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RSE International Survey 2022

World

  1. Education and academic field
  2. Professional developer
  3. How time is spent
  4. Previous employment
  5. Collaboration and training
  6. Publications and citations
  7. Open source and DOI
  8. Good practices
  9. Tools and programming languages
  10. Job satisfaction
  11. Research software engineer

Education and academic field

This section contains the information about the type of education the participants have, as well as their highest degree obtained.

We asked the participants, in which field they are working. With that question, it is possible to see which current field employed the most of RSE/RSD. The questions was specific to each country and was multiple choice. Each participant could choose several fields. We then calculate the different proportion by dividing each field by the total of participants that have selected at least one option.

Questions in this section

  • What is the highest level of education you have attained? (one choice list)
  • In which discipline is your highest academic qualification? (one choice list)
  • List any professional qualifications you hold (free text)

Levels of education

Highest level of education for World Count Percentage Percentage in 2018 Difference with previous year
Doctorate 394 39.52 43.32 -3.8
Master degree 247 24.77 29.45 -4.67
Undergraduate degree 69 6.92 9.45 -2.53
doctorate 65 6.52 nan nan
PhD 34 3.41 2.71 0.7
nan 31 3.11 0.4 2.71
doctorat 29 2.91 nan nan
WO (Wetenschappelijk onderwijs) Master 26 2.61 2.01 0.6
AQF 10 - Doctoral Degree 19 1.91 6.33 -4.43
AQF 8 - Bachelor Honours Degree / Graduate Certificate / Graduate Diploma 7 0.7 1.31 -0.6
Other 7 0.7 0.8 -0.1
Final secondary-school examinations, general qualification for university entrance 5 0.5 0.7 -0.2
Masters Degree 4 0.4 0.1 0.3
AQF 9 - Masters Degree 4 0.4 1.11 -0.7
licentiate 3 0.3 nan nan
HBO (Hoger beroepsonderwijs) Master 3 0.3 0.3 -0
diplôme dingénieur 2 0.2 nan nan
bac+5 2 0.2 nan nan
AQF 7 - Bachelor Degree 2 0.2 1.11 -0.9
doctorat (phd) 2 0.2 nan nan
associate 2 0.2 nan nan
HBO (Hoger beroepsonderwijs) Bachelor 2 0.2 0.1 0.1
Further Education 2 0.2 nan nan
high school 2 0.2 nan nan
bac +5 2 0.2 nan nan
diplome dingenieur (baccalaureat +5) 1 0.1 nan nan
bsc (currently attending; not graduated) 1 0.1 nan nan
High School 1 0.1 nan nan
None 1 0.1 nan nan
magister 1 0.1 nan nan
bsc in computer science 1 0.1 nan nan
master degree 1 0.1 nan nan
Associate degree (typically from a community college) 1 0.1 nan nan
bac+2 1 0.1 nan nan
ma 1 0.1 nan nan
enrolled in phd (computer science) 1 0.1 nan nan
masters of science 1 0.1 nan nan
maestria 1 0.1 nan nan
bsc 1 0.1 nan nan
hochschule 1 0.1 nan nan
doctorant 1 0.1 nan nan
doctorat + 2ans de post-doc 1 0.1 nan nan
WO (Wetenschappelijk onderwijs) Bachelor 1 0.1 0.3 -0.2
btech 1 0.1 nan nan
pre-bachelor 1 0.1 nan nan
habilitation à diriger des thèses - thèse 1 0.1 nan nan
Further Education (NVQ A-Level, …) 1 0.1 0.4 -0.3
graduate degree 1 0.1 nan nan
bac+8 1 0.1 nan nan
applicable 1 0.1 nan nan
phd candidate 1 0.1 nan nan
bac+4 1 0.1 nan nan
mastère spécialisé (bac +6) 1 0.1 nan nan
italian laurea (5 years with thesis) roughly master 1 0.1 nan nan
je suis actuellement en doctorat 1 0.1 nan nan
bac +3 1 0.1 nan nan
GSCEs 1 0.1 0.1 -0

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education_level

Academic field for education and professional development

Alongside of question about education level we also asked the participants in which field they finished their highest level of education. Here again the propositions were specific to each countries so the comparison is difficult despite lot of overlapping in the categories.

