Link Search Menu Expand Document

Germany

  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)
  • Which professional qualification do you hold? (free text)

Levels of education

Highest level of education for Germany Count Percentage Percentage in 2017 Difference with previous year
Master degree 169 50.9036 43.0769 7.82669
Doctorate 133 40.0602 48.3077 -8.24745
Undergraduate degree 19 5.72289 4.61538 1.10751
Final secondary-school examinations, general qualification for university entrance 7 2.10843 1.53846 0.569972
Other 4 1.20482 2.15385 -0.949027

Download CSV

2021-08-04T21:03:41.587138 image/svg+xml Matplotlib v3.4.2, https://matplotlib.org/ 0 10 20 30 40 50 Other Final secondary-school examinations, general qualification for university entrance Undergraduate degree Doctorate Master degree 1% 2% 6% 40% 51% Highest level of education, Germany −5 0 5 Δ

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 Germany Count Percentage Percentage in 2017 Difference with previous year
Computer Science 85 25.8359 16.6154 9.22048
Physics and Astronomy 75 22.7964 25.5385 -2.74211
Geography & Environmental Sciences 25 7.59878 7.07692 0.521861
Biological Sciences 24 7.29483 11.3846 -4.08978
Mathematics 24 7.29483 5.23077 2.06406
Electrical & Electronic Engineering 18 5.47112 2.46154 3.00959
Mechanical Engineering 11 3.34347 1.53846 1.805
Geology 9 2.73556 1.84615 0.889408
Materials Technology 6 1.82371 nan nan
Chemical Engineering 5 1.51976 1.23077 0.288988
History 5 1.51976 0.923077 0.59668
General Engineering 5 1.51976 0.923077 0.59668
Civil Engineering 4 1.21581 0.615385 0.600421
Philosophy 3 0.911854 0.615385 0.296469
Economics 3 0.911854 0.307692 0.604162
Librarianship & Information Management 3 0.911854 0.923077 -0.0112228
German 3 0.911854 0.923077 -0.0112228
Chemistry 3 0.911854 1.84615 -0.9343
Classics & Ancient History 2 0.607903 0.923077 -0.315174
Robotics 2 0.607903 nan nan
Psychology 2 0.607903 2.46154 -1.85364
Linguistics 2 0.607903 0.307692 0.30021
Communication & Media Studies 1 0.303951 0.615385 -0.311433
English 1 0.303951 0.307692 -0.00374094
Agriculture & Forestry 1 0.303951 0.923077 -0.619126
Art & Design 1 0.303951 nan nan
Medicine 1 0.303951 0.307692 -0.00374094
Education 1 0.303951 nan nan
Aeronautical & Manufacturing Engineering 1 0.303951 0.615385 -0.311433
Business & Management Studies 1 0.303951 nan nan
Criminology 1 0.303951 nan nan
Theology & Religious Studies 1 0.303951 nan nan

Download CSV

2021-08-04T21:03:47.324635 image/svg+xml Matplotlib v3.4.2, https://matplotlib.org/ 0 5 10 15 20 25 Theology & Religious Studies Criminology Business & Management Studies Aeronautical & Manufacturing Engineering Education Medicine Art & Design Agriculture & Forestry English Communication & Media Studies Linguistics Psychology Robotics Classics & Ancient History Chemistry German Librarianship & Information Management Economics Philosophy Civil Engineering General Engineering History Chemical Engineering Materials Technology Geology Mechanical Engineering Electrical & Electronic Engineering Mathematics Biological Sciences Geography & Environmental Sciences Physics and Astronomy Computer Science 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 1% 1% 1% 1% 1% 1% 1% 1% 1% 1% 2% 2% 2% 2% 3% 3% 5% 7% 7% 8% 23% 26% Field of education, Germany 0 5 Δ 2021-08-04T21:03:49.490853 image/svg+xml Matplotlib v3.4.2, https://matplotlib.org/ Professional qualification, Germany

