Evidence map›Paper›PMID 35928800›Full record

ArticleFrontiers in research metrics and analytics2022

A Scholarly Knowledge Graph-Powered Dashboard: Implementation and User Evaluation.

Olga Lezhnina, Gábor Kismihók, Manuel Prinz, Markus Stocker, Sören Auer

Abstract read
In one paragraph

Article in Frontiers in research metrics and analytics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Olga LezhninaLearning and Skill Analytics Research Group, TIB-Leibniz Information Centre for Science and Technology, Hannover, Germany.
Gábor KismihókLearning and Skill Analytics Research Group, TIB-Leibniz Information Centre for Science and Technology, Hannover, Germany.
Manuel PrinzData Science and Digital Libraries Group, TIB-Leibniz Information Centre for Science and Technology, Hannover, Germany.
Markus StockerKnowledge Infrastructures Research Group, TIB-Leibniz Information Centre for Science and Technology, Hannover, Germany.
Sören AuerL3S Research Center, Leibniz University of Hannover, Hannover, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Scholarly knowledge graphs provide researchers with a novel modality of information retrieval, and their wider use in academia is beneficial for the digitalization of published works and the development of scholarly communication. To increase the acceptance of scholarly knowledge graphs, we present a dashboard, which visualizes the research contributions on an educational science topic in the frame of the Open Research Knowledge Graph (ORKG). As dashboards are created at the intersection of computer science, graphic design, and human-technology interaction, we used these three perspectives to develop a multi-relational visualization tool aimed at improving the user experience. According to preliminary results of the user evaluation survey, the dashboard was perceived as more appealing than the baseline ORKG-powered interface. Our findings can be used for the development of scholarly knowledge graph-powered dashboards in different domains, thus facilitating acceptance of these novel instruments by research communities and increasing versatility in scholarly communication.

Indexed as

dashboardORKGscholarly communicationscholarly knowledge graphuser evaluation

Identifiers

PMID35928800
PMCPMC9343766

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.