Field of education for World Count Percentage Percentage in 2018 Difference with previous year
Computer Science 233 23.37 22.11 1.26
Physics and Astronomy 216 21.66 23.42 -1.75
Biological Sciences 103 10.33 9.55 0.78
Mathematics 81 8.12 6.93 1.19
Chemistry 48 4.81 2.21 2.6
Geography & Environmental Sciences 38 3.81 4.62 -0.81
Electrical & Electronic Engineering 35 3.51 3.62 -0.11
Mechanical Engineering 28 2.81 1.71 1.1
nan 18 1.81 1.21 0.6
Geology 15 1.5 1.61 -0.1
Civil Engineering 14 1.4 0.9 0.5
Psychology 13 1.3 0.7 0.6
General Engineering 11 1.1 1.11 -0
Agriculture & Forestry 10 1 0.1 0.9
Aeronautical & Manufacturing Engineering 9 0.9 0.4 0.5
Physical sciences 9 0.9 nan nan
Chemical Engineering 8 0.8 1.01 -0.2
History 8 0.8 0.8 -0
Linguistics 8 0.8 0.3 0.5
Medicine 8 0.8 0.4 0.4
Information and computing sciences 7 0.7 nan nan
Materials Technology 6 0.6 0.9 -0.3
Economics 6 0.6 0.6 -0
Earth sciences 5 0.5 nan nan
Business & Management Studies 5 0.5 0.6 -0.1
Robotics 5 0.5 0.3 0.2
Sociology 4 0.4 0.2 0.2
Engineering 4 0.4 nan nan
Philosophy 3 0.3 0.5 -0.2
Communication & Media Studies 3 0.3 0.3 -0
English 3 0.3 0.3 -0
Music 2 0.2 0.2 -0
German 2 0.2 0.3 -0.1
Classics & Ancient History 2 0.2 0.2 -0
Sports Science 2 0.2 nan nan
Anthropology 2 0.2 nan nan
Librarianship & Information Management 2 0.2 0.4 -0.2
Biological sciences 2 0.2 nan nan
Politics 2 0.2 0.2 -0
Biomedical and clinical sciences 1 0.1 nan nan
Environmental sciences 1 0.1 nan nan
Town & Country Planning and Landscape Design 1 0.1 nan nan
Dentistry 1 0.1 nan nan
Language, communication and culture 1 0.1 nan nan
Ophthalmics 1 0.1 nan nan
East & South Asian Studies 1 0.1 0.1 -0
Veterinary Medicine 1 0.1 nan nan
Middle Eastern and African Studies 1 0.1 nan nan
Fashion 1 0.1 nan nan
Art & Design 1 0.1 0.2 -0.1
Anatomy & Physiology 1 0.1 nan nan
Health sciences 1 0.1 nan nan
Education 1 0.1 0.4 -0.3
Theology & Religious Studies 1 0.1 0.2 -0.1
Accounting & Finance 1 0.1 0.2 -0.1
French 1 0.1 nan nan

