Report on the Faculty & Postdoctoral Survey on Research ......Felicity Tayler, E-Research Librarian,...

Report on the Faculty & Postdoctoral Survey

on Research Data Management at the

University of Ottawa

Report prepared by:

Melissa Cheung, Principal Investigator

Co-investigators:

Jessica McEwan

Patrick Labelle

Lindsey Sikora

March 2020

Acknowledgements

This study would not have been successful without the help and support of colleagues. The survey team

would like to thank Catie Sahadath, former Data Librarian, for her work on this project. Many thanks to

Felicity Tayler, E-Research Librarian, and Chantal Ripp, Research Librarian (Data), for their feedback

and guidance in preparing this report, and to library colleagues who provided suggestions to improve the

survey questionnaires. We are also grateful for the support from past University Librarian Leslie Weir,

from current University Librarian Talia Chung as well as from members of the Library’s senior

leadership. We would also like to acknowledge the contributions of Dave Weatherall, former

Communications and Marketing Officer.

Executive Summary

Introduction This report provides an overview of the Faculty and Postdoctoral Survey on Research Data Management

conducted by librarians at the University of Ottawa (uOttawa). The survey was designed to:

• determine how uOttawa researchers manage and share research data beyond the duration of their

project

• determine how the uOttawa Library might help to facilitate data management activities

• understand some of the differences in research data management practices and needs across

disciplines and sub-disciplines

Survey participants were asked general questions related to research data management (RDM) as well as

specific questions about potential RDM services that could be offered by the Library. The bilingual

(English/French) survey was deployed in two phases targeting different disciplines. The surveys for

Science and Engineering, and for Humanities and Social Sciences were available from November 14 to

25, 2016. The survey for Health and Medical Sciences was available from March 20 to March 31, 2017.

Key Findings

• Researchers need RDM services and infrastructure that facilitate collaboration, including

international collaborations that may be subject to multiple RDM policies.

• Researchers indicated their intent to share their data in the future and would benefit from

assistance in identifying appropriate methods of data sharing that comply with applicable

policies related to research ethics. In particular, there is an interest in support for using

institutional repositories to share research data.

• Researchers could benefit from assistance with data documentation for appropriate reuse of their

data and to foster reproducibility in research to meet Tri-Agency expectations for excellence in

data stewardship.

• Researchers need or would prefer assistance and/or guided documentation to prepare data

management plans (DMPs). • Researchers indicated they were not teaching RDM topics, which suggests a lack of education

and training in the essentials of research data management for the next generation of researchers.

Background As public funding agencies and publishers recognize the value in preserving research data, many are

developing policies around data management, sharing, and preservation. In the US and the UK, funding

mandates require that research groups submit a research data management plan (DMP) in order to secure

funding. Similar mandates are expected in Canada, following the release of the Tri-Agency Statement of

Principles on Digital Data Management1 in 2016 and the draft Tri-Agency Research Data Management

Policy2 in 2018.

Librarians from universities across Canada, including uOttawa, are collaborating to conduct a series of

surveys to better understand data management practices and needs in the natural sciences, engineering,

social sciences, humanities, and health sciences.

Methodology

Survey Design The survey instrument was initially developed by the University of Toronto Libraries for researchers in

science and engineering. Members of the Canadian RDM Survey Consortium3 worked together to

modify the survey, creating one version targeting researchers in the humanities and social sciences and

another version for researchers in the health and medical sciences. The uOttawa research team further

customized these three surveys to reflect the departmental structure and unique characteristics of the

uOttawa academic community, including translating the surveys into French to address the bilingual

nature of the University. As a result, the uOttawa survey included six questionnaires: one for each

discipline, and each with separate English and French versions.

The science and engineering (SciEng) survey consisted of 22 questions. The humanities and social

sciences (HUSS) survey included additional questions related to the digital humanities for a total of 24

questions. The health and medical sciences (HSM) survey consisted of 23 questions due to differences in

how the questions were entered and numbered in the survey tool.

The questions in all three surveys were organized into four sections:

1. Demographics and general questions

2. Working with research data

3. Data sharing

4. Funding mandates and RDM services

Survey Distribution The surveys were administered using FluidSurveys. The SciEng and HUSS surveys were deployed at

the same time and were available from November 14 to 25, 2016. The HSM survey, which was

developed at a later date, was available from March 20 to March 31, 2017.

A distribution list containing names, email addresses and language preferences of faculty members and

postdoctoral fellows in each department was requested from uOttawa Human Resources. Personalized

invitations to participate in the survey were sent by email from the University Librarian’s Office to

1 Tri-Agency Statement of Principles on Digital Data Management - http://www.science.gc.ca/eic/site/063.nsf/eng/h_83F7624E.html 2 Draft Tri-Agency Research Data Management Policy - http://www.science.gc.ca/eic/site/063.nsf/eng/h_97610.html 3 Canadian RDM Survey Consortium ‐ https://portagenetwork.ca/network-of-experts/network-of-expertise/rdm-survey-consortium/

http://www.science.gc.ca/eic/site/063.nsf/eng/h_83F7624E.html

http://www.science.gc.ca/eic/site/063.nsf/eng/h_97610.html

https://portagenetwork.ca/network-of-experts/network-of-expertise/rdm-survey-consortium/

3,213 faculty members and postdoctoral fellows. Researchers were invited to complete the appropriate

disciplinary survey that corresponded to their faculty4 and in their preferred language. Completing the

survey was entirely voluntary and anonymous.

Limitations of Research Methodology The results of this survey provide insights into the RDM practices and attitudes of uOttawa faculty

members and postdoctoral fellows who completed the survey. However, there are limitations in the

survey design. Participants who completed the survey were self-selected, which may have led to bias in

the results. Additionally, survey questionnaires were developed at different times and were further

modified to reflect characteristics of the institution administering the survey. This resulted in

inconsistent terminology appearing in the survey.

Furthermore, the timing of survey deployment may have contributed to a low response rate. The SciEng

and HUSS surveys were distributed six months after a Library collections survey that was launched to

inform the decision-making process of a cost-cutting exercise. This may have led to survey fatigue and a

lack of trust in the Library’s motivations for conducting another survey. At least one faculty member

declined to participate in the RDM survey citing concerns that the Library would use survey results to

cancel more services and resources as part of cost reduction. Meanwhile, the HSM survey was

distributed at the end of the academic year before final exams, which may have led to a low response

rate from the Faculty of Health Sciences and the Faculty of Medicine.

Given these limitations, caution must be taken when interpreting the results. The data discussed in this

report are only representative of individuals who completed the survey and cannot be applied to the

larger uOttawa academic community without further research and analysis.

Results

Survey Data Research data, survey questionnaires, and relevant documentation are available at:

Cheung, Melissa; Sahadath, Catie; Labelle, Patrick; McEwan, Jessica; Sikora, Lindsey, 2017, "Faculty

& Postdoctoral Survey on Research Data Management at the University of Ottawa",

https://doi.org/10.5683/SP/L1H3SS, Scholars Portal Dataverse, V6.

Survey Status Table 1 shows the status of survey responses obtained from FluidSurveys after the survey was closed.

The total number of responses to the survey was 260 with 177 complete survey responses and 83

incomplete surveys. Of the 177 complete responses, 48 responses were in French and 129 were in

English; 43 were received from the SciEng survey, 101 from the HUSS survey and 33 from the HSM

survey.

A survey was counted as completed if the respondent answered all required questions and clicked the

submit button. Participants were permitted to skip questions, except for the two required questions

pertaining to rank and affiliated faculty, institute or department. An incomplete survey refers to a survey

4 Researchers in the Faculty of Education, Faculty of Law and Telfer School of Management were invited to complete the HUSS survey.

https://doi.org/10.5683/SP/L1H3SS

where some questions were answered but the respondent never finished the survey by clicking the

submit button.

Based on the number of completed surveys, the response rate was only 5.5% (177/3213).

Table 1. Survey Status reported by FluidSurveys.

Survey Invites Responses Incomplete Completed

HSM EN 994 33 7 26

HSM FR 184 10 3 7

HUSS EN 898 96 29 67

HUSS FR 566 50 16 34

SciEng EN 381 57 21 36

SciEng FR 100 14 7 7

Survey Findings The findings reported here are based on the 177 completed surveys. At least one individual from each

Faculty at uOttawa completed the survey. Given the low response rate, especially from Law and

Management, the survey data are not statistically significant and the findings cannot be generalized to

the entire uOttawa academic community. However, the results may still reveal trends in researcher needs

and/or gaps in knowledge that could be useful for future discussions regarding RDM support or services.

Section 1: Demographics and General Questions

As presented in Table 2, 133 of the survey respondents were professors (assistant, associate and full) and

clinical colleagues, 7 were adjunct professors, 7 were part-time professors, 13 were lecturers, 1 was a

professor emeritus, 1 was a research associate, and 13 were postdoctoral fellows.

Table 2. Respondent rank. Survey participants were asked to indicate their rank at the University of

Ottawa (n=177).

Rank Number of responses % of respondents

Adjunct Professor 7 4%

Assistant/Associate/Full Professor/Clinical Colleague 133 75%

Lecturer 13 7%

Part-time Professor 7 4%

Research Associate 1 1%

Professor Emeritus 1 1%

Postdoctoral Fellow 15 8%

Table 3. Number of distributed surveys, sample responses and percentage of responses by faculty

(n=177).

