References
-
1
AECOM.
(2012). Investigation into overheating in homes.
Literature review. AECOM with UCL and London School
of Hygiene and Tropical Medicine. Retrieved from
https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/7604/2185850.pdf - 2 Anvari, F., & Lakens, D. (2018). The replicability crisis and public trust in psychological science. Comprehensive Results in Social Psychology, 3(3), 266–286. DOI: 10.1080/23743603.2019.1684822
- 3 Baker, M., & Penny, D. (2016). Is there a reproducibility crisis? Nature, 533(May 26), 452–454. DOI: 10.1038/533452a
- 4 Ball, C. (2009). What is transparency? Public Integrity, 11(4), 293–308. DOI: 10.2753/PIN1099-9922110400
- 5 Banks, G. C., O’Boyle, E. H., Pollack, J. M., White, C. D., Batchelor, J. H., Whelpley, C. E., … Adkins, C. L. (2016a). Questions about questionable research practices in the field of management: A Guest commentary. Journal of Management, 42(1), 5–20. DOI: 10.1177/0149206315619011
- 6 Banks, G. C., Rogelberg, S. G., Woznyj, H. M., Landis, R. S., & Rupp, D. E. (2016b). Editorial: Evidence on questionable research practices: The good, the bad, and the ugly. Journal of Business and Psychology, 31, 323–338. DOI: 10.1007/s10869-016-9456-7
-
7
Barba,
L. A. (2018).
Terminologies for reproducible research.
ArXiv. Retrieved from
http://arxiv.org/abs/1802.03311 - 8 Begley, C. G., & Ellis, L. M. (2012). Drug development: Raise standards for preclinical cancer research. Nature, 483(7391), 531–533. DOI: 10.1038/483531a
- 9 Belcher, B. M., Rasmussen, K. E., Kemshaw, M. R., & Zornes, D. A. (2016). Defining and assessing research quality in a transdisciplinary context. Research Evaluation, 25(1), 1–17. DOI: 10.1093/reseval/rvv025
- 10 Budroni, P., Claude-Burgelman, J., & Schouppe, M. (2019). Architectures of knowledge: The European Open Science Cloud. ABI Technik, 39(2), 130–141. DOI: 10.1515/abitech-2019-2006
- 11 Button, K. S., Ioannidis, J. P. A., Mokrysz, C., Nosek, B. A., Flint, J., Robinson, E. S. J., & Munafò, M. R. (2013). Power failure: Why small sample size undermines the reliability of neuroscience. Nature Reviews Neuroscience, 14(5), 365–376. DOI: 10.1038/nrn3475
-
12
Center for Government
Excellence. (2016). Open data—Metadata
guide. Retrieved November 16, 2020, from
https://centerforgov.gitbooks.io/open-data-metadata-guide/content/ - 13 Chambers, C. D., Feredoes, E., Muthukumaraswamy, S. D., & Etchells, P. J. (2014). Instead of ‘playing the game’ it is time to change the rules: Registered reports at AIMS Neuroscience and beyond. AIMS Neuroscience, 1, 4–17. DOI: 10.3934/Neuroscience.2014.1.4
- 14 Chiarelli, A., Johnson, R., Pinfield, S., & Richens, E. (2019). Preprints and scholarly communication: An exploratory qualitative study of adoption, practices, drivers and barriers. F1000Research, 8, 971. DOI: 10.12688/f1000research.19619.2
-
15
Claesen,
A.,
Gomes, S. L. B.
T.,
Tuerlinckx,
F., &
Vanpaemel,
W. (2019).
Preregistration: Comparing dream to reality.
PsyarXiv. Retrieved from
https://psyarxiv.com/d8wex . DOI: 10.31234/osf.io/d8wex - 16 Collins, G. S., Reitsma, J. B., Altman, D. G., & Moons, K. G. M. (2015). Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): The TRIPOD statement. BMJ (Online), 350. DOI: 10.1136/bmj.g7594
- 17 Crüwell, S., & Evans, N. J. (2019). Preregistration in complex contexts: A preregistration template for the application of cognitive models. PsyArXiv. DOI: 10.31234/osf.io/2hykx
-
18
Day,
M. (2005).
DCC digital curation manual instalment on metadata
(November), 41. Retrieved from
http://www.dcc.ac.uk/resource/curation-manual/chapters/metadatahttp://www.ukoln.ac.uk/ - 19 Dickersin, K., Chan, S., Chalmers, T. C., Sacks, H. S., & Smith, H. (1987). Publication bias and clinical trials. Controlled Clinical Trials, 8(4), 343–353. DOI: 10.1016/0197-2456(87)90155-3
- 20 DuBois, J. M., Strait, M., & Walsh, H. (2018). Is it time to share qualitative research data? Qualitative Psychology, 5(3), 380–393. DOI: 10.1037/qup0000076
- 21 Easterbrook, S. M. (2014). Open code for open science? Nature Geoscience, 7, 779–781. DOI: 10.1038/ngeo2283
- 22 Eisner, D. A. (2018). Reproducibility of science: Fraud, impact factors and carelessness. Journal of Molecular and Cellular Cardiology, 114, 364–368. DOI: 10.1016/j.yjmcc.2017.10.009
-
23
Energy Research &
Social Science. (n.d.). Homepage.