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academic_field_edu

academic_field_edu_wordcloud

Academic field of work

field of work for World Count Percentage Percentage in 2018 Difference with previous year
Computer Science 425 42.63 35.58 7.05
Biological Sciences 273 27.38 21.61 5.77
Physics and Astronomy 248 24.87 27.14 -2.26
Geography & Environmental Sciences 159 15.95 15.38 0.57
Mathematics 147 14.74 10.05 4.69
Medicine 111 11.13 8.34 2.79
Chemistry 95 9.53 6.73 2.79
Mechanical Engineering 66 6.62 5.83 0.79
Education 65 6.52 5.13 1.39
Materials Technology 59 5.92 4.92 0.99
Agriculture & Forestry 59 5.92 3.22 2.7
General Engineering 57 5.72 5.13 0.59
Geology 54 5.42 4.62 0.79
Psychology 51 5.12 2.41 2.7
Electrical & Electronic Engineering 47 4.71 6.93 -2.22
Civil Engineering 46 4.61 3.42 1.2
Linguistics 45 4.51 2.91 1.6
Librarianship & Information Management 45 4.51 2.71 1.8
Chemical Engineering 40 4.01 3.02 1
History 39 3.91 3.12 0.8
Sociology 37 3.71 2.31 1.4
Aeronautical & Manufacturing Engineering 31 3.11 3.72 -0.61
Robotics 30 3.01 4.12 -1.11
Economics 30 3.01 3.02 -0.01
Business & Management Studies 23 2.31 1.11 1.2
Communication & Media Studies 22 2.21 2.51 -0.31
English 20 2.01 1.01 1
Politics 20 2.01 1.21 0.8
Classics & Ancient History 19 1.91 2.11 -0.2
Anthropology 17 1.71 0.9 0.8
Accounting & Finance 16 1.6 1.11 0.5
Food Science 15 1.5 0.7 0.8
Philosophy 15 1.5 1.01 0.5
Law 15 1.5 0.9 0.6
Art & Design 13 1.3 1.51 -0.2
History of Art, Architecture & Design 12 1.2 1.11 0.1
Music 12 1.2 0.7 0.5
Information and computing sciences 12 1.2 0 1.2
Pharmacology & Pharmacy 11 1.1 1.91 -0.81
Social Policy 11 1.1 1.41 -0.3
Anatomy & Physiology 10 1 1.31 -0.3
Criminology 10 1 0.8 0.2
Sports Science 9 0.9 0.4 0.5
Social Work 9 0.9 0.6 0.3
German 9 0.9 1.51 -0.6
East & South Asian Studies 9 0.9 0.3 0.6
Architecture 8 0.8 0.7 0.1
Biomedical and clinical sciences 7 0.7 0 0.7
Middle Eastern and African Studies 7 0.7 0.7 -0
Veterinary Medicine 7 0.7 0.6 0.1
French 7 0.7 0.6 0.1
Theology & Religious Studies 7 0.7 1.21 -0.5
Earth sciences 6 0.6 0 0.6
Biological sciences 6 0.6 0 0.6
Health sciences 6 0.6 0 0.6
Complementary Medicine 6 0.6 0.5 0.1
Physical sciences 6 0.6 0 0.6
Built environment and design 5 0.5 0 0.5
Engineering 5 0.5 0 0.5
Language, communication and culture 5 0.5 0 0.5
Town & Country Planning and Landscape Design 5 0.5 0.6 -0.1
Ophthalmics 5 0.5 0.6 -0.1
American Studies 5 0.5 0.6 -0.1
Dentistry 5 0.5 0.6 -0.1
Marketing 5 0.5 0.8 -0.3
Counselling 4 0.4 0.2 0.2
History, heritage and archaeology 4 0.4 0 0.4
Environmental sciences 4 0.4 0 0.4
Iberian Languages/Hispanic Studies 4 0.4 0.5 -0.1
Commerce, management, tourism and services 4 0.4 0 0.4
Chemical sciences 4 0.4 0 0.4
Nursing 4 0.4 0.4 -0
Human society 4 0.4 0 0.4
Economics.1 3 0.3 0 0.3
Education.1 3 0.3 0 0.3
Physiotherapy 3 0.3 0.2 0.1
Mathematical sciences 2 0.2 0 0.2
Psychology.1 2 0.2 0 0.2
Indigenous studies 2 0.2 0 0.2
Russian & East European Languages 2 0.2 0.2 -0
Land & Property Management 2 0.2 0.6 -0.4
Fashion 1 0.1 0.2 -0.1
Creative arts and writing 1 0.1 0 0.1
Law and legal studies 1 0.1 0 0.1
Philosophy and religious studies 1 0.1 0 0.1
Youth Work 1 0.1 0.4 -0.3
Hospitality, Leisure, Recreation & Tourism 1 0.1 0.2 -0.1
02 Physical Sciences 0 0 3.62 -3.62
01 Mathematical Sciences 0 0 2.41 -2.41
HEALTH SCIENCES 0 0 0.1 -0.1
OTHER STUDIES IN NATURAL SCIENCES AND ENGINEERING 0 0 0.2 -0.2
LIFE SCIENCES RESEARCH RELATED TO HUMAN HEALTH AND DISEASE 0 0 0.2 -0.2
PSYCHOLOGY 0 0 0.2 -0.2
EVOLUTION AND ECOLOGY 0 0 0.2 -0.2
MICROBIOLOGY 0 0 0.1 -0.1
04 Earth Sciences 0 0 2.21 -2.21
03 Chemical Sciences 0 0 1.01 -1.01
17 Psychology and Cognitive Sciences 0 0 0.3 -0.3
05 Environmental Sciences 0 0 2.11 -2.11
15 Commerce, Management, Tourism and Services 0 0 0.2 -0.2
HYDROLOGY 0 0 0.1 -0.1
22 Philosophy and Religious Studies 0 0 0.3 -0.3
21 History and Archaeology 0 0 0.3 -0.3
20 Language, Communication and Culture 0 0 0.5 -0.5
19 Studies in Creative Arts and Writing 0 0 0.3 -0.3
18 Law and Legal Studies 0 0 0.1 -0.1
16 Studies in Human Society 0 0 0.4 -0.4
14 Economics 0 0 0.2 -0.2
06 Biological Sciences 0 0 3.42 -3.42
13 Education 0 0 0.9 -0.9
12 Built Environment and Design 0 0 0.2 -0.2
11 Medical and Health Sciences 0 0 2.41 -2.41
10 Technology 0 0 2.61 -2.61
09 Engineering 0 0 2.31 -2.31
08 Information and Computing Sciences 0 0 4.52 -4.52
07 Agricultural and Veterinary Sciences 0 0 1.01 -1.01
FLUID MECHANICS 0 0 0.1 -0.1
BIOMEDICAL ENGINEERING 0 0 0.1 -0.1
DESIGN AND MANUFACTURING 0 0 0.1 -0.1
INDUSTRIAL ENGINEERING 0 0 0.1 -0.1
ENVIRONMENTAL ENGINEERING 0 0 0.1 -0.1
INFORMATION TECHNOLOGY 0 0 0.2 -0.2
ARTIFICIAL INTELLIGENCE 0 0 0.2 -0.2
PHYSICAL GEOGRAPHY 0 0 0.1 -0.1
EARTH SCIENCE 0 0 0.1 -0.1
CONDENSED MATTERPHYSICS 0 0 0.1 -0.1
ASTRONOMY AND ASTROPHYSICS 0 0 0.3 -0.3
THEORETICAL PHYSICS AND CHEMISTRY 0 0 0.1 -0.1
PHYSICS 0 0 0.1 -0.1
STATISTICS AND PROBABILITY 0 0 0.4 -0.4
APPLIED MATHEMATICS 0 0 0.1 -0.1

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academic_field_work

Professional developer

In this section we investigate the relationship between RSEs/RSDs and their own experience in software development Understandably, we expect them having several years of software development experience. However, as shown in previous years, it is not necessarily reflected upon their own feeling of being considered as professional.