Art

s

Educa

tion

Engin

eeri

ng

Hea

lth S

cien

ces

Law

Man

agem

ent

Med

icin

e

Sci

ence

Soci

al S

cien

ces

Not

Dec

lare

d

# distributed surveys 519 152 194 236 198 137 942 286 549

Sample Responses 39 7 20 10 3 6 23 22 46 1

% of Responses 8% 5% 10% 4% 2% 4% 2% 8% 8%

Survey participants were asked to select their home department at uOttawa from a list of options. The

responses were aggregated by faculty and shown in Table 3. The Faculty of Social Sciences had the

highest number of respondents, representing 26% (46/177) of the total number of respondents, followed

by the Faculty of Arts (39/177=22%). Meanwhile, the Faculty of Law (3/177=2%) and the Telfer School

of Management (6/177=3%) had the lowest number of respondents. One respondent who completed the

SciEng survey did not specify their department or faculty.

It is interesting to note that, overall, the Faculty of Engineering did not represent the largest number of

survey respondents. However, they represented the largest sample of the target population for their

faculty. On the other hand, respondents from the Faculty of Medicine, which included medical doctors

employed at affiliated hospitals, represented the smallest sample of the target population.

Section 2: Working with Research Data

Figure 1. Amount of storage in relation to number of research projects. Survey participants were asked to

estimate the amount of storage they use in an average research project as well as the number of research projects

they lead in the past year (n=177).

The relationship between storage volume required for the average research project and the number of

projects led by the researcher in the past year is shown in Figure 1. At the time the survey was

conducted, most research projects required less than 1,000 GB of storage (124/177=70%). However,

approximately 18% (31/177) of respondents were not sure how much storage they used in an average

project.

Two respondents answered “Not Applicable” to both of these questions because they did not work with

the kind of research data defined in the survey introduction or they were not advising research projects

at the time of the survey. One respondent noted they were “Not sure” how many research projects they

lead in a year and they did not require storage (“Not Applicable”) because they did not use the type of

data defined in the survey introduction. One respondent, who led 1-2 research projects in the past year,

noted that they did not require storage (“Not Applicable”) because they stored their data at home.

Researchers in Arts and Social Sciences represented most of the respondents who were unsure of the

amount of storage they used in an average research project (survey responses by faculty are included in

the Appendix). Meanwhile, respondents from the Faculty of Science and the Faculty of Engineering all

provided an estimate for the amount of storage they used; the most frequent response was less than 50

GB. These results suggest that researchers in Arts and Social Sciences may require more support in

identifying the amount of data storage they need to develop an appropriate data management plan.

1

17

1

1

1

3

12

7

12

17

12

3

2

2

2

6

5

7

10

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3

6

5

6

1

2

1

2

2

4

1

1

1

1

2

2

0 5 10 15 20 25 30 35

Not Applicable

Not sure

> 4TB

4TB to 500TB

1TB to 4TB (Terabyte)

1TB to < 4TG (Terabyte)

500GB to < 1000GB

50GB to < 500GB

< 50GB (Gigabyte)

10GB to < 50GB

1GB to < 10GB

< 1GB (Gigabyte)

Number of Responses

Sto

rage

Vo

lum

e fo

r A

vera

ge R

esea

rhc

Pro

ject

1-2 research projects


>5 research projects

Not sure

Not applicable

Figure 2. Type of research data generated or used. Survey participants were asked to indicate all of the

applicable types of research data they generate or use in a typical research project (n=177).

As Figure 2 illustrates, the most frequent data types generated or used by survey respondents were text,

numerical and multimedia. When given examples, respondents in the Faculty of Medicine were the only

ones to select discipline specific (e.g. BAM, fastq, CEL, IDAT, FASTA, PBD, ENT, BRK) as a data

type. Respondents in other disciplines characterized their research data using the more common types

(Appendix).

13

7

11

31

34

38

98

102

151

0 20 40 60 80 100 120 140 160

Other

Discipline specific (e.g. BAM, fastq, CEL, IDAT, FASTA, PBD,ENT, BRK, CIF, FITS, DICOM)

Geospatial - (e.g. raster, vector, grid, boundary files)

Instrument specific (e.g. fMRI, Olympus Confocal MicroscopeData Format, FLIR Infrared Camera (SEQ))

Software– (e.g. Java, C, Perl, Python, Ruby, PHP, R)

Models – (e.g. 3D, statistical, similitude, macroeconomic, causal)

Multimedia (e.g. JPEG, TIFF, MPEG, MP3, Quicktime, Bitmap,Audio/Visual records)

Numerical – (e.g. CSV, MAT, XLS, SPSS)

Text - (e.g. TXT, DOC, PDF, RTF, HTML, XML)

Number of Responses

Dat

a Ty

pe

Figure 3. Software or hardware mentioned most frequently in response to the question “Please list any software

and/or hardware used for the collection, analysis, or manipulation of your research data, if applicable”.

Survey participants were asked to list any software and/or hardware they used for the collection,

analysis, or manipulation of research data. The text responses received, consisting of 202 terms, were

analyzed using Voyant Tools5 to count the number of times a particular software/hardware was named6.

Figure 3 shows the software/hardware that were mentioned more than once in the responses received.

At the time of the survey, Excel (51), SPSS (34), NVIVO (23), Word (23) and MatLab (21) were the

most frequently named software/hardware used for the collection, analysis or manipulation of research

data. These results are unsurprising, given that text and numerical data were identified as the most

commonly generated or used data type (Figure 2). It should also be noted that nearly half of the survey

respondents were from the Faculty of Arts and the Faculty of Social Sciences (Table 2), which may have

skewed the results in Figure 3 towards software/hardware used most frequently in those disciplines.

Therefore, the frequency of software/hardware used in other disciplines may be underrepresented.

5 Sinclair, S.& G. Rockwell. (2019). Trends. Voyant Tools. Retrieved December 22, 2019, from http://voyant-tools.org 6 The number of times statistical computing software R was named was counted manually since Voyant Tools did not recognize it as a

word or term.

http://voyant-tools.org/

Figure 4. Data storage. Survey participants were asked to select all the applicable options for where they store

raw data, manipulated data (e.g. converted, curated, processed), and archived data (e.g. long-term storage or

preservation) from current project(s) (n=176).

The survey results illustrated in Figure 4 show that researchers used a variety of options to store their

research data at different stages of the research data lifecycle7. Survey respondents indicated that they

stored their data primarily on external hard drives, laptops and computer hard drives. On the other hand,

external data repositories (e.g. Protein Data Bank, Cambridge Structural Database, GitHub, Dryad,

Figshare) were not used often as a data storage option8. Flash drives/USBs were used primarily to store

raw and manipulated data, while CDs/DVDs were generally used to store archived data.

At the time of the survey, researchers in the Faculty of Arts and the Faculty of Social Sciences were the

only ones who were “Not Sure” where they stored their research data (Appendix). This suggests that

they would benefit from additional support in data management planning and in identifying appropriate

data storage options for their research. Meanwhile, Engineering, Medicine, Science and Social Sciences

were the only disciplines that made use of grid/high performance computing (HPC) centres for storage.

Only one respondent in the Faculty of Social Sciences selected grid/HPC centres to store archived data.

7 https://biblio.uottawa.ca/en/services/faculty/research-data-management/what-research-data-management 8 The question “Are you aware of any discipline-specific data repositories related to your field? Please list. If you are not aware of any

discipline-specific data repositories related to your field, please say ‘none’.” was asked in the Data Sharing Section of Survey. Text

responses to this question were removed from the data set and are not included in this analysis.

1

89

11

111

112

106

31

62

70

11

5

60

2

79

7

110

104

99

13

57

72

7

4

33

2

20

61

88

104

114

12

57

54

16

2

37

0 50 100 150 200 250 300 350

Not Sure

USB

CD

Computer Hard Drive

Laptop

External Hard Drive

Instrument Hard Drive

Shared Drive

Cloud Storage

External Data Repository

High Performance Computing

Physical Copy

Number of Responses

Sto

rage

Med

ium

Raw Data

Manipulated Data

Archived Data

https://biblio.uottawa.ca/en/services/faculty/research-data-management/what-research-data-management

Figure 5. Documentation for data reuse. Survey participants were asked whether there is sufficient

documentation and description for another person outside the research team to understand and use their research

data (n=177).

When asked whether they were creating sufficient data documentation for another person to understand

and make use of their research data (Figure 5), 43% of respondents said “yes” (76/177), 26% of

respondents said “no” (46/177), and 31% of respondents were “not sure” (55/177). Social Sciences was

the only discipline with a greater number of positive responses over negative responses compared to

other disciplines. These results suggest that researchers require additional support in creating

documentation for data reuse, which is an expectation of the Tri-Agency Statement of Principles on

Digital Data Management.

Figure 6. Documentation for data reproducibility. Survey participants were asked whether there is sufficient

documentation and description for another person outside the research team to replicate the methodologies that

produced their research data (n=177).

