Evidence map›Paper›PMID 26730820›Full record

ArticlePloS one2016

Resource Disambiguator for the Web: Extracting Biomedical Resources and Their Citations from the Scientific Literature.

Ibrahim Burak Ozyurt, Jeffrey S Grethe, Maryann E Martone, Anita E Bandrowski

Abstract read
In one paragraph

Article in PloS one, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 1 pooled it
–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

15 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Establishing an early indicator for data sharing and reuse.Learned publishing : journal of the Association of Learned and Professional Society Publishers · 2024
    Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Review
  13. Article
  14. Article
  15. Article
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

4 authors.

Ibrahim Burak OzyurtCRBS, UCSD, La Jolla, CA, United States of America.
Jeffrey S GretheCRBS, UCSD, La Jolla, CA, United States of America.
Maryann E MartoneCRBS, UCSD, La Jolla, CA, United States of America.
Anita E BandrowskiCRBS, UCSD, La Jolla, CA, United States of America.

Funding

NIDDK Network Coordinating UnitU24DK097771 · NIDDK · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI Shuibing Chen, Jeffrey S. Grethe · 2013 to 2026
$20.9M
OPERATION, SUPPORT AND STRATEGIC ENHANCEMENT OF THE NEUROSCIENCE INFORMATION FRAMEWORKU24DA039832 · NIDA · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI GRETHE, JEFFREY S., MARTONE, MARYANN E · 2015 to 2016
$2.0M
NIDA NIH HHS HHSN271200577531CNIDA NIH HHS U24 DA039832NIDDK NIH HHS U24 DK097771PHS HHS HHSN271200577531C
6 · The paper itself

Abstract

The NIF Registry developed and maintained by the Neuroscience Information Framework is a cooperative project aimed at cataloging research resources, e.g., software tools, databases and tissue banks, funded largely by governments and available as tools to research scientists. Although originally conceived for neuroscience, the NIF Registry has over the years broadened in the scope to include research resources of general relevance to biomedical research. The current number of research resources listed by the Registry numbers over 13K. The broadening in scope to biomedical science led us to re-christen the NIF Registry platform as SciCrunch. The NIF/SciCrunch Registry has been cataloging the resource landscape since 2006; as such, it serves as a valuable dataset for tracking the breadth, fate and utilization of these resources. Our experience shows research resources like databases are dynamic objects, that can change location and scope over time. Although each record is entered manually and human-curated, the current size of the registry requires tools that can aid in curation efforts to keep content up to date, including when and where such resources are used. To address this challenge, we have developed an open source tool suite, collectively termed RDW: Resource Disambiguator for the (Web). RDW is designed to help in the upkeep and curation of the registry as well as in enhancing the content of the registry by automated extraction of resource candidates from the literature. The RDW toolkit includes a URL extractor from papers, resource candidate screen, resource URL change tracker, resource content change tracker. Curators access these tools via a web based user interface. Several strategies are used to optimize these tools, including supervised and unsupervised learning algorithms as well as statistical text analysis. The complete tool suite is used to enhance and maintain the resource registry as well as track the usage of individual resources through an innovative literature citation index honed for research resources. Here we present an overview of the Registry and show how the RDW tools are used in curation and usage tracking.

Indexed as

InternetSoftwareBiomedical ResearchComputational BiologyDatabases, FactualHumansInformation Storage and RetrievalNeurosciencesPublicationsRegistriesReproducibility of Results

Identifiers

PMID26730820
PMCPMC5156472

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.