Academic field of work

field of work for Germany Count Percentage Percentage in 2017 Difference with previous year
Computer Science 138 41.4414 34.7692 6.67221
Physics and Astronomy 81 24.3243 27.3846 -3.06029
Geography & Environmental Sciences 56 16.8168 20.3077 -3.49088
Biological Sciences 53 15.9159 26.7692 -10.8533
Electrical & Electronic Engineering 40 12.012 3.69231 8.3197
Mathematics 36 10.8108 9.23077 1.58004
Mechanical Engineering 30 9.00901 2.15385 6.85516
Robotics 27 8.10811 2.76923 5.33888
General Engineering 23 6.90691 3.07692 3.82998
Geology 23 6.90691 7.38462 -0.477708
Materials Technology 22 6.60661 0.307692 6.29891
Aeronautical & Manufacturing Engineering 19 5.70571 0.923077 4.78263
Chemistry 16 4.8048 6.15385 -1.34904
Medicine 16 4.8048 5.23077 -0.425964
Education 15 4.5045 5.23077 -0.726265
Librarianship & Information Management 14 4.2042 5.53846 -1.33426
German 12 3.6036 1.53846 2.06514
History 12 3.6036 2.76923 0.834373
Agriculture & Forestry 12 3.6036 2.15385 1.44976
Communication & Media Studies 10 3.003 0.923077 2.07993
Civil Engineering 10 3.003 0.923077 2.07993
Linguistics 9 2.7027 3.07692 -0.37422
Classics & Ancient History 9 2.7027 3.07692 -0.37422
Economics 8 2.4024 2.76923 -0.366828
Chemical Engineering 8 2.4024 1.84615 0.556249
Theology & Religious Studies 7 2.1021 1.53846 0.563641
Law 6 1.8018 0.615385 1.18642
Psychology 6 1.8018 2.76923 -0.967429
Philosophy 5 1.5015 0.615385 0.886117
Politics 5 1.5015 0.307692 1.19381
Art & Design 4 1.2012 0.615385 0.585817
Pharmacology & Pharmacy 4 1.2012 0.923077 0.278124
History of Art, Architecture & Design 4 1.2012 0.923077 0.278124
Business & Management Studies 4 1.2012 0.615385 0.585817
Sociology 3 0.900901 nan nan
Marketing 3 0.900901 0.307692 0.593209
Music 3 0.900901 0.307692 0.593209
Accounting & Finance 3 0.900901 0.923077 -0.022176
Food Science 3 0.900901 0.615385 0.285516
American Studies 3 0.900901 nan nan
Criminology 3 0.900901 nan nan
Land & Property Management 2 0.600601 nan nan
Veterinary Medicine 2 0.600601 0.615385 -0.014784
English 2 0.600601 nan nan
Middle Eastern and African Studies 2 0.600601 0.307692 0.292908
Social Work 2 0.600601 nan nan
Anthropology 2 0.600601 0.307692 0.292908
Architecture 1 0.3003 0.307692 -0.00739201
Town & Country Planning and Landscape Design 1 0.3003 0.307692 -0.00739201
Sports Science 1 0.3003 0.307692 -0.00739201
Anatomy & Physiology 1 0.3003 1.23077 -0.930469
Social Policy 1 0.3003 nan nan
Russian & East European Languages 1 0.3003 nan nan
Counselling 1 0.3003 0.615385 -0.315084
Complementary Medicine 1 0.3003 nan nan
Physiotherapy 1 0.3003 nan nan
Iberian Languages/Hispanic Studies 1 0.3003 0.307692 -0.00739201
Dentistry 1 0.3003 nan nan
Ophthalmics 1 0.3003 nan nan
Nursing 1 0.3003 0.307692 -0.00739201
East & South Asian Studies 1 0.3003 nan nan
Fashion 1 0.3003 nan nan
French 1 0.3003 0.307692 -0.00739201
Hospitality, Leisure, Recreation & Tourism 1 0.3003 nan nan
Youth Work 1 0.3003 nan nan