Questions in this section:

  • Do you consider yourself a professional software developer? (Yes/No)
  • How many years of software development experience do you have? (integer)

How many professional developers?

Professional developer for World Count Percentage Percentage in 2018 Difference with previous year
Yes 555 57.81 53.37 4.44
No 405 42.19 46.63 -4.44

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proportion-professional-developer

Years of software development experience

How many years of software development experience for World (without 95 percentile) Results in 2022 Results in 2018
count 173 52
mean 6.43 9.21
std 3.7 5.25
min 0 1
25% 3 5
50% 6 10
75% 10 10.75
max 14 24

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density-years-professional-developer

How time is spent

RSE/RSE are supposed to be an hybrid role, compared to pure software developer. They bring a knowledge from their field but also are developing software. To capture this different tasks they may do during their work, we asked them how they spend their time but also how they wish to spend their time to investigate any difference between what they do and what they want to do.

How to read the plots

Respondents were asked how much time is spent in a particular activity using a Likert scale from from 1 (None at all) to 10 (All my time).

The same questions asked them how much time they wanted to spend on these activities. With that it was possible to see if discrepancies exist between what they actually do and what they want to do.

To read the results, when the bars shift to the right (in blue), it means they reported positive values (from 6 to 10); when the bars are on the left (in red), it means they reported more negative values (relative to the scale). Each bar has a number that represents the percentage of participants that selected that value. The total bar represents 100%.

To calculate the difference between what they want and what they do, we subtract the answers to the the time that they wished to have spent from the the answer to actual time spent. It is therefore possible to understand the results as:

  1. The result is zero: The time spent matches, they do as much as they want.
  2. The result is negative: They wish to spend less time to do that activity
  3. The result is positive: They wish to spend more time to do that activity

Questions in this section

All questions were asked on a 1 to 10 Likert scale.

  • On average, how much of your time is spent developing software?
  • On average, how much of your time is spent on research?
  • On average, how much of your time is spent on management?
  • On average, how much of your time is spent on teaching?
  • On average, how much of your time is spent on other activities?

how-time-is-spent

Previous employment

Several questions were about the participants’ previous job. The idea is to collect insights of their career path and understand what their motivations are to be an RSE.

We also asked the participants to rank the reasons why they chose their actual position among 8 different ones:

  • Desire to work in a research environment
  • Freedom to choose own working practices
  • Desire to advance research
  • I want to learn new skills
  • Opportunity to develop software
  • Flexible working hours
  • Ability to work across disciplines
  • Opportunity for career advancement
  • The salary

Questions in this section

  • Where was your previous job based? (single choice)
  • Rank the following factors dependent on how strongly they influenced your decision to accept your current position (ranking)

Where the previous job was based

Where the previous job was based for World Count Percentage Percentage in 2018 Difference with previous year
University 450 50.45 53.58 -3.13
Private company 182 20.4 14.32 6.08
National laboratory 53 5.94 3.81 2.13
This is my first job 45 5.04 nan nan
Government 43 4.82 3.81 1.01
Other 35 3.92 7.74 -3.81
Helmholtz Association of German Research Centres 29 3.25 3.58 -0.33
Non-profit organization 27 3.03 2.31 0.72
Max Planck Society 14 1.57 1.04 0.53
NGO 4 0.45 0.12 0.33
University of Applied Sciences 4 0.45 0.58 -0.13
Leibniz Association 4 0.45 1.27 -0.82
Fraunhofer Society 2 0.22 1.15 -0.93

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where-previous-job-based

What were the reasons to choose the current job

Top reason to choose current job for World Count Percentage Percentage in 2018 Difference with previous year
Desire to work in a research environment 208 24.73 25.22 -0.49
Desire to advance research 156 18.55 19 -0.45
Freedom to choose own working practices 154 18.31 16.89 1.42
Opportunity to develop software 110 13.08 11.44 1.64
Opportunity for career advancement 54 6.42 6.56 -0.13
I want to learn new skills 54 6.42 9.56 -3.13
Ability to work across disciplines 45 5.35 3.11 2.24
Flexible working hours 36 4.28 4.33 -0.05
The salary 24 2.85 3.89 -1.04

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reasons-to-choose-current-job

Collaboration and training

Questions in this section:

