Evidence map›Paper›PMID 37106414›Full record

ArticleBMC research notes2023

Advancing methods in big data capture, integration, classification and liberation.

Eftim Zdravevski, Ivan Miguel Pires

Abstract readEditorial
In one paragraph

Article in BMC research notes, 2023. 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

2 authors.

Eftim ZdravevskiFaculty of Computer Science and Engineering, University Ss Cyril and Methodius, Skopje, 1000, Macedonia. eftim.zdravevski@finki.ukim.mk.
Ivan Miguel PiresInstituto de Telecomunicações, Universidade da Beira Interior, Covilhã, 6200-001, Portugal.

Funding

FEDER - PT2020 UIDB/50008/2020
6 · The paper itself

Abstract

This special issue focuses on the importance of advancing research techniques for managing and analyzing data in today's data-rich landscape. In this editorial, we set the context and invite contributions for a BMC Collection of articles titled 'Advancing methods in data capture, integration, classification and liberation'. The collection emphasizes the need for efficient ways to standardize, cleanse, integrate, enrich, and liberate data, highlighting recent advancements in research methods and industrial technologies that facilitate this. We invite researchers to submit their best work to the collection and to showcase the latest advancements and additions to research techniques.

Indexed as

Big DataResearch DesignIndustry

Identifiers

PMID37106414
PMCPMC10141912

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.