Evidence map›Paper›PMID 31334252›Full record

ArticleFrontiers in veterinary science2019

A Transdisciplinary Approach Supporting the Implementation of a Big Data Project in Livestock Production: An Example From the Swiss Pig Production Industry.

Céline Faverjon, Abraham Bernstein, Rolf Grütter, Christina Nathues, Heiko Nathues, Cristina Sarasua, Martin Sterchi, Maria-Elena Vargas, John Berezowski

Abstract read
In one paragraph

Article in Frontiers in veterinary science, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Review
  3. 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

9 authors.

Céline FaverjonVetsuisse Faculty, Veterinary Public Health Institute, University of Bern, Bern, Switzerland.
Abraham BernsteinDepartment of Informatics, University of Zurich, Zurich, Switzerland.
Rolf GrütterSwiss Federal Research Institute, Birmensdorf, Switzerland.
Christina NathuesFederal Veterinary Office, Bern, Switzerland.
Heiko NathuesVetsuisse Faculty, Clinic for Swine, University of Bern, Bern, Switzerland.
Cristina SarasuaDepartment of Informatics, University of Zurich, Zurich, Switzerland.
Martin SterchiDepartment of Informatics, University of Zurich, Zurich, Switzerland.
Maria-Elena VargasDepartment of Informatics, University of Zurich, Zurich, Switzerland.
John BerezowskiVetsuisse Faculty, Veterinary Public Health Institute, University of Bern, Bern, Switzerland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Big Data approaches offer potential benefits for improving animal health, but they have not been broadly implemented in livestock production systems. Privacy issues, the large number of stakeholders, and the competitive environment all make data sharing, and integration a challenge in livestock production systems. The Swiss pig production industry illustrates these and other Big Data issues. It is a highly decentralized and fragmented complex network made up of a large number of small independent actors collecting a large amount of heterogeneous data. Transdisciplinary approaches hold promise for overcoming some of the barriers to implementing Big Data approaches in livestock production systems. The purpose of our paper is to describe the use of a transdisciplinary approach in a Big Data research project in the Swiss pig industry. We provide a brief overview of the research project named "Pig Data," describing the structure of the project, the tools developed for collaboration and knowledge transfer, the data received, and some of the challenges. Our experience provides insight and direction for researchers looking to use similar approaches in livestock production system research.

Indexed as

big datafood animal productionnetwork analysispigtransdisciplinary

Identifiers

PMID31334252
PMCPMC6620609

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.