26

7

9

4

2

2

7

2

17

8

7

4

4

8

2

13

1

12

8

10

2

1

4

5

3

9

0 5 10 15 20 25 30 35 40 45 50

Not Declared

Social Sciences

Science

Medicine

Management

Law

Health Sciences

Engineering

Education

Arts

Number of Responses

Facu

lty

Yes

No

Not sure

21

9

13

2

2

3

11

3

17

16

7

4

3

6

4

12

1

9

6

6

4

1

4

3

10

0 5 10 15 20 25 30 35 40 45 50

Not Declared

Social Sciences

Science

Medicine

Management

Law

Health Sciences

Engineering

Education

Arts

Number of Responses

Facu

lty

Yes

No

Not sure

When asked whether they were creating sufficient data documentation for another person to replicate the

methodologies that produced their research data (Figure 6), 46% of respondents said “yes” (n=81), 29%

of respondents said “no” (52/177), and 25% of respondents were “not sure” (44/177). Researchers in

Social Sciences were less confident that they had produced sufficient documentation for reproducibility

compared to data documentation produced to understand and make use of data (shown in Figure 5).

Meanwhile, researchers in Science and Engineering were slightly more confident that they had produced

sufficient data documentation for reproducibility compared to documentation for understanding and

making use of their data.

These results suggest that researchers could benefit from additional support in creating documentation

for data reproducibility to meet the Tri-Agency’s expectation that experiments and studies be replicable

to meet standards in research excellence as described in the draft Tri-Agency RDM policy.

Figure 7. Length of Time Research Data Are Kept. Survey participants were asked to indicate how long they

typically intentionally keep “source material/survey results/raw data” (n=177), “intermediate/working data”

(n=175), and “processed data ready for publication” (n=174) after project completion.

The majority of respondents indicated they typically intentionally kept their research data until the data

becomes inaccessible or lost (Figure 7). However, survey participants were not asked about the data

curation practices they used to actively preserve their data for as long as possible. Therefore, the

intention to keep research data until it becomes inaccessible or lost may be the default practice among

researchers who do not take action to dispose or destroy their data (e.g. compliance with research ethics

requirements).

Researchers in Arts, Management and Social Sciences intentionally kept their raw data for the length of

their project; researchers in all the other disciplines intentionally kept their raw data beyond completion

of their project (Appendix). Researchers in Engineering and Science indicated that they kept raw data

less than 3 years, while Education, Law, Health Sciences and Medicine kept raw data for longer than 3

years. Researchers in Arts, Engineering, Health Sciences and Social Sciences specified that they kept

73

33

36

23

4

8

68

31

36

20

13

7

79

36

34

20

3

2

0 50 100 150 200 250

Until the data becomes inaccessible or lost

More than 10 years

Between 5-10 years

Between 3-5 years

Less than 3 years

I only keep data for the length of the project

Number of Responses

Len

gth

of

Tim

e R

esea

rch

Dat

a A

re K

ept

Raw Data

Intermediate Data

Processed Data

intermediate data only for the length of the project; all other disciplines kept data beyond completion of

project. Notably, Law kept intermediate data for at least 3 years, while Education kept intermediate data

for more than 5 years.

When it comes to processed data ready for publication, only researchers in Social Sciences intended to

keep processed data for the length of the project; all other disciplines intended to keep processed data

beyond the completion of the project. In particular, Engineering and Health Sciences indicated that they

kept processed data for less than 3 years, while all other disciplines intended to keep processed data

longer than 3 years.

Section 3: Data Sharing

Figure 8. Comparison of current methods and future intentions of sharing research data. Survey participants

were asked to select all the applicable methods of sharing research data they currently use (n=177) and would

consider using in the future (n=176).

As Figure 8 illustrates, at the time of the survey, 28% (49/177) of respondents were not currently sharing

their data. However, only 10% (18/176) were not planning to share their data in the future, which

indicates that more researchers would consider sharing their data in the future. Share by personal request

was the most frequent method of data sharing with 53% (93/177) of respondents currently sharing their

data using this method and 50% (105/176) of respondents reporting they would consider sharing their

data in the future using this method.

49

93

40

1913

40

1718

105

67

5044

53

30

0

20

40

60

80

100

120

Nu

mb

er o

f R

esp

on

ses

Methods of Sharing Research Data

Current methods of sharing research data

Future intentions of sharing research data

In general, data repositories were not frequently used to share research data. Researchers in Management

and Education were not using data repositories (institutional, general, or discipline-specific), while

Science and Engineering made use of general or discipline-specific repositories, but not institutional

repositories (Appendix). Researchers in Engineering were also more likely to share by personal request

only over any other method of sharing. In Science and Medicine, respondents indicated they were more

likely to share as supplementary files to journal publication over any other method, which is not

surprising since this is a fairly well-established practice in these disciplines.

Comparing current practices at the time of the survey and future intentions of data sharing, the results

showed an increased interest in using a variety of mechanisms for data sharing. Notably, 25% of

respondents (44/176) indicated willingness to consider using an institutional data repository, such as

Dataverse, in the future while only 7% (13/177) were using an institutional repository to share their data

at the time of the survey. Notably, in the context of this survey, “institutional repository” referred to an

institutional data repository (i.e. uOttawa’s instance of Dataverse) and not a repository for self-archiving

of research publications and/or conference materials (ie uOttawa’s uOResearch). The survey results may

therefore reflect confusion over the meaning of “institutional repository”. That said, the results suggest

there is interest from researchers in using an institutional repository for data sharing to achieve

compliance with data deposit requirements.

Researchers in Education, Law, and Science all indicated intent to share their data in the future, whereas

some researchers in other disciplines responded that they were not planning to share their data in the

future (Appendix).

Figure 9. Restrictions or embargoes on data sharing. Survey participants were asked to select all applicable

restrictions or embargoes that may limit their ability to share their data with others (n=176).

When asked about restrictions or embargoes that may limit the ability to share their data with others,

“privacy, confidentiality, or ethics restrictions” was the most frequently chosen response, followed by

the need to publish before sharing the data (Figure 9). Meanwhile, 25% (45/176) of respondents

14

11

62

31

9

9

22

66

5

45

0 10 20 30 40 50 60 70

Other

I'm unsure if I am allowed to share my data

I need to publish my data first

May jeopardize intellectual property rights

I plan to file for a patent

Commercial concerns

Contractual obligation

Privacy, confidentiality, or ethics restrictions

Public safety or sensitive nature

No restrictions or embargoes

Number of Responses

Res

tric

tio

n o

r Em

bar

goes

indicated that there were no restrictions on embargoes that may limit the ability to share their data with

others, and 6% (11/176) of respondents were unsure if they were allowed to share their data.

An analysis of restrictions or embargos identified by each faculty (Appendix) revealed that researchers

in all disciplines were affected by privacy, confidentiality, or ethics restrictions. Arts and Social

Sciences were the only disciplines that had restrictions because their data were a matter of public safety

or of a sensitive nature. They were also the only disciplines to indicate that they were unsure if they

were allowed to share their data at the time of the survey; researchers in all other disciplines were aware

of whether or not there were any restrictions on sharing their data. These results suggest that researchers

in Arts and Social Sciences may require more support in navigating policies related to data sharing and

research ethics requirements compared to other disciplines.

Interestingly, researchers in Management, Law, and Education were the only disciplines that indicated

they were not concerned about the need to publish their research before sharing their data (i.e. being

scooped).

Figure 10. Audience/Collaborators for data sharing. Survey participants were asked to select all the applicable

audiences and/or collaborators with whom they would be willing to share their data with if they were not affected

by restrictions or embargos (n=173).

If their data were not affected by restrictions or embargos, survey participants indicated they would be

most willing to share their data with immediate collaborators, followed by researchers in their field

(Figure 10). Only 5 participants indicated they were not willing to share their data (“nobody”). As the

survey did not ask respondents to specify where their immediate collaborators were located it is not

possible to deduce whether survey respondents had collaborators outside Canada. However, given the

rise of inter-disciplinary and inter-institutional research collaborations, it is highly possible that

researchers at uOttawa may need to comply with multiple RDM policies, mandates, and/or practices,

including those of international collaborators, and this will have implications on the development of

RDM services to support researchers in the uOttawa context.

5

95

50

37

82

31

59

0 20 40 60 80 100

Nobody

Immediate collaborators

Researchers in my department

Researchers at uOttawa

Researchers in my field

Researchers outside my field

Anybody, including the general public

Number of Responses

Au

die

nce

/Co

llab

ora

tors

Researchers in Arts were most willing to share with anybody, including the general public, compared to

researchers in other disciplines (Appendix), followed by researchers in Engineering and Science. Survey

respondents from the Telfer School of Management (n=6) indicated that they would only be willing to

share their data with specific audiences or collaborators; none of them indicated they would be willing to

share with anybody.

Researchers in Medicine were more likely to share with other researchers in the same department

(12/23=52%) compared to other disciplines, which may suggest a higher degree of departmental

collaboration than other disciplines.

Figure 11. Reasons for not sharing research data. Survey participants were asked to indicate all applicable

reasons why they would not be willing to share their research data and associated methods/tools (n=173).

When asked about reasons why they would not be willing to share their research data and associated

methods/tools, survey respondents cited incomplete or not finished data and privacy, legal or security

issues as the primary reasons (Figure 11). Respondents also indicated that they still wished to derive

value from their data and were concerned that their data could potentially be used without proper

citation or their data could be potentially misused. On the other hand, 25% (44/173) of respondents were

willing to share their data.

