? Give us feedback
visibility
download
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
OpenAIRE UsageCountsViews provided by UsageCounts
downloads
OpenAIRE UsageCountsDownloads provided by UsageCounts
0
Average
Average
Average
106
91
Green