Download CSV

2021-08-04T21:04:06.398355 image/svg+xml Matplotlib v3.4.2, https://matplotlib.org/ 0 10 20 30 40 Youth Work Hospitality, Leisure, Recreation & Tourism French Fashion East & South Asian Studies Nursing Ophthalmics Dentistry Iberian Languages/Hispanic Studies Physiotherapy Complementary Medicine Counselling Russian & East European Languages Social Policy Anatomy & Physiology Sports Science Town & Country Planning and Landscape Design Architecture Anthropology Social Work Middle Eastern and African Studies English Veterinary Medicine Land & Property Management Criminology American Studies Food Science Accounting & Finance Music Marketing Sociology Business & Management Studies History of Art, Architecture & Design Pharmacology & Pharmacy Art & Design Politics Philosophy Psychology Law Theology & Religious Studies Chemical Engineering Economics Classics & Ancient History Linguistics Civil Engineering Communication & Media Studies Agriculture & Forestry History German Librarianship & Information Management Education Medicine Chemistry Aeronautical & Manufacturing Engineering Materials Technology Geology General Engineering Robotics Mechanical Engineering Mathematics Electrical & Electronic Engineering Biological Sciences Geography & Environmental Sciences Physics and Astronomy Computer Science 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 1% 1% 1% 1% 1% 1% 1% 1% 1% 1% 1% 1% 1% 1% 1% 1% 1% 2% 2% 2% 2% 2% 2% 2% 3% 3% 3% 3% 4% 4% 4% 4% 5% 5% 5% 6% 7% 7% 7% 8% 9% 11% 12% 16% 17% 24% 41% field of work, Germany −10 0 Δ

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 Germany Count Percentage Percentage in 2017 Difference with previous year
Yes 150 47.3186 42.7692 4.54938
No 167 52.6814 57.2308 -4.54938

Download CSV

2021-08-04T21:05:05.356903 image/svg+xml Matplotlib v3.4.2, https://matplotlib.org/ 0 10 20 30 40 50 No Yes 53% 47% Professional developer, Germany −5 0 5 Δ

Years of software development experience

How many years of software development experience for Germany (without 95 percentile) Results in 2018 Results in 2017
count 313 304
mean 9.16374 9.38322
std 6.23297 6.23934
min 0 0
25% 4 5
50% 8 8
75% 13 13
max 28 28

Download CSV

2021-08-04T21:05:06.380979 image/svg+xml Matplotlib v3.4.2, https://matplotlib.org/ 2017 2018 Year 0 5 10 15 20 25 Value 0 10 20 Value 0 10 20 30 40 50 Count Year 2017 2018 How many years of software development experience for Germany (without 95 percentile)

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?
2021-08-04T21:03:27.338326 image/svg+xml Matplotlib v3.4.2, https://matplotlib.org/ Percentage Developing software Research Management Teaching Other activities 6 15 51 11 17 33 26 34 19 22 18 13 22 13 17 11 14 14 12 8 11 12 8 5 18 9 13 Time spent 1 2 3 4 5 6 7 8 9 10 Percentage Developing software Research Management Teaching Other activities 32 29 23 6 28 25 31 9 9 20 21 21 12 13 7 10 8 20 21 7 9 9 14 13 18 13 16 10 5 6 5 Time wish to spent 1 2 3 4 5 6 7 8 9 10 100 90 80 70 60 50 40 30 20 10 0 10 20 30 40 50 60 70 80 90 100 Percentage Developing software Research Management Teaching Other activities 13 10 12 26 8 20 33 23 32 42 42 20 26 9 22 10 17 21 15 7 11 5 7 Difference between time spent and wish -7.0 -6.0 -5.0 -4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 Germany: Difference between time wish to spent and actually spent for each type of activity

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)
  • What were the reasons to choose the current job? (ranking)

Where the previous job was based

Where the previous job was based for Germany Count Percentage Percentage in 2017 Difference with previous year
University 144 46.0064 54.1139 -8.10753
Private Company 58 18.5304 10.443 8.08731
Other 40 12.7796 10.443 2.33651
Helmholtz Association of German Research Centres 31 9.90415 6.96203 2.94213
Leibniz Association 11 3.51438 3.79747 -0.283091
Fraunhofer Society 10 3.19489 nan nan
Max Planck Society 9 2.8754 11.0759 -8.20055
University of Applied Sciences 5 1.59744 0.949367 0.648077
Government 5 1.59744 2.21519 -0.617746

Download CSV

2021-08-04T21:05:19.840009 image/svg+xml Matplotlib v3.4.2, https://matplotlib.org/ 0 10 20 30 40 Government University of Applied Sciences Max Planck Society Fraunhofer Society Leibniz Association Helmholtz Association of German Research Centres Other Private Company University 2% 2% 3% 3% 4% 10% 13% 19% 46% Where the previous job was based, Germany −5 0 5 Δ