  • Who uses the code that you write? (one choice)
  • Do you always work with the same researchers, or do you regularly change the researchers you work with? (one choice)
  • Are you part of a dedicated research software group within your institution? (yes-no)
  • How many software projects are you currently involved in? (numeric)
  • How many people who develop software typically work on your projects? (numeric)
  • On average, how many times a year do you take part in providing training? (numeric)
  • What training programs are you involved with? (free text)

Developing code for others

Developing code for others for World Count Percentage Percentage in 2018 Difference with previous year
0 - Mostly me 72 7.67 6.83 0.83
1 105 11.18 13.47 -2.29
2 141 15.02 17.69 -2.67
3 187 19.91 18.19 1.72
4 187 19.91 17.89 2.03
5 - Mostly other people 247 26.3 25.93 0.37

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developing-code-for-others

Working with same researchers

Working with same researchers for World Count Percentage Percentage in 2018 Difference with previous year
Different researchers, same research group 133 15.63 17.13 -1.5
Regularly change researcher(s) 390 45.83 38.3 7.53
Same researcher(s) 328 38.54 44.57 -6.03

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working-with-same-researchers

Part of dedicated group

Member of a dedicated group for World Count Percentage Percentage in 2018 Difference with previous year
No 402 47.24 49.78 -2.54
Yes 449 52.76 50.22 2.54

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member-of-a-dedicated-group

Number of projects

Number of software projects for World Count Percentage Percentage in 2018 Difference with previous year
0 17 2.04 1.53 0.5
1 133 15.93 16.27 -0.35
2 218 26.11 25.83 0.28
3 210 25.15 25 0.15
4 85 10.18 10.73 -0.55
5 88 10.54 10.5 0.04
6 17 2.04 3.54 -1.5
7 17 2.04 0.94 1.09
8 10 1.2 1.18 0.02
10 17 2.04 2.12 -0.09
13 1 0.12 nan nan
15 22 2.63 0.12 2.52

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number-of-software-projects

Number of software developers per projects for World Count Percentage Percentage in 2018 Difference with previous year
0 26 3.29 2.01 1.28
0.5 1 0.13 nan nan
1 193 24.4 31.29 -6.89
1.2 1 0.13 nan nan
1.5 2 0.25 0.24 0.02
2 231 29.2 29.75 -0.55
2.5 1 0.13 0.12 0.01
3 160 20.23 15.82 4.41
4 43 5.44 6.02 -0.59
5 56 7.08 6.02 1.06
6 9 1.14 2.48 -1.34
7 10 1.26 0.71 0.56
8 9 1.14 0.83 0.31
9 1 0.13 0.24 -0.11
10 24 3.03 2.01 1.03
12 2 0.25 0.24 0.02
15 5 0.63 0.47 0.16
18 1 0.13 nan nan
20 8 1.01 0.47 0.54
30 2 0.25 0.47 -0.22
32 1 0.13 nan nan
50 1 0.13 0.12 0.01
100 3 0.38 0.12 0.26
200 1 0.13 nan nan

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number-of-software-developers-per-projects

Training

Number of time per year providing training for World (without 95 percentile) Results in 2022 Results in 2018
count 197 38
mean 1.8 2.08
std 2.19 2.71
min 0 0
25% 0 0
50% 1 1
75% 3 3
max 10 12

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training-frequency

training-name-wordcloud

Publications and citations

RSEs is an hybrid role between a researcher and a software developer. We investigated both of these aspects concerning publication and dissemination of their work, one on the traditional aspect of it (publications and conference).

One essential aspect of career in academia is the publications and the conferences to gain recognition. However, the role of RSE being less about writing articles than creating the infrastructure and the software for the article to exist, there is some fear that they will fail to have recognition through the papers and conferences.

Questions in the section:

  • In general, when your software contributes to a paper, are you acknowledged in that paper? (one choice)
  • Have you presented your software work at a conference or workshop? (yes-no)
  • At which conference(s)/workshop(s) have you presented your software work? (free text)

Acknowledgment in paper

Acknowledgment in paper for World Count Percentage Percentage in 2018 Difference with previous year
Not mentioned at all 126 16.09 20.85 -4.76
Acknowledged in the main text 60 7.66 8.07 -0.41
Acknowledged in acknowledgements section 128 16.35 18.39 -2.04
Named as co-author 426 54.41 47.09 7.32
Named as main author 43 5.49 5.61 -0.11

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acknowledgment-in-paper

Participation in conferences

Did you participate in conference for World Count Percentage Percentage in 2018 Difference with previous year
Yes 464 57.71 56.01 1.7
No 340 42.29 43.99 -1.7

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did-you-participate-in-conference

Conference name

conference-name-wordcloud

Open source and DOI

RSEs is an hybrid role between a researcher and a software developer. We investigated both of these aspects concerning publication and dissemination of their work, one on the traditional aspect of it (publications and conference) and, as developed here, on the more software aspect (open source and DOI).

