Evidence map›Paper›PMID 33117974›Full record

ArticleAnalytica chimica acta: X2019

Procedures for systematic capture and management of analytical data in academia.

Jan Potthoff, Pierre Tremouilhac, Patrick Hodapp, Bernhard Neumair, Stefan Bräse, Nicole Jung

Open access · hybridAbstract read
In one paragraph

Article in Analytica chimica acta: X, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
4.8field-weighted citation impact, top 4% of its field
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

6 citing papers in PubMed, 22 citations in OpenAlex.

  1. A Guide to Bayesian Optimization in Bioprocess Engineering.Biotechnology and bioengineering · 2026
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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

6 authors at 1 institution in 1 country.

Jan PotthoffSteinbuch Centre for Computing, Karlsruhe Institute of Technology, Hermann-von-Helmholtz-Platz 1, 76344, Eggenstein-Leopoldshafen, Germany.
Pierre TremouilhacInstitute of Toxicology and Genetics, Karlsruhe Institute of Technology, Hermann-von-Helmholtz-Platz 1, 76344, Eggenstein-Leopoldshafen, Germany.
Patrick HodappInstitute of Toxicology and Genetics, Karlsruhe Institute of Technology, Hermann-von-Helmholtz-Platz 1, 76344, Eggenstein-Leopoldshafen, Germany.
Bernhard NeumairSteinbuch Centre for Computing, Karlsruhe Institute of Technology, Hermann-von-Helmholtz-Platz 1, 76344, Eggenstein-Leopoldshafen, Germany.
Stefan BräseInstitute of Toxicology and Genetics, Karlsruhe Institute of Technology, Hermann-von-Helmholtz-Platz 1, 76344, Eggenstein-Leopoldshafen, Germany.
Nicole JungInstitute of Toxicology and Genetics, Karlsruhe Institute of Technology, Hermann-von-Helmholtz-Platz 1, 76344, Eggenstein-Leopoldshafen, Germany.
Karlsruhe Institute of Technology · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Data management in universities is a challenging endeavor in particular due to the diverse infrastructure of devices and software in combination with limited budget. Nevertheless, in particular the analytical measurements and data sets need to be stored if possible digitally and in a well-organized manner. This manuscript describes how scientists can achieve a data management workflow focusing on data capture and storage by small adaptions to commonly used systems. The presented method includes data transfer options from ubiquitous devices like NMR instruments, GC (MS) or LC (MS), IR and Raman, or mass spectrometers to a central server and the visualization of the available data files in an electronic lab notebook (ELN). The given instruments were chosen according to the needs of synthetic chemists, in particular devices needed in organic, inorganic and polymer chemistry where single data files in the range of several megabytes per data set are produced. Altogether, three different data transfer systems were elaborated to allow a flexible handling of different devices running with different proprietary software: The first procedure allows data capture via the use of a mail server as data exchange point. With the second procedure, data are automatically mirrored from a local file folder to a central storage server where new files are monitored and processed. The third procedure was designed to transfer data with manual support to a central server which is supervised to register new information. All components that are necessary to install and use the herein elaborated functions are available as Open Source and the designed workflows are described step by step to facilitate the adaption of procedures in other universities accordingly if desired.

Indexed as

Analytical dataELNInformation and management systemsInfrastructureResearch data management

Identifiers

PMID33117974
PMCPMC7587027
OpenAlexW2914140298

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.