What were the reasons to choose the current job

Reasons to choose current job Rank 1 Rank 2 Rank 3 Rank 4 Rank 5 Rank 6 Rank 7 Rank 8
Desire to work in a research environment 24.2236 15.528 14.9533 8.09969 7.1875 nan nan nan
Freedom to choose own working practices 23.913 16.7702 14.9533 9.03427 13.4375 nan nan nan
Desire to advance research 16.4596 12.7329 8.09969 9.34579 7.1875 nan nan nan
I want to learn new skills 12.7329 13.354 15.2648 15.5763 14.6875 nan nan nan
Opportunity to develop software 8.38509 13.9752 14.9533 10.5919 9.6875 nan nan nan
Opportunity for career advancement 4.65839 4.03727 7.47664 7.47664 7.1875 nan nan nan
Ability to work across disciplines 3.41615 11.8012 9.03427 14.9533 12.5 nan nan nan
Flexible working hours 3.41615 9.62733 11.838 17.4455 18.4375 nan nan nan
The salary 2.79503 2.17391 3.42679 7.47664 9.6875 nan nan nan

Download CSV

2021-08-04T21:05:20.614701 image/svg+xml Matplotlib v3.4.2, https://matplotlib.org/ 0 20 40 60 80 100 Ranking of importance Rank 1 Rank 2 Rank 3 Rank 4 Rank 5 Percentage 24 16 15 8 7 24 17 15 9 13 16 13 8 9 7 13 13 15 16 15 8 14 15 11 10 5 7 7 7 12 9 15 12 10 12 17 18 7 10 Reasons to choose current job: Germany 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 Opportunity for career advancement Ability to work across disciplines Flexible working hours The salary

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 software developers 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 (comma separated list, e.g., Software Carpentry, local university training, etc.)? (free text)

Developing code for others

developing code for others for Germany Count Percentage Percentage in 2017 Difference with previous year
0 - Mostly me 30 9.00901 8.30769 0.701317
1 55 16.5165 20.9231 -4.40656
2 66 19.8198 22.4615 -2.64172
3 63 18.9189 16 2.91892
4 56 16.8168 16.6154 0.201432
5 - Mostly other people 63 18.9189 15.6923 3.22661

Download CSV

2021-08-04T21:02:30.745533 image/svg+xml Matplotlib v3.4.2, https://matplotlib.org/ 0 5 10 15 20 5 - Mostly other people 4 3 2 1 0 - Mostly me 19% 17% 19% 20% 17% 9% developing code for others, Germany −2.5 0.0 2.5 Δ

Working with same researchers

Working with same researchers for Germany Count Percentage Percentage in 2017 Difference with previous year
Different researchers, same research group 53 17.9661 nan nan
Regularly change researcher(s) 98 33.2203 35.786 -2.56561
Same researcher(s) 144 48.8136 64.214 -15.4005

Download CSV

2021-08-04T21:02:31.177553 image/svg+xml Matplotlib v3.4.2, https://matplotlib.org/ 0 10 20 30 40 50 Same researcher(s) Regularly change researcher(s) Different researchers, same research group 49% 33% 18% Working with same researchers, Germany −10 0 Δ

Part of dedicated group

member of a dedicated group for Germany Count Percentage Percentage in 2017 Difference with previous year
No 115 38.8514 43.6667 -4.81532
Yes 181 61.1486 56.3333 4.81532

Download CSV

2021-08-04T21:02:31.460197 image/svg+xml Matplotlib v3.4.2, https://matplotlib.org/ 0 10 20 30 40 50 60 Yes No 61% 39% member of a dedicated group, Germany −5 0 5 Δ

Number of projects

Number of software projects for Germany Count Percentage Percentage in 2017 Difference with previous year
0 4 1.42857 1.66667 -0.238095
1 48 17.1429 24.6667 -7.52381
2 84 30 23.3333 6.66667
3 77 27.5 24 3.5
4 32 11.4286 9 2.42857
5 20 7.14286 8.66667 -1.52381
6 7 2.5 2 0.5
7 1 0.357143 0.666667 -0.309524
8 3 1.07143 1.33333 -0.261905
9 1 0.357143 nan nan
10 2 0.714286 3.33333 -2.61905
20 1 0.357143 0.333333 0.0238095