At the time of the survey, 55% of the 20 respondents from the Faculty of Engineering were most willing

to share their data (Appendix). However, they indicated that the most frequent reasons for not sharing

were due to incomplete data or they still wished to derive value from their data. These results suggest

that researchers in Engineering could benefit from training and support to identify ways to share their

14

53

43

11

28

6

11

5

33

25

23

17

15

53

43

36

44

0 10 20 30 40 50 60

Other

Incomplete or not finished

Still wish to derive value

Do not have technical skills or knowledge

Do not hold rights to share

Funding body does not require sharing

I believe they should not be shared

I did not know I could share

Insufficient time

Lack of standards

Lack of funding

No place to put them

Not useful to others

Privacy, legal or security concerns

Could potentially be used without proper citation

My data could potentially be misused

I am willing to share

Number of Responses

Rea

son

s fo

r N

ot

Shar

ing

Res

earc

h D

ata

data to comply with the anticipated Tri-Agency RDM policy requirements regarding data deposit, while

mitigating the risks of being scooped.

Researchers in Social Sciences were least willing to share their data with only 3 of 46 (7%) respondents

indicating that they were willing to share their data. Researchers in Education and Social Sciences were

the most concerned about privacy, legal or security restrictions on data sharing. Researchers in Arts and

Medicine also frequently cited privacy, legal and security concerns as a reason for not sharing data.

Researchers in Arts, Health Sciences, Medicine, Science and Social Sciences were more frequently

concerned about improper citation compared to other disciplines. Additionally, researchers in Health

Sciences, Science and Social Sciences were more frequently concerned about misuse of data compared

to other disciplines. These results suggest that researchers in these disciplines could benefit from

training and increased awareness of topics such as proper data citation and improving data

documentation practices to lower the risks of data misuse.

Although the sample responses from the Faculty of Law (n=6) were too low to determine any trends,

respondents indicated that the reasons for not sharing their data included incomplete data, a lack of

standards to make them usable by others, a lack of funding and nowhere to deposit their data. These

results suggest there may not be a culture of data sharing in Law at the time of the survey, but there is an

interest in developing one because respondents indicated they were interested in sharing their data in the

future (Appendix).

Figure 12. Benefits of sharing research data. Survey participants were asked to select all the applicable benefits

they see to sharing their research data (n=174).

7

20

63

94

80

39

32

110

85

92

64

86

68

51

0 20 40 60 80 100 120

Other

No benefits

Safeguards against misconduct

Training next generation researchers

Enables my data to be cited

Strengthens my academic portfolio

Increased my ability to obtain funding

Encourages collaborative scholarship

Encourages interdisciplinary research

Moves my field of research forward

Reduces redundant data collection

Supports open access to knowledge

Helps verify results

Help data integrity

Number of Responses

Ben

efit

s o

f D

ata

Shar

ing

When asked what benefits they see to sharing their research data, “encourages collaborative

scholarship”, “training the next generation of researchers” and “moves my field of research forward”

were the most frequently selected responses as illustrated in Figure 12. These results correspond to the

results illustrated in Figure 10, which suggest that the primary reason researchers share their data is

to collaborate on their research projects. Therefore, RDM services and infrastructure should facilitate

research collaborations, including international collaborations that may be subject to multiple RDM

policies.

Although most respondents saw some benefits to sharing their data, twenty respondents (20/174=11%)

indicated that they saw no benefits to sharing their data. These respondents were from disciplines other

than Science and Law (Appendix).

Section 4. Funding Mandates and Research Data Management (RDM) Services

Figure 13. Ability to draft a data management plan. Survey participants were asked whether they would be able

to draft a data management plan (DMP) as part of a grant application (n=173).

Figure 13 shows that 15% of respondents (26/173) indicated they would be able to draft a data

management plan (DMP) without assistance; 37% (65/173) would be able to draft a DMP, but would

prefer to have assistance and/or guided documentation; and 48% (83/173) would need assistance and/or

guided documentation to appropriately address the sections of a DMP. These results clearly indicate an

interest in assistance and guidance for preparing DMPs to meet anticipated Tri-Agency RDM

requirements and should be a priority in the development of RDM services.

Researchers in Science and Engineering were more likely to need assistance to draft a DMP compared to

other disciplines (Appendix). Responses from researchers in other disciplines were more evenly divided

between “need assistance” and “prefer assistance”. These results suggest that researchers in Science and

Engineering may not be accustomed to planning and/or describing their data management strategies.

Whereas researchers in other disciplines working with data that are subject to research ethics policies

15%

37%

48%

I would be able to draft a datamanagement plan without assistance

I would prefer to have assistanceand/or guided documentation

I would need assistance and/orguided documentation

may be more familiar with certain aspects of planning adequate data management strategies, such as

privacy, legal or security concerns (Appendix).

Taken together, our survey results suggest that researchers in all disciplines would benefit from

guidance to address different sections of a DMP. For example, researchers in Arts and Social Sciences

may need more assistance to identify storage requirements (Appendix) and to determine data sharing

permissions (Appendix), while researchers in Science and Engineering may need more assistance in

articulating the specifics of their data management strategies in a DMP.

Figure 14. RDM topics in teaching. Survey participants were asked to select all the applicable topics related to

RDM they include in their teaching practice (n=173).

The majority of respondents (118/173=68%) indicated that they do not teach RDM topics as illustrated

in Figure 14.

Overall, the most popular RDM topics taught by respondents were data ethics and data privacy. When

comparing disciplinary differences (Appendix), researchers in Arts, Engineering, Management, and

Social Sciences indicated that they included all the topics listed in their teaching practice. While

researchers in Science excluded data security and researchers in Medicine excluded version control from

their teaching practice but included all the other topics listed. Researchers in Health Sciences did not

teach version control and data documentation. Finally, researchers in Education taught the fewest

number of RDM concepts only including security, privacy, ethics and retention in their teaching

practice.

7

20

22

23

16

41

22

12

37

23

118

0 20 40 60 80 100 120 140

Other

Data archiving

Data retention

Data documentation

Data sharing

Data ethics

Data backup

Data version control

Data privacy

Data security

I do not teach RDM topics

Number of Responses

RD

M T

op

ics

in T

each

ing

Figure 15. Use of own research data in teaching. Survey participants were asked if they use their own research

data in their teaching practice (n=175).

Although the majority of respondents reported that they did not teach RDM topics (Figure 14), half of

the respondents (88/175=50%) indicated that they used their own research data in their teaching practice

(Figure 15), which corresponds with researchers indicating that sharing their data is beneficial to

training the next generation of researchers (Figure 12).

Researchers in Arts were most likely to use their own data, while researchers in Medicine were least

likely to use their own data. Taken together, these results suggest that researchers’ teaching practices

may include the use of data, either their own or from another source, but they do not cover how to

manage that data. Therefore, there is potentially a lack of education and training in the essentials of

research data management for the next generation of researchers.

23

10

5

2

2

4

9

6

27

1

19

7

11

3

1

2

7

1

8

4

5

7

1

4

3

3

0 5 10 15 20 25 30 35 40 45 50

Not Declared

Social Sciences

Science

Medicine

Management

Law

Health Sciences

Engineering

Education

Arts

Number of Responses

Facu

lty

Yes

No

Not applicable

Figure 16. Interest in data services. Survey participants were asked to rate their interest in potential services if

DMPs were required as part of grant applications (n=174).

Overall, respondents indicated they were interested in data services (Figure 16). However, respondents

generally selected the same level of interest for each of the potential services listed and some only

provided responses to services of interest while skipping over others. These results may reflect survey

fatigue due to the long list of potential services in addition to a rather long survey questionnaire.

Therefore, it is not possible to draw any significant conclusions regarding the level of interest in specific

data services from this particular survey question.

However, gaps in researcher knowledge and readiness to meet RDM requirements have been identified

in previous sections of this report. For example, researchers indicated they would need or prefer

assistance and/or guided documentation to prepare DMPs (Figure 13). The identified gaps can be used to

determine priorities for RDM service development. Furthermore, interest in the potential services

proposed in the survey may increase when the Tri-Agency RDM policy comes into effect.

52

52

52

52

52

53

53

54

54

54

54

51

55

75

76

77

76

77

79

75

76

77

78

79

76

80

22

22

22

22

22

22

23

23

23

23

23

23

23

13

13

13

13

13

13

13

13

12

13

13

13

13

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Assistance in finding and accessing data sources

Assignment of DOIs

Assistance with disciplinary or other external data repositories

Institutional repository for long-term access and preservation

Data storage and backup

Assistance with data preservation and/or sharing

Assistance with metadata creation

Digitization of physical records

Assistance preparing DMPs or data management policies

Information about funding and journal requirements

Personalized RDM Consultations

Workshops for Grad Students

Workshops for Faculty

Very Interested Interested Not Interested Not Applicable

Research Data Management in the Digital Humanities

Digital Humanities (DH) or Digital Scholarship is a growing trend in research methodologies and there

is an increasing interest from libraries to develop services and support for DH researchers. To explore

RDM practices that are potentially unique to DH researchers, faculty members and postdoctoral fellows

who were invited to participate in the Humanities and Social Sciences (HUSS) version of the survey

were asked this additional question:

Digital Humanities, or Digital Scholarship, can be defined as the collection and use of digital

research data (either through digitization of print resources, or using born-digital resources)

combined with methodologies from traditional Humanities and Social Science scholarship.

Do you feel your research falls under this definition?

A total of 100 survey participants responded to this question (100/101=99%). Figure 17 shows that 46

respondents identified themselves as digital humanists/digital scholars, while 37 did not and 17 were not

sure if their research fit this definition of digital humanities/digital scholarship.