Retrieved October 2, 2020, from
https://www.journals.elsevier.com/energy-research-and-social-science -
24
Equator Network.
(2016). EQUATOR reporting guideline decision tree:
Which guidelines are relevant to my work? Retrieved July 7, 2020,
from
https://www.equator-network.org/wp-content/uploads/2013/11/20160226-RG-decision-tree-for-Wizard-CC-BY-26-February-2016.pdf -
25
European Commission.
(2016a). G20 leaders’ communique Hangzhou
Summit. Retrieved from
https://ec.europa.eu/commission/presscorner/detail/en/STATEMENT_16_2967 -
26
European Commission.
(2016b). Guidelines on fair data management in Horizon
2020 (December
6). Retrieved from
http://ec.europa.eu/research/participants/data/ref/h2020/grants_manual/hi/oa_pilot/h2020-hi-oa-data-mgt_en.pdf -
27
European Commission.
(2018). Turning FAIR into Reality 2018: Final report
and action plan from the European Commission Expert Group on FAIR
Data. Retrieved from
https://doi.org/10.2777/54599 -
28
European Commission.
(n.d.). Clean energy for all Europeans package|Energy.
Retrieved October 1, 2020, from
https://ec.europa.eu/energy/topics/energy-strategy/clean-energy-all-europeans_en -
29
Eysenbach,
G. (2006).
The open access advantage. Journal of
Medical Internet Research, 8(2),
e8 . DOI: 10.2196/jmir.8.2.e8 - 30 Fell, M. J. (2019). The economic impacts of open science: A rapid evidence assessment. Publications, 7, 46. DOI: 10.3390/publications7030046
- 31 Ferguson, C. J., & Brannick, M. T. (2012). Publication bias in psychological science: Prevalence, methods for identifying and controlling, and implications for the use of meta-analyses. Psychological Methods, 17(1), 120–128. DOI: 10.1037/a0024445
- 32 Frankenhuis, W. E., & Nettle, D. (2018). Open science is liberating and can foster creativity. Perspectives on Psychological Science, 13(4), 439–447. DOI: 10.1177/1745691618767878
- 33 George, S. L. (2018). Research misconduct and data fraud in clinical trials: Prevalence and causal factors. Getting to Good: Research Integrity in the Biomedical Sciences, 21, 421–428. DOI: 10.1007/s10147-015-0887-3
- 34 Grant, M. J., & Booth, A. (2009). A typology of reviews: An analysis of 14 review types and associated methodologies. Health Information and Libraries Journal, 26, 91–108. DOI: 10.1111/j.1471-1842.2009.00848.x
-
35
Han,
S. H.,
Olonisakin, T.
F., Pribis,
J. P.,
Zupetic,
J.,
Yoon, J.
H., Holleran,
K. M., …
Lee, J.
S. (2017). A
checklist is associated with increased quality of reporting preclinical
biomedical research: A systematic review. PLoS
ONE, 12(9),
e0183591 . DOI: 10.1371/journal.pone.0183591 - 36 Hardwicke, T. E., Wallach, J. D., Kidwell, M. C., Bendixen, T., Crüwell, S., & Ioannidis, J. P. A. (2020). An empirical assessment of transparency and reproducibility-related research practices in the social sciences (2014–2017). Royal Society Open Science, 7(2), 190806. DOI: 10.1098/rsos.190806
- 37 Hirst, A., & Altman, D. G. (2012). Are peer reviewers encouraged to use reporting guidelines? A survey of 116 health research journals. PLoS ONE, 7. DOI: 10.1371/journal.pone.0035621
-
38
HM Government.
(2017). The Clean Growth Strategy: Leading the way to a
low carbon future. Retrieved from
https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/700496/clean-growth-strategy-correction-april-2018.pdf - 39 Hoy, M. B. (2020). Rise of the Rxivs: How preprint servers are changing the publishing process. Medical Reference Services Quarterly, 39(1), 84–89. DOI: 10.1080/02763869.2020.1704597
- 40 Huebner, G. M. & Mahdavi, A. (2019). A structured open data collection on occupant behaviour in buildings. Scientific Data, 6(1), 292. DOI: 10.1038/s41597-019-0276-2
-
41
Huebner,
G. M.,
Nicolson, M.