We asked the participants if they have ever released their work under open source licence but also questions about the referencing system. We asked them how often they reference software, and if they use DOI for it, and which tools for it.

We also asked them if they have an ORCID ID, a system that gives a unique reference ID for the researcher.

Questions in this section:

  • How often do you use an open-source licence for your software? (likert scale)
  • How often do you reference software directly or the papers describing the software? (likert scale)
  • How often do you associate your software with a Digital Object Identifier (DOI)? (likert scale)
  • Which tools do you use to mint a DOI (e.g. local library, Zenodo)? (free text)
  • Do you have an ORCID ID? (yes-no)

Open source use

Open source use for World Count Percentage Percentage in 2018 Difference with previous year
1 (None at all) nan nan nan nan
2 24 2.83 3.92 -1.09
3 29 3.42 4.14 -0.72
4 13 1.53 2.24 -0.71
5 40 4.72 5.04 -0.32
6 25 2.95 3.02 -0.08
7 37 4.36 5.49 -1.12
8 92 10.85 8.85 2
9 102 12.03 11.87 0.16
10 (All the time) 417 49.17 43.45 5.73

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open-source-use

Referencing software

Citation of software for World Count Percentage Percentage in 2018 Difference with previous year
1 (None at all) nan nan nan nan
2 27 3.82 6.57 -2.75
3 32 4.53 5.89 -1.36
4 28 3.96 4.3 -0.34
5 46 6.51 9.63 -3.12
6 27 3.82 5.1 -1.28
7 66 9.34 6.34 2.99
8 98 13.86 9.74 4.12
9 70 9.9 5.78 4.13
10 (All the time) 253 35.79 27.63 8.15

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citation-of-software

Use of Digital Object Identifier (DOI)

Use of Digital Object Identifier for World Count Percentage Percentage in 2018 Difference with previous year
1 (None at all) nan nan nan nan
2 59 8.05 6.68 1.37
3 54 7.37 5.44 1.93
4 29 3.96 3.4 0.56
5 66 9 7.36 1.64
6 35 4.77 3.62 1.15
7 43 5.87 3.62 2.24
8 50 6.82 3.06 3.76
9 34 4.64 2.72 1.92
10 (All the time) 88 12.01 6.68 5.32

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use-of-digital-object-identifier

Tools used for DOI

tool-used-for-doi-wordcloud

ORCID

Using ORCID for World Count Percentage Percentage in 2018 Difference with previous year
Yes 696 84.47 63.36 21.11
No 99 12.01 14.84 -2.83

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using-orcid

Good practices

This section comprises sections that focus on the technical and development aspects of the RSEs’ work. They aim to understand good practices in developing software.

We chose two broad measures to provide an insight into sustainability: the bus factor and technical hand over planning.

  • The bus factor is a measure of the number of developers who understand a specific software project and could, with only a cursory review of the project, maintain or extend the code. A project with a bus factor of 1 is completely reliant on only one developer. If this developer finds new employment, becomes ill or is hit by the titular bus, then the project will fail. A high bus factor provides some confidence that the project can be sustained even if a developer leaves.

  • A technical hand over plan is used to introduce a new developer to a software project. These plans cover basic information, such as the license and location of the software, a repository, a description of the software architecture, a summary of development plans and any other information that a new developer would need to understand the software. A project that has written (and maintained) a technical hand over plan can withstand the departure of a developer, even a key developer, significantly better than one without such a plan.

Developing software requires a set of good practices to ensure the quality of the subsequent analysis as well as the robustness of the developed software, to name a few of important aspects. We wanted to see if the implementation of some simple but essential good practices were a reality beside the bus factor and technical hand over planning.

When developing software, version control and testing can be seen as tool to enhance the quality of the developed software, especially considering the importance of code review and sharing in public funded places such as academia.

For testing, we asked the participants to choose any of the following testing methods:

  • Automated testing with continuous integration
  • Test engineers conduct testing
  • Developers conduct own testing
  • No formal testing but users provide feedback
  • No formal testing

Test engineers conducting testing is the most robust testing method but may not be possible in smaller projects while no formal testing should not occur in any ideal scenario, regardless of the size of the project.

We also asked the participants if they use any version control tools through a list of choice. And finally we asked them which repository they are currently using for their most important project.

