Evidence map›Paper›PMID 42699088›Full record

ArticleiScience2026

A multi-technique approach for improving summary polar diagrams.

Aleksandar Anžel, Zewen Yang, Georges Hattab

Abstract read
In one paragraph

Article in iScience, 2026. 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

3 authors.

Aleksandar AnželCenter for Artificial Intelligence in Public Health Research (ZKI-PH), Robert Koch-Institute, Nordufer 20, 13353 Berlin, Germany.
Zewen YangCenter for Artificial Intelligence in Public Health Research (ZKI-PH), Robert Koch-Institute, Nordufer 20, 13353 Berlin, Germany.
Georges HattabCenter for Artificial Intelligence in Public Health Research (ZKI-PH), Robert Koch-Institute, Nordufer 20, 13353 Berlin, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

While the polar system may lack the universal familiarity of its Cartesian counterpart, it remains indispensable for certain tasks. Summary polar diagrams, such as Taylor and mutual information diagrams, address tasks like discovering relationships, visualizing data similarity, and quantifying correspondence. Although useful for revealing data relationships, these diagrams can be less intuitive and prone to issues like overplotting. We present a hybrid approach that combines overview+detail, aggregation, interactive filtering, Cartesian linking, and small multiples for summary polar diagrams. We performed a user study to assess the approach, and observed comparable response times among participants. In addition, three domain experts with varying levels of visualization experience reviewed the implemented solution, which applied summary polar diagrams across multiple application domains. Their feedback was essential for refining the design before the user study. The findings demonstrate the approach's versatility across these application areas and its effectiveness in supporting comprehension, accessibility, and utility.

Indexed as

model comparisonmutual information diagramoverview detailPolar coordinatespolar spacesmall multipleTaylor diagram

Identifiers

PMID42699088
PMCPMC13542598

What OpenQuestion holds

Textmetadata
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.