Figure 17 Digital Scholarship by Faculty. HUSS Survey respondents were asked if they identified themselves as

digital scholars/digital humanists (n=100).

Interestingly, all three participants from the Faculty of Law identified themselves as digital scholars.

Given the low response rate, the survey results are only representative of the individuals who

participated and cannot be generalized to the larger population in the Faculty of Law.

Additionally, more than half of the researchers in Arts (20/38=53%), Education (5/7=71%), and

Management (5/6=83%) identified themselves as digital scholars; only 28% (13/46) of the researchers in

Social Sciences identified themselves as digital scholars.

13

5

3

5

20

20

1

1

15

13

1

3

0 5 10 15 20 25 30 35 40 45 50

Social Sciences

Management

Law

Education

Arts

Number of Responses

Facu

lty

Yes

No

Not Sure

Figure 19 Type of research data generated or used in Digital Scholarship. Comparing the applicable types of

research data generated or used in a typical research project by researchers who identified as a digital

humanist/scholar (n=46).

The three most common types of research data generated or used in Digital Scholarship/Digital

Humanities (Figure 19) were similar to those generated or used in the overall survey sample population

(Figure 2): text, multimedia and numerical. However, multimedia data was cited as the second most

frequently generated or used in Digital Scholarship, while in the overall survey sample population

numerical data was the second most frequently generated or used data type. These results suggest that

support for multimedia data may be needed more frequently among digital scholars/digital humanists

compared to other researchers.

Figure 20 Type of data used in digital humanities/digital scholarship research. Survey participants who identified

as digital scholars/digital humanists were asked to identify the type of data they use (n=46).

1

3

4

6

6

20

28

43

0 10 20 30 40 50

Discipline specific (e.g. BAM, fastq, CEL, IDAT, FASTA, PBD, ENT,…

Instrument specific (e.g. fMRI, Olympus Confocal Microscope…

Other

Geospatial - (e.g. raster, vector, grid, boundary files)

Models – (e.g. 3D, statistical, similitude, macroeconomic, causal)

Software– (e.g. Java, C, Perl, Python, Ruby, PHP, R)

Numerical – (e.g. CSV, MAT, XLS, SPSS)

Multimedia (e.g. JPEG, TIFF, MPEG, MP3, Quicktime, Bitmap,…

Text - (e.g. TXT, DOC, PDF, RTF, HTML, XML)

Number of Responses

Dat

a Ty

pe

9

10

16

32

25

41

0 5 10 15 20 25 30 35 40 45

Other

Encoded textual data

Editions or translations of texts

Born digital texts or images

Digitized texts or images of unpublished works

Digitized texts or images of published works

Number of Responses

Dat

a Ty

pe

The 46 respondents who identified themselves as digital scholars/digital humanists were also asked to

specify the type of data they used in their research in more detail. Figure 20 shows that the most

frequently used type of data were digitized texts or images of published works, born digital texts or

images and digitized texts or images of unpublished works. Further research and analysis are required to

determine whether digitization of physical records is a data service that would be of interest to digital

scholars/digital humanists.

Figure 21. Amount of storage in relation to number of research projects in Digital Scholarship. Summary of the

estimated amount of storage digital scholars/digital humanists use in an average research project as well as the

number of research projects they lead in the past year (n=46).

Figure 21 illustrates the relationship between storage volume required for the average research project

and the number of projects led by the digital scholar/digital humanist in the past year. At the time of the

survey, the majority of DH research projects required less than 50 GB of storage (26/46=57%).

Generally, digital scholars/digital humanists required less data storage compared to the overall survey

sample population, where the majority of research projects required less than 1000 GB of storage

(Figure 1). However, digital scholars/digital humanists were even more uncertain of how much storage

they used in an average project: 24% (11/46) compared to 18% of the overall survey sample population

(Figure 1).

1

6

1

2

7

8

1

1

1

1

1

6

1

1

1

4

1

1

1

0 2 4 6 8 10 12 14 16

Not Applicable, please explain:

Not sure

> 4TB


500GB to < 1000GB

50GB to < 500GB

10GB to < 50GB

1GB to < 10GB

< 1GB (Gigabyte)

Number of Responses

Sto

rage

Vo

lum

e fo

r A

vera

ge R

esea

rhc

Pro

ject



>5 research projects

Not applicable

Figure 22. Comparison of current methods and future intentions of sharing research data in Digital Scholarship.

Digital scholars/digital humanists (n=46) selected all the applicable methods of sharing research data they

currently use and would consider using in the future.

Figure 22 compares current methods and future intentions of sharing research data among digital

scholars/digital humanists at the time of the survey. The results indicated that trends in current practices

and future considerations were similar to those seen in the overall survey sample population (Figure 8).

Digital scholars/digital humanists indicated an increased interest in sharing their data in the future and

that share by personal request was the most popular method of data sharing when the survey was

conducted.

However, there were two notable differences in other data sharing methods used by digital

scholars/digital humanists compared to the overall survey sample population. Firstly, the percentage of

digital scholars/digital humanists who used the institutional data repository (Dataverse) as a current

method of data sharing was larger than the overall survey sample population with 13% (6/46) of digital

scholars/digital humanists using Dataverse compared to 7% of the overall survey sample population.

Secondly, the increase in interest in using an institutional or personal website to share data in the future

was larger among digital scholars/digital humanists from 7% to 35% compared to the overall survey

sample population (from 11% to 28%).

11

23

14

3

6

8

5

28

20

16

1011

2

0

5

10

15

20

25

30

Nu

mb

er o

f R

esp

on

ses

Methods of Sharing Research Data

Current methods of sharing research data

Future intentions of sharing research data

Figure 23. Reasons digital scholars/digital humanists would not share research data. Digital scholars/digital

humanists indicate all applicable reasons why they would not be willing to share their research data and

associated methods/tools (N=45).

Reasons why digital scholars/digital humanists would not be willing to share their research data and

associated methods/tools (Figure 23) follow the same trends as the overall survey sample population

(Figure 12). Incomplete or not finished data; privacy, legal or security issues; and the wish to derive

value from their data were cited as the primary reasons they would not be willing to share. The

percentage of digital scholars/digital humanists who were willing to share their data (10/46=22%) is

similar to the overall survey sample population (25%).

Conclusions At the time of the survey’s dissemination (2016-2017), there was limited information about RDM

practices or attitudes among uOttawa researchers. The Tri-Agencies had released their Statement of

Principles on Digital Data Management and the research community anticipated a Tri-Agency policy on

Research Data Management would soon follow. Librarians conducting this survey set out to address

their knowledge gap by determining how uOttawa researchers in different disciplines were managing

and sharing their research data and how the uOttawa Library might help to facilitate research data

management activities in the future.

The key findings of the survey suggest that researchers, irrespective of discipline, indicate gaps in their

RDM knowledge and may benefit from additional training and support to effectively manage their data

and meet Tri-Agency RDM policy requirements. Specifically, researchers expressed interest in making

use of a data repository associated with the University Ottawa, such as Dataverse, and in receiving

guidance in the preparation of data management plans. The survey findings also imply that researchers

could benefit from assistance with navigating RDM and research ethics policies as well as data

documentation for reuse and reproducibility.

In addition, survey results point to a gap in infrastructure that facilitates collaboration, including

international collaborations that may be subject to multiple RDM policies, and education and training in

the essentials of research data management for students as the next generation of researchers.

218

112

922

16

56

73

157

810

0 2 4 6 8 10 12 14 16 18 20

Other

Still wish to derive value

Do not hold rights to share

I believe they should not be shared

Insufficient time

Lack of funding

Not useful to others

Could potentially be used without proper citation

I am willing to share

Number of Responses

Rea

son

s fo

r N

ot

Shar

ing

Dat

a

Limitations of the Survey Results Although the survey has revealed interesting insights and trends into the RDM practices and attitudes of

uOttawa researchers, the low response rate and lack of statistical significance limit the interpretation of

the results. Survey findings cannot be applied to the larger uOttawa academic community without

further research, particularly in Law and Medicine where the survey sample populations only represent

2% of the target populations.

Additionally, the iterative process of developing and modifying the questionnaires led to errors and

inconsistent terminology appearing in the survey that respondents may have found confusing. The

question related to data storage for example, presented the stages of research data as: raw data,

manipulated data (e.g. converted, curated, processes), and archived data (e.g. long-term storage or

preservation). However, in a question that appeared later in the survey asking researchers how long they

keep their data, the stages of research data were presented as: source material/raw data,

intermediate/working data, and processed data ready for publication, which may include supporting

information such as metadata and documentation.

Another challenge of conducting a multi-institutional study was the terminology used to describe

institutional repositories and institutional Dataverses of the Scholars Portal Dataverse. At the time of the

survey, institutional branding and support for users of the Scholars Portal Dataverse9 were still in

development. As a result, there wasn’t a clear consensus on how to describe Dataverse to local academic

communities. At some Canadian institutions, Dataverse was presented as an institutional repository for

data, while other institutions were promoting Dataverse as a data repository platform and still others

were not using Dataverse at all. The survey presented Dataverse as an example of an institutional

repository for data sharing, which was a bias towards institutions that were using Dataverse as an

institutional data repository.

