Table 1
Literature Citing Social Barriers to Data Reuse.
Table 2
Literature Citing Technical Barriers to Data Reuse.
| Issue | Literature Mentioned |
|---|---|
| Lack of data storage and support services | Akers & Doty 2013; Coetzee 2015; Fecher, Friesike, & Hebing 2015; Hsu et al. 2015; McLure et al. 2014; Michener 2015; Pepe et al. 2014; NAS 2009; Pericas, Taura & Matsuoka 2014; Sayogo & Pardo 2013 |
| Difficulties with accessing data | Enke et al. 2012; Hsu et al. 2015; Jin et al. 2015; RSSPC 2012; SI 2015; Specht et al. 2015; van Panhuis et al. 2014 |
| Lack of discoverability | Dallmeier-Tiessen et al. 2014; Elwood 2008; Enke et al. 2012; RSSPC 2012; SI 2015; Specht et al. 2015; Willibanks & Friend 2016 |
| Inability of researchers to control access to data | Dallmeier-Tiessen et al. 2014; Enke et al. 2012; Federer et al. 2015; Pepe et al. 2014; van Panhuis et al. 2014 |
| Inconsistent citation standards | Duke & Porter 2013; Nahar 2016; SI 2015; Wallis, Rolando & Borgman 2013; Wynholds et al. 2012 |
| Lack of metadata guidelines | Hsu et al. 2015; Michener 2015; Specht et al. 2015 |
Table 3
Literature Citing Legal Barriers to Data Reuse.
| Issue | Literature Mentioned |
|---|---|
| Differing government standards for archiving | Elwood 2008; Enke et al. 2012; Hodson & Molloy 2015; Michener 2015; NAS 2009; Piwowar & Chapman 2010; Specht et al. 2015; Treloar 2014; Wallis, Rolando & Borgman 2013; Wicherts, Bakker, & Molenaar 2011 |
| Government requirements for privacy | Coetzee 2015; Dallmeier-Tiessen et al. 2014; Hodson & Molloy 2015; NAS 2009; RSSPC 2012; Sayogo & Pardo 2013; SI 2015 |
| No ability to track down original source of data | Fecher, Friesike, & Hebing 2015; NAS 2009; RSSPC 2012; Sayogo & Pardo 2013 |
Table 4
Study Participants.
| Attributes | Data Consumers (n = 3) | Data Managers (n = 5) | Data Producers (n = 5) |
|---|---|---|---|
| Occupation | 1 – Professor 2 – Research Scientists | 4 – Research Scientists 1 – Software Engineer | 3 – Research Scientists 2 – Post-Doctoral Fellows/Researchers |
| Field | 3 – Research | 3 – Government 1 – Research | 5 – Government |
| Experience Using Neutron Data | 1 – 5–10 years 2 – Over 10 years | 1 – 1–4 years 1 – 5–10 years 3 – Over 10 years | 1 – 1–4 years 2 – 5–10 years 2 – Over 10 years |
| Experience Using ORNL Facilities | 1 – Less than 1 year 1 – 5–10 years 1 – Over 10 years | 1 – Less than 1 year 3 – 5–10 years 1 – Over 10 years | 2 – 1–4 years 2 – 5–10 years 1 – Over 10 years |
Figure 1
The Consumers Managers Producers (CMP) Model. The CMP Model illustrates the flow of neutron data and the interactions of data consumers, data managers, and data producers with data at various stages of production at Oak Ridge National Laboratory (ORNL). Users are represented in blue, data are represented in red, and interactions between users and data are represented in green.
| Social Barriers |
|---|
| 1. Differences between disciplines in creating data |
| 2. Lack of incentives to share or reuse data |
| 3. Differences in quality of data for particular research purposes |
| 4. Lack of education about best practices |
| 5. Journals incentivize different kinds of data sharing |
| 6. Lack of standards for peer review of data |
| 7. Misuse of research data |
| 8. Competing interests of researchers |
| 9. Too much time required to share data |
| Technical Barriers |
|---|
| 10. Lack of data storage and support services |
| 11. Difficulties with accessing data |
| 12. Lack of discoverability |
| 13. Inability of researchers to control access to data |
| 14. Inconsistent citation standards |
| 15. Lack of metadata guidelines |
| Legal Barriers |
|---|
| 16. Differing government standards for archiving |
| 17. Government requirements for privacy |
| 18. No ability to track down original source of data |
Table 6
Barriers to data reuse mentioned in focus groups.
| Session | Barriers |
|---|---|
| Data Managers | 1, 3, 11, 13, 15 |
| Data Producers | 1, 3, 5, 7, 8, 9, 10, 11, 12 |
| Data Consumers | 1, 3, 15 |
| Wrap-up | 10, 11, 12, 14, 15 |
Table 7
Barriers common to multiple groups or unique to other groups.
| Issue | Mentioned by |
|---|---|
| Differences between disciplines in creating data (1) | Data Managers, Data Producers, Data Consumers |
| Differences in quality of data for particular research purposes (3) | Data Managers, Data Producers, Data Consumers |
| Journals incentivize different kinds of data sharing (5) | Data Producers |
| Lack of data storage and support (10) | Data Producers |
| Misuse of research data (7) | Data Producers |
| Competing interests of researchers (8) | Data Producers |
| Too much time required to share data (9) | Data Producers |
| Difficulties with accessing data (11) | Data Managers, Data Producers, Wrap-up |
| Lack of discoverability (12) | Data Producers, Wrap-Up |
| Inconsistent citation standards (14) | Wrap-Up |
| Lack of metadata guidelines (15) | Data Managers, Data Consumers, Wrap-Up |