L., Fell,
M. J.,
Kennard,
H.,
Elam,
S.,
Hanmer,
C., …
Shipworth,
D. (2017).
Are we heading towards a replicability crisis in energy
efficiency research? A toolkit for improving the quality, transparency and
replicability of energy efficiency impact evaluations.
UCL Discovery, May,
1871–1880. Retrieved from
https://discovery.ucl.ac.uk/id/eprint/1561512/ - 42 Huston, P., Edge, V., & Bernier, E. (2019). Reaping the benefits of open data in public health. Canada Communicable Disease Report, 45(10), 252–256. DOI: 10.14745/ccdr.v45i10a01
-
43
IEA. (n.d.).
Global EV Outlook 2019: Scaling up the transition to electric
mobility. International Energy Agency
(IEA). Retrieved October 1, 2020, from
https://www.iea.org/reports/global-ev-outlook-2019 - 44 John, L. K., Loewenstein, G., & Prelec, D. (2012). Measuring the prevalence of questionable research practices with incentives for truth telling. Psychological Science, 23(5), 524–532. DOI: 10.1177/0956797611430953
- 45 Kerr, N. L. (1998). HARKing: Hypothesizing after the results are known. Personality and Social Psychology Review, 2(3), 196–217. DOI: 10.1207/s15327957pspr0203_4
- 46 Kjærgaard, M. B., Ardakanian, O., Carlucci, S., Dong, B., Firth, S. K., Gao, N., … Zhu, Y. (2020). Current practices and infrastructure for open data based research on occupant-centric design and operation of buildings. Building and Environment, 177, 106848. DOI: 10.1016/j.buildenv.2020.106848
- 47 Haven, T., & Van Grootel, D. L. (2019). Preregistering qualitative research. Accountability in Research, 26(3), 229–244. DOI: 10.1080/08989621.2019.1580147
- 48 Love, J., & Cooper, A. C. (2015). From social and technical to socio-technical: Designing integrated research on domestic energy use. Indoor and Built Environment, 24(7), 986–998. DOI: 10.1177/1420326X15601722
- 49 Macleod, M. R. (2017). Findings of a retrospective, controlled cohort study of the impact of a change in Nature journals’ editorial policy for life sciences research on the completeness of reporting study design and execution. BioRxiv, 187245. DOI: 10.1101/187245
- 50 Marshall, I. J., & Wallace, B. C. (2019). Toward systematic review automation: A practical guide to using machine learning tools in research synthesis. Systematic Reviews, 8, 163. DOI: 10.1186/s13643-019-1074-9
- 51 Mavrogianni, A., Davies, M., Taylor, J., Chalabi, Z., Biddulph, P., Oikonomou, E., … Jones, B. (2014). The impact of occupancy patterns, occupant-controlled ventilation and shading on indoor overheating risk in domestic environments. Building and Environment, 78, 183–198. DOI: 10.1016/j.buildenv.2014.04.008
- 52 McGrath, C., & Nilsonne, G. (2018). Data sharing in qualitative research: Opportunities and concerns. MedEdPublish, 7(4). DOI: 10.15694/mep.2018.0000255.1
- 53 Miguel, E., Camerer, C., Casey, K., Cohen, J., Esterling, K. M., Gerber, A., … Van der Laan, M. (2014). Promoting transparency in social science research. Science, 343(6166), 30–31. DOI: 10.1126/science.1245317
- 54 Moher, D., Liberati, A., Tetzlaff, J., & Altman, D. G. (2009). Preferred reporting items for systematic reviews and meta-analyses: The PRISMA statement. BMJ (Online), 339, 332–336. DOI: 10.1136/bmj.b2535
- 55 Moravcsik, A. (2014). Transparency: The revolution in qualitative research. PS—Political Science and Politics, 47(1), 48–53. DOI: 10.1017/S1049096513001789
-
56
MRC. (n.d.).