Furthermore, the RDM landscape at uOttawa has continued to evolve since the survey was conducted in

2016-2107. The survey reflected the priorities at the time: data storage, data sharing, DMPs and interest

in RDM services. More nuanced or particular aspects of RDM were not included in the survey. For

example, the survey did not address best practices in data backups and/or the prevention of data loss,

awareness of RDM national and/or international RDM policies. As a result, the findings in this report

provide a historical snapshot of the RDM landscape at uOttawa and may have limited practical use in

shaping RDM support and services moving forward.

Future Directions The survey findings provide information about researcher RDM practices at uOttawa that may serve to

inform institutional policy, services, and infrastructure development that are aligned with funding

agency requirements and effective data stewardship practices. Furthermore, this survey is part of a larger

project with the Canadian RDM Survey Consortium, which aims to provide a national view of the RDM

landscape in Canada by compiling survey data collected by participating members. The results of the

Consortium’s efforts will provide insights into trends in RDM practices across the country and will

enable comparisons of unique practices and attitudes between disciplines and regions.

9 https://dataverse.scholarsportal.info/

https://dataverse.scholarsportal.info/

Appendix Survey Question: Which funding sources have you used within the past 5 years, or are planning to apply for in the next 5 years? Please exclude funding earmarked exclusively for operations and infrastructure. Select all that apply:

Funding sources in the Faculty of Arts.

Other funding sources specified:

• Travel grants (APTPUO)

• ArcticNet, MEOPAR

• Educational Testing Services

• external funds (fellowships funded by other governments)

• Private donors and foundations outside this list

• grants for organizations such as Access Copyright Foundation and the Bibliographical Society of Canada

• Government contracts (IRCC), research funding from Pathways to Prosperity and the Centre for Research and Education on Women and Work at Carleton U.

• Canada Council Grants

• FQRSC Postdoc

• Bourse post-doctorale Fonds de recherche Société et culture du Québec

• City of Ottawa public funding campagne

• Financement externe BAnQ

• Ministère de l’Éducation

• Chaire de recherche de l'Université

• Fonds de développement de l'APTPUO

16

20

13

2

5

8

1

2

1

2

2

2

5

3

4

0 5 10 15 20 25

Other

SSHRC Insight Grant

SSHRC Insight Development Grant

SSHRC Partnership Grant

SSHRC Partnership Development Grant

SSHRC Connection Grant

SSHRC Knowledge Synthesis Grant

SSHRC Postdoctoral Fellowship

CIHR

CFI

NSERC

Industry

uOttawa Seed Funding Opportunity

uOttawa Bridge Funding Opportunity

None

Number of Responses

Fun

din

g So

urc

e

Funding sources in the Faculty of Education.

Other funding source specified: School Board funding.

Funding sources in the Faculty of Engineering.

Other funding sources specified: NSERC CRD, Ontario Research Fund, Mitacs Postdoctoral Fellowship

1

5

6

2

4

4

2

1

2

2

1

0 1 2 3 4 5 6 7

Other

SSHRC Insight Grant






CFI

Industry



Number of Responses

Fun

din

g So

urc

e

3111

21

22

67

21

64

9111

142

32

62

0 2 4 6 8 10 12 14 16

Other

Canadian Space Agency

Environment Canada

NCE: Arcticnet

NCE: Canadian Institute for Photonic Innovations

NCE: Carbon Management Canada

United States National Science Foundation (NSF)

Canadian Institute of Advanced Research

CIHR

CFI

SSHRC

NSERC Postdoctoral Fellowship

NSERC: Collaborative Health Research Project

DND - NSERC Research Partnership Program

NSERC: Engage Grants (EG) Program

NSERC: Idea to Innovation (I2I)

NSERC: Strategic Grants (Individual & Group)

NSERC: Strategic Research Networks

NSERC: Discovery Grant

NSERC: CREATE Program Grant

NSERC: Discovery Accelerator Supplement

NIH

Industry


Number of Responses

Fun

din

g So

urc

e

Funding sources in the Faculty of Health Sciences.

Other funding source specified:

• OCHSU, CHEO, IASP

• Consortium national de formation en santé, Action for Hearing Loss (International)

• Fondations ou associations (ex. diabète, diétÈtique)

• Fondations professionnelles

Funding sources in the Faculty of Law.

Other funding source specified: Law Foundation of Ontario.

4

6

1

5

1

2

5

3

1

3

1

0 1 2 3 4 5 6 7

Other

CIHR Project Grant Program

CIHR Foundation Grant

CIHR Initiatives: Strategic Initiatives

CFI

SSHRC

NSERC

Industry



None

Number of Responses

Fun

din

g So

urc

e

1

2

1

1

2

1

1

0 0.5 1 1.5 2 2.5

Other

SSHRC Insight Grant




CIHR


Number of Responses

Fun

din

g So

urc

es

Funding sources in the Faculty of Management.

Other funding sources specified: Financement Telfer, Privées, International foundation grant (Germany).

3

4

5

1

1

1

1

2

2

0 1 2 3 4 5 6

Other

SSHRC Insight Grant





Industry



Number of Responses

Fun

din

g So

urc

e

Funding sources in the Faculty of Medicine.


• Medical Council of Canada, Royal College of Physicians and Surgeons of Canada, TOHAMO

• Medical foundations; Private foundations

• AMS/Phoenix

• Chemical Management Plan, Health Canada

• International Development Research Centre project grant

• Cancer Research Society

• Heart and Stroke Foundation

• Royal College of Physicians and Surgeons of Canada Medical Education Research Grants

• Association Française contre les Myopathies (AFM)

9

3

2

14

6

4

5

4

2

8

1

3

3

4

0 2 4 6 8 10 12 14 16

Other

CIHR Vanier Canada Graduate Scholarships

CIHR Banting Postdoctoral Fellowships

CIHR Project Grant Program

CIHR Foundation Grant

CIHR Initiatives: Signature Initiatives

CIHR Initiatives: Strategic Initiatives

CFI

SSHRC

NSERC

NIH

Industry


None

Number of Responses

Fun

din

g So

urc

e

Funding sources in the Faculty of Science.


• Contrats de recherche Ville d'Ottawa,

• US Government

• Canada Research Chairs Program

• Natural Resources Canada, Canadian Nuclear Safety Commission

• Funding from my supervisor.

• ERA: Early Researcher Award (Ontario)

• Gates Foundation

7

3

1

4

8

2

2

2

2

1

1

1

15

6

1

0 2 4 6 8 10 12 14 16

Other

United States National Science Foundation (NSF)

Canadian Institute of Advanced Research

CIHR

CFI

SSHRC

NSERC Postdoctoral Fellowship

NSERC: Collaborative Health Research Project

NSERC: Engage Grants (EG) Program

NSERC: Idea to Innovation (I2I)

NSERC: Strategic Grants (Individual & Group)

NSERC: Strategic Research Networks

NSERC: Discovery Grant

NSERC: Discovery Accelerator Supplement

Industry

Number of Responses

Fun

din

g So

urc

e

Funding sources in the Faculty of Social Sciences.


• Ontario Centres of Excellence

• French government/EU funding

• Alzheimer Society of Canada

• NSERC Equipment Grant

• CNFS

• Banting

• Fondation Chiang Ching-kuo, foundation indo-canadienne Shastri,

• Fond de development professionel U Ottawa

• CNFS UOttawa et CNFS Secrétariat National

9

19

16

7

10

11

8

9

4

9

3

6

1

5

0 2 4 6 8 10 12 14 16 18 20

Other

SSHRC Insight Grant





SSHRC Postdoctoral Fellowship

CIHR

CFI

NSERC

Industry



None

Number of Responses

Fun

din

g So

urc

e

Survey Question: How much data storage do you estimate you use in an average research project? Select one:

Amount of storage used in each Faculty.

2

12

1

1

1

4

4

10

4

3

3

1

1

1

4

5

9

3

2

1

1

2

1

1

1

1

1

1

2

2

4

1

3

2

3

5

4

1

2

3

2

5

10

2

9

2

3

3

7

8

12

1

0 5 10 15 20 25 30 35

Not Applicable

Not sure

> 4TB

4TB to 500TB


1TB to < 4TG (Terabyte)

500GB to < 1000GB

50GB to < 500GB

< 50GB (Gigabyte)

10GB to < 50GB

1GB to < 10GB

< 1GB (Gigabyte)

Number of Responses

Sto

rage

Vo

lum

e fo

r A

vera

ge R

esea

rch

Pro

ject

Arts

Education

Engineering

Health Sciences

Law

Management

Medicine

Science

Social Sciences

Not Declared

Survey Question: Which of the following best describes the type of research data you generate or use in a typical research project? Select all that apply:

Text

- (

e.g.

TX

T, D

OC

, PD

F, R

TF, H

TML,

XM

L)

Nu

mer

ical

– (

e.g.