Bus factor

Bus factor for World Count Percentage Percentage in 2018 Difference with previous year
-1 1 0.12 nan nan
0 31 3.71 3.51 0.2
1 441 52.81 52.83 -0.02
1.3 1 0.12 nan nan
1.5 5 0.6 0.23 0.37
2 221 26.47 28.12 -1.65
3 70 8.38 8.05 0.33
3.5 1 0.12 nan nan
4 18 2.16 3.29 -1.13
5 21 2.51 1.47 1.04
6 4 0.48 0.68 -0.2
7 1 0.12 0.45 -0.33
8 2 0.24 0.11 0.13
10 8 0.96 0.34 0.62
18 1 0.12 nan nan
20 2 0.24 0.11 0.13
50 2 0.24 0.11 0.13
100 2 0.24 nan nan
1000 1 0.12 nan nan
1e+10 1 0.12 nan nan
1e+20 1 0.12 nan nan

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bus-factor

Presence of transition plan

Presence of transition plan for World Count Percentage Percentage in 2018 Difference with previous year
Yes 145 17.12 18.25 -1.13
No 702 82.88 81.75 1.13

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presence-of-transition-plan

Use of version control

Use of version control for World Count Percentage Percentage in 2018 Difference with previous year
Git 814 81.64 82.81 -1.17
SVN 70 7.02 22.41 -15.39
None 30 3.01 3.82 -0.81
Mercurial 10 1 5.53 -4.52
CVS 9 0.9 4.12 -3.22

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use-of-version-control

Testing strategies

Testing strategies for World Count Percentage Percentage in 2018 Difference with previous year
No formal testing 111 11.13 10.85 0.28
No formal testing but users provide feedback 238 23.87 31.06 -7.18
The developers do their own testing 599 60.08 77.99 -17.91
Test engineers conduct testing 34 3.41 4.82 -1.41
Automated testing with continuous integration 502 50.35 0 50.35
Don’t know 10 1 0 1

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testing-strategies

Repository

repository-wordcloud

Tools and programming languages

On technical details we wanted to know which of the programming languages are mostly used by the RSEs. We give them a multi-choice list inspired by the results published by Stackoverflow.

We also wanted to know which operating system they use for work.

Questions in this section:

  • Which operating system do you primarily use for development? (one choice)
  • What programming languages do you use at work? Please select all that apply. (multiple choice)

Programming languages

Programming languages for World Count Percentage Percentage in 2018 Difference with previous year
Python 708 71.01 70.65 0.36
C++ 301 30.19 34.87 -4.68
R 269 26.98 26.93 0.05
JavaScript 246 24.67 26.73 -2.06
SQL 220 22.07 26.73 -4.67
C 193 19.36 28.64 -9.29
Fortran 170 17.05 19.6 -2.55
Java 143 14.34 20.1 -5.76
Matlab 130 13.04 16.88 -3.85
other. What programming languages do you use at work? Please select all that apply. 111 11.13 0 11.13
PHP 77 7.72 8.54 -0.82
Perl 68 6.82 9.05 -2.22
Julia 65 6.52 3.52 3
TypeScript 63 6.32 3.22 3.1
C# 41 4.11 7.34 -3.22
Ruby 29 2.91 2.91 -0.01
Rust 27 2.71 1.81 0.9
Go 21 2.11 2.11 -0
Scala 14 1.4 1.61 -0.2
Lua 13 1.3 1.21 0.1
Assembly 13 1.3 2.01 -0.71
Groovy 12 1.2 1.71 -0.5
Haskell 9 0.9 0.5 0.4
Common Lisp 9 0.9 0.5 0.4
VBA 9 0.9 2.71 -1.81
Objective-C 7 0.7 0.4 0.3
Swift 7 0.7 0.5 0.2
VB.NET 6 0.6 0.9 -0.3
Visual Basic 6 0.6 1.31 -0.7
F# 4 0.4 0.1 0.3
Dart 3 0.3 0 0.3
Clojure 2 0.2 0.4 -0.2
CoffeeScript 1 0.1 0.7 -0.6
Elixir 1 0.1 0.2 -0.1
Erlang 0 0 0.3 -0.3

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programming-languages

Operating systems

Operating systems for World Count Percentage Percentage in 2018 Difference with previous year
GNU/Linux 509 63.15 61.55 1.6
macOS 169 20.97 nan nan
Windows 120 14.89 20.52 -5.63
Other 8 0.99 1.06 -0.06

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operating-systems

Job satisfaction

Job satisfaction is an essential pulse to take about a community’s health. It helps to track the evolution and the current state of the RSEs within their role and to catch any sign of structural or organisational dysfunction that are translated into well-being. There are a lot of different metrics to measure the quality of a job on a personal and psychological level [1]. Several models exist to understand the link between different factors of job satisfaction and turnover intention [2]–[6]. Turnover intention is an important measure that is highly associated with the risk of employees leaving the organisation [3]. Job satisfaction is important in retaining RSEs. Perceived employability provides information on how workers values their own skills in regard of the market. To measure the different attitudes toward the RSE role, we used scales that have been created in [5], [6], [7], [8]. These are Likert scale [7], which are 5 point ordinal scales graduated from Strongly disagree to Strongly agree. Each scale is composed of several so called items (i.e. questions) that each measure one attitude.

Beside these specific concepts we asked more general question about their satisfaction in their current position and their satisfaction with their career in general with a range of answers from 0 (not at all satisfied) to 10 (completely satisfied).

