10.5061/DRYAD.ZKH18938M
Kos-Braun, Isabelle
0000-0002-2380-5720
Heidelberg University
Gerlach, Bjoern
0000-0002-4900-6302
PAASP
Pitzer, Claudia
Heidelberg University
Survey of Core Facilities Raw Data
Dryad
dataset
2020
Life science
Federal Ministry of Education and Research BMBF*
01PW18001
Federal Ministry of Education and Research BMBF
01PW18001
2020-11-04T00:00:00Z
2020-11-04T00:00:00Z
en
1960070 bytes
2
CC0 1.0 Universal (CC0 1.0) Public Domain Dedication
Recently, it has become evident that academic research faces issues with
the reproducibility of research data. As Core Facilities (CFs) have a
central position in the research infrastructure they are able to promote
and disseminate good research standards through their users. To identify
the most important factors for research quality, we polled 253 CFs across
Europe about their practices and analysed in detail the interaction
process between CFs and their users, from the first contact to the
publication of the results. Although the survey showed that CFs aim to
train and advise their users, it highlighted the following areas, the
improvement of which would directly increase research quality: 1)
motivating users to follow the advice and procedures for best research
practice, 2) providing clear guidance on data management practices, 3)
improving communication along the whole research process and 4) clearly
defining the responsibilities of each party.
We developed a 68-question online survey asking various questions about
research quality in core facilities (CFs) using Limesurvey software. We
sent the survey individually to 1000 CFs’ leaders by email. In addition,
our survey was publicized in the CTLS newsletter (Core Technologies for
Life Sciences) and several facilities we contacted by initial email
further forwarded the survey link to their colleagues. The survey was open
from December 2019 to July 2020. All survey participants were anonymous.
We received 276 total forms (28% participation rate), 253 of which were
complete. The survey contained yes/no, multiple-choice and open-field text
questions. The survey data was analysed using Microsoft Office 365 Excel.
We had 28 free text fields to allow the respondents express themselves
freely, to eliminate potential bias stemming from suggested answers.
Open-field answers were evaluated by reading each of them personally and
defining categories manually based on the replies so that they correspond
to the opinions of the participants as faithfully as possible (see the
last sheet “explanations” of the excel file). Keywords were then chosen to
allow automatic counting in Excel. We analysed the data using standard
Excel tools in three different ways: 1) all facilities together, 2)
facilities grouped by their type/specialization (genomics, microscopy,
etc) and 3) grouped by their operating mode (full-, hybrid-,
self-service).