Download CSV

2021-08-04T21:02:31.949717 image/svg+xml Matplotlib v3.4.2, https://matplotlib.org/ 0 5 10 15 20 25 30 20.0 10.0 9.0 8.0 7.0 6.0 5.0 4.0 3.0 2.0 1.0 0.0 0% 1% 0% 1% 0% 2% 7% 11% 28% 30% 17% 1% Number of software projects, Germany −5 0 5 Δ
Number of software developers per projects for Germany Count Percentage
0 6 2.12014
1 82 28.9753
2 96 33.9223
3 48 16.9611
4 21 7.42049
5 14 4.947
6 5 1.76678
7 1 0.353357
8 1 0.353357
10 5 1.76678
15 1 0.353357
20 2 0.706714
30 1 0.353357

Download CSV

2021-08-04T21:02:32.455252 image/svg+xml Matplotlib v3.4.2, https://matplotlib.org/ 0 5 10 15 20 25 30 35 30.0 20.0 15.0 10.0 8.0 7.0 6.0 5.0 4.0 3.0 2.0 1.0 0.0 Number of software developers per projects, Germany

Training

Number of time per year providing training for Germany (without 95 percentile) Results in 2018 Results in 2017
count 281 187
mean 0.869395 1.65791
std 1.13892 1.58011
min 0 0
25% 0 0.415
50% 0 1
75% 1 2
max 4 7

Download CSV

2021-08-04T21:02:33.867471 image/svg+xml Matplotlib v3.4.2, https://matplotlib.org/ 2017 2018 Year 0 1 2 3 4 5 6 7 Value 0 2 4 6 Value 0 20 40 60 80 100 120 140 Count Year 2017 2018 Number of time per year providing training for Germany (without 95 percentile) 2021-08-04T21:02:36.152785 image/svg+xml Matplotlib v3.4.2, https://matplotlib.org/ Number of time per year providing training, Germany

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 Germany Count Percentage
Not mentioned at all 63 21.3559
Acknowledged in the main text 28 9.49153
Acknowledged in acknowledgements section 56 18.9831
Named as co-author 124 42.0339
Named as main author 24 8.13559

Download CSV

2021-08-04T21:03:05.026494 image/svg+xml Matplotlib v3.4.2, https://matplotlib.org/ 0 10 20 30 40 Named as main author Named as co-author Acknowledged in acknowledgements section Acknowledged in the main text Not mentioned at all Acknowledgment in paper, Germany

Participation in conferences

Did you participate in conference for Germany Count Percentage Percentage in 2017 Difference with previous year
Yes 150 54.3478 55.6667 -1.31884
No 126 45.6522 44.3333 1.31884

Download CSV

2021-08-04T21:03:05.277954 image/svg+xml Matplotlib v3.4.2, https://matplotlib.org/ 0 10 20 30 40 50 No Yes 46% 54% Did you participate in conference, Germany −1 0 1 Δ

Conference name

2021-08-04T21:03:08.060598 image/svg+xml Matplotlib v3.4.2, https://matplotlib.org/ Did you participate in conference, Germany

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 Germany Count Percentage Percentage in 2017 Difference with previous year
1 (None at all) nan nan nan nan
2 19 6.41892 6.95187 -0.532953
3 17 5.74324 4.27807 1.46517
4 13 4.39189 1.06952 3.32237
5 15 5.06757 13.369 -8.30142
6 7 2.36486 5.88235 -3.51749
7 14 4.72973 8.02139 -3.29166
8 18 6.08108 8.55615 -2.47507
9 29 9.7973 10.1604 -0.363131
10 (All the time) 89 30.0676 nan nan

Download CSV

2021-08-04T21:01:48.872539 image/svg+xml Matplotlib v3.4.2, https://matplotlib.org/ 0 5 10 15 20 25 30 10 (All the time) 9 8 7 6 5 4 3 2 1 (None at all) 30% 10% 6% 5% 2% 5% 4% 6% 6% Open source use, Germany −5 0 Δ

Referencing software

Citation of software for Germany Count Percentage
1 (None at all) nan nan
2 30 10.1351
3 20 6.75676
4 13 4.39189
5 24 8.10811
6 15 5.06757
7 19 6.41892
8 21 7.09459
9 17 5.74324
10 (All the time) 67 22.6351

Download CSV

2021-08-04T21:01:51.002754 image/svg+xml Matplotlib v3.4.2, https://matplotlib.org/ 0 5 10 15 20 10 (All the time) 9 8 7 6 5 4 3 2 1 (None at all) Citation of software, Germany