CSV

, MA

T, X

LS, S

PSS

)

Mu

ltim

edia

(e.

g. J

PEG

, TIF

F, M

PEG

, MP

3, Q

uic

ktim

e, B

itm

ap, A

ud

io/V

isu

al

reco

rds)

Mo

del

s –

(e.g

. 3D

, sta

tist

ical

, sim

ilitu

de,

mac

roec

on

om

ic, c

ausa

l)

Soft

war

e–

(e.g

. Jav

a, C

, Per

l, P

yth

on

, Ru

by,

PH

P, R

)

Inst

rum

ent

spec

ific

(e.

g. f

MR

I, O

lym

pu

s C

on

foca

l Mic

rosc

op

e D

ata

Form

at,

FLIR

Infr

ared

Cam

era

(SE

Q))

Geo

spat

ial -

(e.

g. r

aste

r, v

ecto

r, g

rid

, bo

un

dar

y fi

les)

Dis

cip

line

spec

ific

(e.

g. B

AM

, fas

tq, C

EL, I

DA

T, F

AST

A, P

BD

, EN

T, B

RK

, CIF

, FIT

S,

DIC

OM

)

Oth

er

Arts 37 13 21 3 2 1 3 4

Education 7 3 6 3

Engineering 16 14 10 8 7 5 1

Health Sciences 9 8 4 2 1 4

Law 3 3 1

Management 6 3 4 1 2

Medicine 19 18 17 7 5 9 1 7 2

Science 15 17 13 7 9 7 3 3

Social Sciences 38 22 22 9 5 4 3 4

Not Declared 1 1 1 1

Survey Question: Please indicate where you store research data from your current project(s). Select all that apply:

Data storage used in the Faculty of Arts.

Data storage used in the Faculty of Education.

1

19

4

23

21

17

2

5

14

1

15

1

18

3

26

20

19

6

17

10

2

7

15

24

20

22

1

5

11

1

11

0 10 20 30 40 50 60 70 80

Not Sure

USB

CD

Computer Hard Drive

Laptop

External Hard Drive


Shared Drive

Cloud Storage



Physical Copy

Number of Responses

Sto

rage

Med

ium

Raw Data

Manipulated Data

Archived Data

0

5

1

5

6

6

2

5

2

0

4

5

4

5

2

4

2

3

4

4

4

1

3

1

0 2 4 6 8 10 12 14 16

Not Sure

USB

CD

Computer Hard Drive

Laptop

External Hard Drive


Shared Drive

Cloud Storage



Physical Copy

Number of Responses

Sto

rage

Med

ium

Raw Data

Manipulated Data

Archived Data

Data storage used in the Faculty of Engineering.

Data storage used in the Faculty of Health Sciences.

0

8

1

13

10

11

6

8

10

4

2

4

4

12

9

10

3

6

7

2

1

3

1

6

10

9

10

2

6

6

4

3

0 5 10 15 20 25 30 35 40

Not Sure

USB

CD

Computer Hard Drive

Laptop

External Hard Drive


Shared Drive

Cloud Storage



Physical Copy

Number of Responses

Sto

rage

Med

ium

Raw Data

Manipulated Data

Archived Data

0

6

6

7

7

2

7

3

1

5

0

5

6

6

6

2

6

3

1

2

1

4

6

6

6

1

7

2

1

3

0 5 10 15 20 25

Not Sure

USB

CD

Computer Hard Drive

Laptop

External Hard Drive


Shared Drive

Cloud Storage



Physical Copy

Number of Responses

Sto

rage

Med

ium

Raw Data

Manipulated Data

Archived Data

Data storage used in the Faculty of Law.

Data storage used in the Telfer School of Management.

0

2

1

2

2

3

1

2

0

1

1

1

1

2

1

1

1

1

1

2

0 1 2 3 4 5 6 7 8

Not Sure

USB

CD

Computer Hard Drive

Laptop

External Hard Drive


Shared Drive

Cloud Storage



Physical Copy

Number of Responses

Sto

rage

Med

ium

Raw Data

Manipulated Data

Archived Data

0

4

1

3

5

2

1

1

2

0

5

1

3

4

2

1

2

1

3

4

2

4

5

2

1

1

0 2 4 6 8 10 12 14

Not Sure

USB

CD

Computer Hard Drive

Laptop

External Hard Drive


Shared Drive

Cloud Storage



Physical Copy

Number of Responses

Sto

rage

Med

ium

Raw Data

Manipulated Data

Archived Data

Data storage used in the Faculty of Medicine.

Data storage used in the Faculty of Science.

0

11

14

15

15

8

18

6

1

1

7

0

11

15

17

16

3

17

10

2

1

4

2

6

9

17

18

2

16

7

6

5

0 10 20 30 40 50 60

Not Sure

USB

CD

Computer Hard Drive

Laptop

External Hard Drive


Shared Drive

Cloud Storage



Physical Copy

Number of Responses

Sto

rage

Med

ium

Raw Data

Manipulated Data

Archived Data

0

8

14

14

14

4

7

8

2

2

3

0

8

14

13

12

1

6

10

2

2

2

5

9

13

14

7

5

2

1

1

0 5 10 15 20 25 30 35 40 45

Not Sure

USB

CD

Computer Hard Drive

Laptop

External Hard Drive


Shared Drive

Cloud Storage



Physical Copy

Number of Responses

Sto

rage

Med

ium

Raw Data

Manipulated Data

Archived Data

Data storage used in the Faculty of Social Sciences.

26

4

32

31

33

9

11

20

1

19

1

23

3

28

29

29

3

11

17

8

6

17

23

29

33

5

11

17

2

1

11

0 10 20 30 40 50 60 70 80 90 100

Not Sure

USB

CD

Computer Hard Drive

Laptop

External Hard Drive


Shared Drive

Cloud Storage



Physical Copy

Number of Responses

Sto

rage

Med

ium

Raw Data

Manipulated Data

Archived Data

Survey Question: Use the chart below to indicate the length of time after project completion that you typically intentionally keep each type of research data. Project completion could include until publication, for example.

Length of Time Research Data are Kept in the Faculty of Arts.

Length of Time Research Data are Kept in the Faculty of Education.

20

8

4

5

2

21

7

4

3

2

22

6

6

2

0 10 20 30 40 50 60 70


More than 10 years

Between 5-10 years

Between 3-5 years

Less than 3 years


Number of Responses

Len

gth

of

Tim

e D

ata

are

Kep

t

Raw Data

Intermediate Data

Archived Data

4

2

1

0

0

0

3

2

2

0

0

0

4

2

1

0 2 4 6 8 10 12


More than 10 years

Between 5-10 years

Between 3-5 years

Less than 3 years


Number of Responses

Len

gth

of

Tim

e D

ata

are

Kep

t

Raw Data

Intermediate Data

Archived Data

Length of Time Research Data are Kept in the Faculty of Engineering.

8

2

3

5

2

8

1

2

6

2

1

8

3

3

4

2

0 5 10 15 20 25 30


More than 10 years

Between 5-10 years

Between 3-5 years

Less than 3 years


Number of Responses

Len

gth

of

Tim

e D

ata

are

Kep

t

Raw Data

Intermediate Data

Archived Data

Length of Time Research Data are Kept in the Faculty of Health Sciences.

Length of Time Research Data are Kept in the Faculty of Law.

2

1

4

3

2

3

4

1

1

3

2

3

1

0 2 4 6 8 10 12


More than 10 years

Between 5-10 years

Between 3-5 years

Less than 3 years


Number of Responses

Len

gth

of

Tim

e R

esea

rch

Dat

a ar

e K

ept

Raw Data

Intermediate Data

Archived Data

1

1

1

1

1

1

1

1

1

0 1 2 3 4


More than 10 years

Between 5-10 years

Between 3-5 years

Less than 3 years


Number of Responses

Len

gth

of

Tim

e D

ata

are

Kep

t

Raw Data

Intermediate Data

Archived Data

Length of Time Research Data are Kept in the Faculty of Management.

Length of Time Research Data are Kept in the Faculty of Medicine.

2

1

2

1

3

1

1

1

2

1

2

1

0 1 2 3 4 5 6 7 8


More than 10 years

Between 5-10 years

Between 3-5 years

Less than 3 years


Number of Responses

Len

gth

of

TIm

e D

ata

are

Kep

t

Raw Data

Intermediate Data

Archived Data

8

8

4

3

7

6

6

3

1

9

6

5

3

0 5 10 15 20 25 30


More than 10 years

Between 5-10 years

Between 3-5 years

Less than 3 years


Number of Responses

Len

gth

of

Tim

e D

ata

are

Kep

t

Raw Data

Intermediate Data

Archived Data

Length of Time Research Data are Kept in the Faculty of Science.

Length of Time Research Data are Kept in the Faculty of Social Sciences.

14

3

1

3

1

12

4

1

1

4

15

6

1

0 10 20 30 40 50


More than 10 years

Between 5-10 years

Between 3-5 years

Less than 3 years


Number of Response

Len

gth

of

Tim

e D

ata

are

Kep

t

Raw Data

Intermediate Data

Archived Data

14

8

15

3

1

5

13

8

15

5

2

3

16

9

14

5

2

0 10 20 30 40 50


More than 10 years

Between 5-10 years

Between 3-5 years

Less than 3 years


Number of Responses

Len

gth

of

Tim

e D

ata

are

Kep

t

Raw Data

Intermediate Data

Archived Data

Survey Question: Which methods of sharing your research data do you currently use? Select all that apply. If you do not currently share your data, choose ‘not currently sharing’.