The specific questions about their job satisfaction reflect, in general, the same opinion as the two more generic questions. However, the granularity helps to identify a couple of issues that would not appears with generic questions:

  • Recognition: These questions ask if the RSEs feel that they receive enough information about their work and their performance.
  • The turnover intention: These questions aim to measure the desire to quit their current position.
  • The perceived employability: This concept is linked to the previous one. People may not have the intention to leave their jobs, not because they like it, but because they fear they are not employable.
  • The possibility of progression: This question aims to study the possibility of evolution for the RSEs, if information is available and if they see a possibility of evolution within their current career. This is the only questions that clearly received negative answers.

Questions in this section:

All questions were asked in a Likert scale.

  • In general, how satisfied are you with your current position?
  • In general, how satisfied are you with your career?
  • Do you feel that your contribution to research is recognised by your supervisor/line manager?
  • Do you feel that your contribution to research is recognised by the researchers you work with?
  • Do you feel that your contribution to research is recognised by your institution?
  • How often do you consider leaving your job?
  • I would accept another job at the same compensation level if I was offered it
  • It would not be very difficult for me to get an equivalent job in a different institution
  • My experience is in demand on the labour market
  • It is likely that I will gain a promotion within my current group
  • The process I have to complete to gain a promotion is clear and understandable
  • There are many opportunities within my chosen career plan
  • It is likely that my next position will be an Research Software Engineer / Research

/References/

  1. B. Aziri, “Job satisfaction: A literature review,” vol. 3, no. 4, pp. 77–86.
  2. N. De Cuyper, S. Mauno, U. Kinnunen, and A. Mkikangas, “The role of job resources in the relation between perceived employability and turnover intention: A prospective two-sample study,” vol. 78, no. 2, pp. 253–263.
  3. A. B. Bakker and E. Demerouti, “The job demands-resources model: State of the art,” vol. 22, no. 3, pp. 309–328.
  4. G. H. L. Cheng and D. K. S. Chan, “Who Suffers More from Job Insecurity? A Meta-Analytic Review.” vol. 57, no. 2, p. 272.
  5. E. R. Thompson and F. T. Phua, “A brief index of affective job satisfaction,” vol. 37, no. 3, pp. 275–307.
  6. L. Greenhalgh and Z. Rosenblatt, “Job insecurity: Toward conceptual clarity,” pp. 438–448.
  7. R. Likert, “A technique for the measurement of attitudes.” vol. 22, no. 140, p. 55.

General satisfaction

general-satisfaction

Recognition

recognition

Turn-over intention

consider-leaving-job

would-accept-another-job-at-same-compensation

Perceived employability

perceived-employability

Progression in the current role

progression-in-the-current-role

Research software engineer

In this section we wanted to know if the participants are member or not of local organisations and if they are interested to participate to conference specific for RSE.

We also asked them to tell them which skills is important as RSE and which they and to acquire for their current role.

Questions in this section

  • Are you a member of an association of Research Software Developers (e.g. AUS-RSE, CANARIE, DE-RSE, NZ_RSE, UK RSE, …)? (yes-no)
  • Would you be interested in joining such an organisation? (yes-no)
  • What is important for such an organisation? (multiple choice)
  • Would you like to attend a conference about software development in academia? (yes-no)
  • How did you learn the skills you need to become an Research Software Engineer / Research Software Developer? (free text)
  • What three skills would you like to acquire or improve to help your work as a Research Software Engineer/ Research Software Developer? The skills can be technical and non-technical (free text)

RSE member

RSE Member for World Count Percentage Percentage in 2018 Difference with previous year
Yes 331 42.71 21.12 21.59
No 444 57.29 78.88 -21.59

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rse-member

Joining a RSE/RSD association

Joining a RSE/RSD association for World Count Percentage Percentage in 2018 Difference with previous year
Yes 231 64.53 70.66 -6.14
No 127 35.47 29.34 6.14

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joining-a-rse-rsd-association

What is important for such an organisation

What is important for such an organisation for World Count Percentage Percentage in 2018 Difference with previous year
Networking 492 49.35 27.44 21.91
Research software standards and interoperability definition 359 36.01 24.02 11.99
Job opportunities 319 32 20.4 11.59
Training 313 31.39 22.11 9.28
Research collaborations 274 27.48 21.71 5.77
other. What would you hope to get out of such an organisation (check all that apply)? 48 4.81 0 4.81

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what-is-important-for-such-an-organisation

Attending a national conference of RSE/RSD

Attending a national conference of RSE/RSD for World Count Percentage Percentage in 2018 Difference with previous year
Yes 628 86.62 81.42 5.2
No 97 13.38 18.58 -5.2

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attending-a-national-conference-of-rse-rsd

Learning skills for RSE/RSD

learning-skills-rse-rsd-wordcloud

Which skills to improve

which-skills-to-improve-rse-rsd-wordcloud