Use of Digital Object Identifier (DOI)

Use of Digital Object Identifier for Germany Count Percentage Percentage in 2017 Difference with previous year
1 (None at all) nan nan nan nan
2 22 7.43243 11.3208 -3.88832
3 15 5.06757 13.2075 -8.13998
4 6 2.02703 1.88679 0.140235
5 18 6.08108 18.8679 -12.7868
6 6 2.02703 7.54717 -5.52014
7 5 1.68919 13.2075 -11.5184
8 4 1.35135 7.54717 -6.19582
9 7 2.36486 1.88679 0.478072
10 (All the time) 14 4.72973 nan nan

Download CSV

2021-08-04T21:01:53.023965 image/svg+xml Matplotlib v3.4.2, https://matplotlib.org/ 0 1 2 3 4 5 6 7 10 (All the time) 9 8 7 6 5 4 3 2 1 (None at all) 5% 2% 1% 2% 2% 6% 2% 5% 7% Use of Digital Object Identifier, Germany −10 0 Δ

Tools used for DOI

2021-08-04T21:01:54.238287 image/svg+xml Matplotlib v3.4.2, https://matplotlib.org/ Which tool is used for Digital Object Identifier, Germany

ORCID

Using ORCID for Germany Count Percentage
Yes 154 52.5597
No 58 19.7952

Download CSV

2021-08-04T21:01:54.737193 image/svg+xml Matplotlib v3.4.2, https://matplotlib.org/ 0 10 20 30 40 50 Yes No Using ORCID, Germany

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:

  • Test engineers conduct testing
  • Developers conduct testing
  • Users conduct testing
  • No formal testing

Obviously, the test engineers conduct 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 Germany Count Percentage
0 17 5.76271
0.5 1 0.338983
1 169 57.2881
1.2 1 0.338983
1.5 2 0.677966
2 78 26.4407
3 17 5.76271
4 3 1.01695
5 3 1.01695
6 2 0.677966
50 1 0.338983
200 1 0.338983

Download CSV

2021-08-04T21:01:21.991403 image/svg+xml Matplotlib v3.4.2, https://matplotlib.org/ 0 10 20 30 40 50 60 200.0 50.0 6.0 5.0 4.0 3.0 2.0 1.5 1.2 1.0 0.5 0.0 Bus factor, Germany

Presence of transition plan

Presence of transition plan for Germany Count Percentage Percentage in 2017 Difference with previous year
Yes 48 16.2162 18.6667 -2.45045
No 248 83.7838 81.3333 2.45045

Download CSV

2021-08-04T21:01:22.281666 image/svg+xml Matplotlib v3.4.2, https://matplotlib.org/ 0 10 20 30 40 50 60 70 80 No Yes 84% 16% Presence of transition plan, Germany −2.5 0.0 2.5 Δ

Use of version control

Use of version control for Germany Count Percentage
Git 263 78.979
SVN 94 28.2282
None 22 6.60661
Mercurial 15 4.5045
CVS 13 3.9039

Download CSV

2021-08-04T21:01:22.616917 image/svg+xml Matplotlib v3.4.2, https://matplotlib.org/ 0 10 20 30 40 50 60 70 80 Git SVN None Mercurial CVS Use of version control, Germany

Testing strategies

Testing strategies for Germany Count Percentage Percentage in 2017 Difference with previous year
No formal testing 47 14.1141 25.2308 -11.1167
No formal testing but users provide feedback 116 34.8348 56 -21.1652
The developers do their own testing 257 77.1772 80.9231 -3.7459
Test engineers conduct testing 14 4.2042 6.15385 -1.94964

Download CSV

2021-08-04T21:01:22.969727 image/svg+xml Matplotlib v3.4.2, https://matplotlib.org/ 0 20 40 60 80 Test engineers conduct testing The developers do their own testing No formal testing but users provide feedback No formal testing 4% 77% 35% 14% Testing strategies, Germany −20 0 Δ

Repository

2021-08-04T21:01:25.051521 image/svg+xml Matplotlib v3.4.2, https://matplotlib.org/ Repository, Germany

