Discoverability in (a) Crisis
Open accessAbstract
The coronavirus pandemic has exposed a host of issues with the current scholarly communication system, one aspect being the discoverability of scientific knowledge. Observing the many shortcomings of discovery workflows in the course of COVID-19 confirms that discoverability itself is in crisis. In this article, we analyze the discoverability crisis and its root causes. We introduce open discovery infrastructure as a promising approach for the development of innovative discovery solutions. We present several efforts based on open discovery infrastructure that have emerged to provide better discovery of coronavirus research and discuss what is still needed to overcome the discoverability crisis.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The more freely metadata and full texts are available, the better they can be read, evaluated, processed and combined with data sets from other filter systems.
“The more freely metadata and full texts are available, the better they can be read, evaluated, processed and combined with data sets from other filter systems (Kraker et al. 2021).”
From The structural transformation of the scientific public sphere: Constitution and consequences of the path towards open access (2024) · cites this paper as Kraker et al. 2021
Cited by
Sorted by citations
Dobusch, L., & Heimstädt, M. (2024) · Philosophy & Social Criticism · doi:10.1177/01914537231203558 · Cited by 8 · see citing works
“The more freely metadata and full texts are available, the better they can be read, evaluated, processed and combined with data sets from other fi lter systems (Kraker et al. 2021).”
Background
- Authors
- Kraker, P., Schramm, M., & Kittel, C.
- Affiliations
- Open Knowledge Maps Gumpendorfer Straße 16/1/8 1060 Vienna Austria
- Corresponding author
- Kraker, Peter
- Venue
- ABI Technik
- Publisher
- Walter de Gruyter GmbH
- Published
- 2021-02-01
- Volume
- 41
- Issue
- 1
- Pages
- 3-12
- ISSN
- 0720-6763 (ISSN-L)
- 2191-4664
- OpenAlex
- W3128339580
- Cited by
- 7
- References
- 0
- Citations by year
- 2026: 1 · 2024: 2 · 2023: 1 · 2022: 2 · 2021: 1
- FWCI
- 1.28
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- ABI-Technik (publishedVersion, cc-by)
- Funders
- European Commission
- Horizon 2020 Framework Programme
- Topics
- Social Sciences › Decision Sciences › Information Systems and Management › Academic Publishing and Open Access
- Social Sciences › Business, Management and Accounting › Management Information Systems › Optics and Image Analysis
- Physical Sciences › Computer Science › Information Systems › Library Science and Information
- Keywords
- discoverability, scholarly communication, COVID-19 pandemic, research discovery, coronavirus research, open science
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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