No

t cu

rren

tly

shar

ing

Pe

rso

nal

req

ues

t o

nly

On

line

wit

h r

estr

icte

d a

cces

s

Inst

itu

tio

nal

or

per

son

al w

ebsi

te

Inst

itu

tio

nal

rep

osi

tory

, su

ch a

s D

atav

erse

Sup

ple

men

tary

file

s to

jou

rnal

Gen

eral

or

dis

cip

line

-sp

ecif

ic r

epo

sito

ry

Arts 12 20 8 4 4 4 1

Education 1 3 4 1 1

Engineering 7 9 3 5 1 3

Health Sciences 2 6 3 1 3 2

Law 1 1 1 1 1

Management 5 1 1

Medicine 3 15 6 2 2 13 6

Science 3 12 5 4 12 6

Social Sciences 20 21 8 2 3 5 1

Not Declared 1 1

Survey Question: Hypothetically speaking, which methods of sharing your research data would you consider using in the future? Select all that apply. If you do not plan to share your data in the future choose ‘not planning to share'.

No

t p

lan

nin

g to

sh

are

Shar

e b

y p

erso

nal

req

ues

t

On

line

wit

h r

estr

icte

d a

cces

s

Inst

itu

tio

nal

or

per

son

al w

ebsi

te

Inst

itu

tio

nal

rep

osi

tory

, su

ch a

s D

atav

erse

Sup

ple

men

tary

file

s to

jou

rnal

Gen

eral

or

dis

cip

line

-sp

ecif

ic r

epo

sito

ry

Arts 5 23 15 14 7 7 2

Education 6 4 3 2 2 1

Engineering 2 13 6 7 4 4 6

Health Sciences 1 6 6 2 6 3 1

Law 1 1 1 2 1

Management 5 2 2 1

Medicine 1 11 9 7 11 12 9

Science 11 8 7 6 14 9


Not Declared 1 1

Survey Question: Some research data cannot be shared because of legal or privacy restrictions or embargoes. Which of the following restrictions or embargoes may limit your ability to share your data with others? Select all that apply. If there are no restrictions or embargoes, choose ‘there are no restrictions or embargoes on sharing my data with other parties’.

No

res

tric

tio

ns

or

emb

argo

es

Pu

blic

saf

ety

or

sen

siti

ve n

atu

re

Pri

vacy

, co

nfi

den

tial

ity,

or

eth

ics

rest

rict

ion

s

Co

ntr

actu

al o

blig

atio

n

Co

mm

erci

al c

on

cern

s

I pla

n t

o f

ile f

or

a p

aten

t

May

jeo

par

diz

e in

telle

ctu

al p

rop

erty

rig

hts

I nee

d t

o p

ub

lish

my

dat

a fi

rst

I'm u

nsu

re if

I am

allo

wed

to

sh

are

my

dat

a

Oth

er

Arts 16 1 12 2 1 7 10 4 5

Education 5 1 2

Engineering 6 4 5 2 3 4 10 1

Health Sciences 3 4 2 2 1

Law 2 1

Management 2 2 2 2

Medicine 1 10 4 3 5 7 15 2

Science 7 3 1 1 5 11 1

Social Sciences 7 4 25 7 1 6 14 6 3

Not Declared 1

Survey Question: If your research data were not affected by restrictions or embargoes, with whom would you be willing to share them? Select all that apply:

No

bo

dy

Imm

edia

te c

olla

bo

rato

rs

Res

earc

her

s in

my

dep

artm

ent

Res

earc

her

s at

uO

ttaw

a

Res

earc

her

s in

my

fiel

d

Res

earc

her

s o

uts

ide

my

fiel

d

An

ybo

dy,

incl

ud

ing

the

gen

eral

pu

blic

Arts 2 13 9 7 19 6 20

Education 5 3 3 3 1 3

Engineering 1 8 1 2 5 1 9

Health Sciences 1 8 4 3 6 1 1

Law 1 1 1 1 3

Management 6 4 3 4 2

Medicine 17 12 8 12 9 5

Science 9 4 3 10 1 9


Not Declared

Survey Question: What, if any, are the reasons you would not be willing to share your research data and associated methods/tools? Select all that apply. If you are willing to share, choose ‘I am willing to share them’.

I am

will

ing

to s

har

e

Inco

mp

lete

or

no

t fi

nis

hed

Still

wis

h t

o d

eriv

e va

lue

Do

no

t h

ave

tech

nic

al s

kills

or

kno

wle

dge

Do

no

t h

old

rig

hts

to

sh

are

Fun

din

g b

od

y d

oe

s n

ot

req

uir

e sh

arin

g

I bel

ieve

th

ey s

ho

uld

no

t b

e sh

are

d

I did

no

t kn

ow

I co

uld

sh

are

Insu

ffic

ien

t ti

me

Lack

of

stan

dar

ds

Lack

of

fun

din

g

No

pla

ce t

o p

ut

them

No

t u

sefu

l to

oth

ers

Pri

vacy

, leg

al o

r se

curi

ty c

on

cern

s

Co

uld

po

ten

tial

ly b

e u

sed

wit

ho

ut

pro

per

ci

tati

on

M

y d

ata

cou

ld p

ote

nti

ally

be

mis

use

d

Oth

er

Arts 11 11 6 1 9 1 2 2 4 4 4 3 3 9 9 6 4

Education 1 1 2 1 2 3 2 1 1 3 4 1 2

Engineering 11 5 5 1 3 3 3 1 1 1 3 3 3

Health Sciences

4 4 2 2 1 1 1 1 2 3 3 1

Law 1 2 1 1 1

Management 2 2 2 1 1 1 1 1 1 1 1

Medicine 7 5 6 2 5 2 1 6 4 3 5 1 9 7 3 2

Science 4 9 8 1 2 1 1 6 6 4 1 4 3 8 5 2

Social Sciences

3 14 12 6 6 4 6 2 9 4 5 3 2 24 11 13 2

Not Declared

Survey Question: What benefits do you see to sharing your research data? Select all that apply. If you see no benefits, choose ‘I see no benefits to sharing my data’.

No

ben

efit

s

Safe

guar

ds

agai

nst

mis

con

du

ct

Trai

nin

g n

ext

gen

erat

ion

res

earc

her

s

Enab

les

my

dat

a to

be

cite

d

Stre

ngt

hen

s m

y ac

adem

ic p

ort

folio

Incr

ease

d m

y ab

ility

to

ob

tain

fu

nd

ing

Enco

ura

ges

colla

bo

rati

ve s

cho

lars

hip

Enco

ura

ges

inte

rdis

cip

linar

y re

sear

ch

Mo

ves

my

fiel

d o

f re

sear

ch f

orw

ard

Red

uce

s re

du

nd

ant

dat

a co

llect

ion

Sup

po

rts

op

en a

cces

s to

kn

ow

led

ge

Hel

ps

veri

fy r

esu

lts

Hel

p d

ata

inte

grit

y

Oth

er

Arts 5 7 24 20 12 11 25 24 27 15 25 12 10 2

Education 1 1 3 2 1 1 4 3 2 2 3 2 1

Engineering 3 8 10 10 7 5 15 10 8 7 10 10 6 1

Health Sciences 1 1 5 4 1 6 6 7 6 4 4 2 1

Law 1 3 2 1 2 2 1 1 2 1

Management 1 2 2 2 1 4 2 2 2 1 2 2

Medicine 1 13 10 12 8 7 15 14 17 15 15 14 8

Science 11 10 8 1 12 7 11 5 8 8 8 1

Social Sciences 8 21 27 20 6 7 26 17 17 13 19 15 12 1

Not Declared 1

Survey Question: Data management plans typically address questions about research data types and formats: standards to be used for describing data; ethics and legal compliance; plans for preservation, access, sharing, and reuse; and responsibilities assigned and resources needed. If you were asked to draft a data management plan as part of a grant application, which of the following statements would best describe your situation? Select one:

I wo

uld

be

able

to

dra

ft a

dat

a m

anag

emen

t p

lan

wit

ho

ut

assi

stan

ce

I wo

uld

nee

d a

ssis

tan

ce a

nd

/or

guid

ed d

ocu

men

tati

on

I wo

uld

pre

fer

to h

ave

assi

stan

ce a

nd

/or

guid

ed d

ocu

men

tati

on

Arts 7 17 13

Education 5 2

Engineering 4 12 3

Health Sciences 1 3 6

Law 1 2

Management 3 3

Medicine 3 11 9

Science 3 12 7

Social Sciences 7 19 19

Not Declared 1

Survey Question: Do you include any of the following topics related to RDM in your teaching practice? Select all that apply. If you do not teach RDM topics, choose ‘I do not teach RDM topics’.

I do

no

t te

ach

RD

M t

op

ics

Dat

a se

curi

ty

Dat

a p

riva

cy

Dat

a ve

rsio

n c

on

tro

l

Dat

a b

acku

p

Dat

a et

hic

s

Dat

a sh

arin

g

Dat

a d

ocu

men

tati

on

Dat

a re

ten

tio

n

Dat

a ar

chiv

ing

Oth

er

Arts 26 3 7 3 5 6 5 5 4 3 1

Education 4 2 2 2 1

Engineering 13 4 4 3 2 5 3 3 3 3 2

Health Sciences 7 2 3 2 2 1 2 2

Law 3

Management 3 1 2 1 1 3 1 1 1 1

Medicine 17 3 5 4 6 1 3 3 3

Science 16 1 2 3 1 1 4 1 1 2

Social Sciences 28 8 13 3 5 16 4 7 7 7 2

Not Declared 1

Report on the Faculty & Postdoctoral Survey on Research ......Felicity Tayler, E-Research Librarian,...

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Transcript of Report on the Faculty & Postdoctoral Survey on Research ......Felicity Tayler, E-Research Librarian,...