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 Germany Count Percentage Percentage in 2017 Difference with previous year
Python 211 63.3634 53.8462 9.51721
C++ 125 37.5375 30.4615 7.076
C 88 26.4264 22.4615 3.96489
JavaScript 76 22.8228 26.4615 -3.63872
Java 74 22.2222 21.2308 0.991453
Matlab 73 21.9219 20.6154 1.30654
R 69 20.7207 23.0769 -2.3562
SQL 66 19.8198 19.6923 0.127512
Fortran 58 17.4174 18.7692 -1.35181
PHP 31 9.30931 12.6154 -3.30608
C# 29 8.70871 4.30769 4.40102
Perl 16 4.8048 10.1538 -5.34904
Julia 14 4.2042 3.69231 0.511897
TypeScript 14 4.2042 1.53846 2.66574
VBA 11 3.3033 4 -0.696697
Rust 8 2.4024 0.615385 1.78702
Assembly 8 2.4024 3.07692 -0.674521
Go 7 2.1021 1.23077 0.871333
Ruby 6 1.8018 4 -2.1982
VB.NET 5 1.5015 1.23077 0.270732
Scala 5 1.5015 0.923077 0.578425
Visual Basic 5 1.5015 2.46154 -0.960037
Groovy 5 1.5015 1.23077 0.270732
Lua 5 1.5015 2.46154 -0.960037
Common Lisp 3 0.900901 0.307692 0.593209
Haskell 3 0.900901 0.923077 -0.022176
Swift 2 0.600601 0.615385 -0.014784
Objective-C 1 0.3003 0.615385 -0.315084
CoffeeScript 1 0.3003 0.615385 -0.315084
F# 0 0 0 0
Erlang 0 0 0 0
Elixir 0 0 0 0
Hack 0 0 0 0
Dart 0 0 0 0
Smalltalk 0 0 0 0
Clojure 0 0 0.307692 -0.307692

Download CSV

2021-08-04T21:04:18.609391 image/svg+xml Matplotlib v3.4.2, https://matplotlib.org/ 0 10 20 30 40 50 60 Clojure Smalltalk Dart Hack Elixir Erlang F# CoffeeScript Objective-C Swift Haskell Common Lisp Lua Groovy Visual Basic Scala VB.NET Ruby Go Assembly Rust VBA TypeScript Julia Perl C# PHP Fortran SQL R Matlab Java JavaScript C C++ Python 0% 0% 0% 0% 0% 0% 0% 0% 0% 1% 1% 1% 2% 2% 2% 2% 2% 2% 2% 2% 2% 3% 4% 4% 5% 9% 9% 17% 20% 21% 22% 22% 23% 26% 38% 63% Programming languages, Germany 0 10 Δ

Operating systems

Operating systems for Germany Count Percentage Percentage in 2017 Difference with previous year
GNU/Linux 164 58.363 60.0806 -1.71766
Windows 84 29.8932 22.5806 7.31259
OS X 28 9.96441 14.9194 -4.95494
Other 5 1.77936 2.41935 -0.639995

Download CSV

2021-08-04T21:04:19.211156 image/svg+xml Matplotlib v3.4.2, https://matplotlib.org/ 0 10 20 30 40 50 60 Other OS X Windows GNU/Linux 2% 10% 30% 58% Operating systems, Germany −5 0 5 Δ

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

2021-08-04T21:04:34.372436 image/svg+xml Matplotlib v3.4.2, https://matplotlib.org/ 100 90 80 70 60 50 40 30 20 10 0 10 20 30 40 50 60 70 80 90 100 Percentage satisGen1. In general, how satisfied are you with your current position satisGen2. In general, how satisfied are you with your career 6 7 10 16 10 13 22 19 34 23 13 12 6 7 10 16 10 13 22 19 34 23 13 12 General satisfaction 1 2 3 4 5 6 7 8 9 10 General satisfaction: Germany

Recognition

2021-08-04T21:04:35.090814 image/svg+xml Matplotlib v3.4.2, https://matplotlib.org/ 100 90 80 70 60 50 40 30 20 10 0 10 20 30 40 50 60 70 80 90 100 Percentage satisGen1. In general, how satisfied are you with your current position satisGen2. In general, how satisfied are you with your career 6 7 10 16 10 13 22 19 34 23 13 12 6 7 10 16 10 13 22 19 34 23 13 12 Recognition 1 2 3 4 5 6 7 8 9 10 Recognition: Germany

