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Data · dataset · 2026

SYNERGY+

Listed in IISH Dataverse and ODISSEI Portal — shown once because both records carry DOI 10.34894/ddcvcv

Description

SYNERGY+ is the successor of SYNERGY, a free and open dataset on study selection in systematic reviews. When using this dataset, please cite the accompanying preprint: van der Kuil, T., Westerbeek, E., de Bruin, J., Fang, Q., & van de Schoot, R. (2026). SYNERGY+: A Large-Scale, Curated Benchmark Dataset of Expert Screening Decisions for Systematic Reviews. arXiv preprint. arxiv.org/abs/XXXX.XXXXX The preprint contains a full description of what is in the dataset, an overview of steps taken, and the processes followed.

For a quick overview: this new version now covers 119 systematic reviews, bringing the total number of records to 494.203. In total 168.948 are classified as open-access by OpenAlex and used in the official benchmark. We have gathered, checked and thoroughly cleaned all the abstracts.

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Similar to SYNERGY, this dataset can be used in various fields and for several types of research. But with the addition of more and cleaner records, the options for answering more specific questions will increase. As with the earlier version of SYNERGY, the dataset contains a large number of variables for each record, provided by OpenAlex.

Additionaly, we have gathered and extracted information on each of the included reviews. This data can be found in reviews.csv, along with an explanation about the data in codebook.pdf. We thank the authors of all systematic reviews included for publishing their data, please see this page for a full overview.

The easiest way to get the SYNERGY+ dataset is via the synergy-dataset Python package. Please read this page for how to do that.

Links

Where it is published

Catalogue records · 2

Topics

Stated by source
Computer and Information Science · Computer and Information Science · Engineering · Engineering · Medicine, Health and Life Sciences · Medicine, Health and Life Sciences · Social Sciences · Social Sciences
From keywords
Computer Science & AI · Computer Science & AI · Engineering · Engineering · Humanities · Humanities · Life Sciences · Life Sciences · Machine learning · Machine learning · Medicine & Health · Medicine & Health · Natural language processing · Natural language processing · Social Science · Social Science
Provenance · 2 source records, 30 field assertions
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IISH Dataversedoi:10.34894/DDCVCV10 d agoJSON v1
ODISSEI Portaldoi:10.34894/DDCVCV6 d agoJSON v1
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