Turn-over intention

2021-08-04T21:04:35.894532 image/svg+xml Matplotlib v3.4.2, https://matplotlib.org/ 100 90 80 70 60 50 40 30 20 10 0 10 20 30 40 50 60 70 80 90 100 Percentage satisGen1. In general, how satisfied are you with your current position satisGen2. In general, how satisfied are you with your career 6 7 10 16 10 13 22 19 34 23 13 12 6 7 10 16 10 13 22 19 34 23 13 12 Consider leaving job 1 2 3 4 5 6 7 8 9 10 Consider leaving job: Germany 2021-08-04T21:04:36.611993 image/svg+xml Matplotlib v3.4.2, https://matplotlib.org/ 100 90 80 70 60 50 40 30 20 10 0 10 20 30 40 50 60 70 80 90 100 Percentage satisGen1. In general, how satisfied are you with your current position satisGen2. In general, how satisfied are you with your career 6 7 10 16 10 13 22 19 34 23 13 12 6 7 10 16 10 13 22 19 34 23 13 12 Would accept another job at same compensation 1 2 3 4 5 6 7 8 9 10 Would accept another job at same compensation: Germany

Perceived employability

2021-08-04T21:04:37.335302 image/svg+xml Matplotlib v3.4.2, https://matplotlib.org/ 100 90 80 70 60 50 40 30 20 10 0 10 20 30 40 50 60 70 80 90 100 Percentage satisGen1. In general, how satisfied are you with your current position satisGen2. In general, how satisfied are you with your career 6 7 10 16 10 13 22 19 34 23 13 12 6 7 10 16 10 13 22 19 34 23 13 12 Perceived employability 1 2 3 4 5 6 7 8 9 10 Perceived employability: Germany

Progression in the current role

2021-08-04T21:04:38.046896 image/svg+xml Matplotlib v3.4.2, https://matplotlib.org/ 100 90 80 70 60 50 40 30 20 10 0 10 20 30 40 50 60 70 80 90 100 Percentage satisGen1. In general, how satisfied are you with your current position satisGen2. In general, how satisfied are you with your career 6 7 10 16 10 13 22 19 34 23 13 12 6 7 10 16 10 13 22 19 34 23 13 12 Progression in the current role 1 2 3 4 5 6 7 8 9 10 Progression in the current role: Germany

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 Germany Count Percentage
Yes 28 10.9375
No 228 89.0625

Download CSV

2021-08-04T21:06:08.731794 image/svg+xml Matplotlib v3.4.2, https://matplotlib.org/ 0 20 40 60 80 No Yes RSE Member, Germany

Joining a RSE/RSD association

Joining a RSE/RSD association for Germany Count Percentage
Yes 114 65.1429
No 61 34.8571

Download CSV

2021-08-04T21:06:08.994667 image/svg+xml Matplotlib v3.4.2, https://matplotlib.org/ 0 10 20 30 40 50 60 Yes No Joining a RSE/RSD association, Germany

What is important for such an organisation

What is important for such an organisation for Germany Count Percentage
Research software standards and interoperability definition 90 27.027
Networking 89 26.7267
Research collaborations 79 23.7237
Training 76 22.8228
Job opportunities 58 17.4174

Download CSV

2021-08-04T21:06:09.270130 image/svg+xml Matplotlib v3.4.2, https://matplotlib.org/ 0 5 10 15 20 25 Research software standards and interoperability definition Networking Research collaborations Training Job opportunities What is important for such an organisation, Germany

Attending a national conference of RSE/RSD

Attending a national conference of RSE/RSD for Germany Count Percentage Percentage in 2017 Difference with previous year
Yes 201 80.4 77.665 2.73503
No 49 19.6 22.335 -2.73503

Download CSV

2021-08-04T21:06:09.512044 image/svg+xml Matplotlib v3.4.2, https://matplotlib.org/ 0 10 20 30 40 50 60 70 80 No Yes 20% 80% Attending a national conference of RSE/RSD, Germany −2.5 0.0 2.5 Δ

Learning skills for RSE/RSD

2021-08-04T21:06:12.060669 image/svg+xml Matplotlib v3.4.2, https://matplotlib.org/ Learning skill to become a RSE/RSD, Germany

Which skills to improve

2021-08-04T21:06:15.064180 image/svg+xml Matplotlib v3.4.2, https://matplotlib.org/ Which skill to improve as RSE/RSD, Germany