Good research practice. Medical Research
Council (MRC). Retrieved October 1, 2020, from
https://mrc.ukri.org/research/policies-and-guidance-for-researchers/good-research-practice/ - 57 Mueller-Langer, F., & Andreoli-Versbach, P. (2018). Open access to research data: Strategic delay and the ambiguous welfare effects of mandatory data disclosure. Information Economics and Policy, 42, 20–34. DOI: 10.1016/j.infoecopol.2017.05.004
- 58 Munafò, M. R., Nosek, B. A., Bishop, D. V. M., Button, K. S., Chambers, C. D., Percie du Sert, N., … Ioannidis, J. P. A. (2017). A manifesto for reproducible science. Nature Human Behaviour, 1(1), 0021. DOI: 10.1038/s41562-016-0021
- 59 National Academies of Sciences, Engineering, and Medicine. (2019). Reproducibility and replicability in science. National Academies Press. DOI: 10.17226/25303
- 60 National Academy of Sciences, National Academy of Engineering, & Institute of Medicine. (1992). Responsible science: Ensuring the integrity of the research process: Volume I. National Academies Press. DOI: 10.17226/1864
-
61
National Center for Dissemination
of Disability. (2005). What are the standards
for quality research? (Technical Brief No. 9). Retrieved from
http://ktdrr.org/ktlibrary/articles_pubs/ncddrwork/focus/focus9/Focus9.pdf - 62 Nature. (2016). Reality check on reproducibility. Nature, 533(May 25), 437. DOI: 10.1038/533437a
- 63 Nature. (2018). Checklists work to improve science editorial. Nature, 556(April 19), 273–274. DOI: 10.1038/d41586-018-04590-7
- 64 Nicolson, M., Huebner, G. M., Shipworth, D., & Elam, S. (2017). Tailored emails prompt electric vehicle owners to engage with tariff switching information. Nature Energy, 2(6), 1–6. DOI: 10.1038/nenergy.2017.73
-
65
Nosek,
B. (2020).
Changing a research culture toward openness and reproducibility . OSF. DOI: 10.17605/OSF.IO/ZVP8K - 66 Nosek, B. A., Ebersole, C. R., DeHaven, A. C., & Mellor, D. T. (2018). The preregistration revolution. Proceedings of the National Academy of Sciences, USA, 115(11), 2600–2606. DOI: 10.1073/pnas.1708274114
-
67
Ofgem. (n.d.).
Vulnerable customers & energy efficiency. Retrieved
from
https://www.ofgem.gov.uk/sites/default/files/docs/2014/01/vcee_project_direction.pdf -
68
Ofosu,
G. K., &
Posner, D.
N. (2019).
Pre-analysis plans: A stocktaking. Retrieved
from
http://danielnposner.com/wp-content/uploads/2019/12/Ofosu-Posner-191212.pdf . DOI: 10.31222/osf.io/e4pum - 69 Olken, B. A. (2015). Promises and perils of pre-analysis plans. Journal of Economic Perspectives, 29(3), 61–80. DOI: 10.1257/jep.29.3.61
- 70 Open Science Collaboration. (2015). Estimating the reproducibility of psychological science. Science, 349(6251), aac4716. DOI: 10.1126/science.aac4716
-
71
OSF. (n.d. a).
OSF|Templates of OSF Registration Forms Wiki.
Open Science Framework (OSF). Retrieved
October 1, 2020, from
https://osf.io/zab38/wiki/home/ -
72
OSF. (n.d. b).
OSF Preprints|Search. Open Science
Framework (OSF). Retrieved October 1, 2020, from
https://osf.io/preprints/discover - 73 Park, C. L. (2004). What is the value of replicating other studies? Research Evaluation, 13(3), 189–195. DOI: 10.3152/147154404781776400
- 74 Pätzold, H. (2005). Secondary analysis of audio data. Technical procedures for virtual anonymization and pseudonymization. Forum Qualitative Sozialforschung, 6(1). DOI: 10.17169/fqs-6.1.512
- 75 Pfenninger, S., DeCarolis, J., Hirth, L., Quoilin, S., & Staffell, I. (2017). The importance of open data and software: Is energy research lagging behind? Energy Policy, 101, 211–215. DOI: 10.1016/j.enpol.2016.11.046
- 76 Pfenninger, S., Hirth, L., Schlecht, I., Schmid, E., Wiese, F., Brown, T., … Wingenbach, C. (2018). Opening the black box of energy modelling: Strategies and lessons learned. Energy Strategy Reviews, 19, 63–71. DOI: 10.1016/j.esr.2017.12.002
-
77
Phelps,
R. P. (2018).
To save the research literature, get rid of the literature
review. Impact of Social Sciences [LSE
Blog]. Retrieved November 16, 2020, from
https://blogs.lse.ac.uk/impactofsocialsciences/2018/06/12/to-save-the-research-literature-get-rid-of-the-literature-review/ -
78
Pienta,
A.,
Alter,
G., &
Lyle,
J. (2010).
The enduring value of social science research: The use and
reuse of primary research data. Journal of the
Bertrand Russell Archives, 71(20),
7763–7772.
http://141.213.232.243/handle/2027.42/78307 - 79 Piwowar, H., Priem, J., Larivière, V., Alperin, J. P., Matthias, L., Norlander, B., … Haustein, S. (2018). The state of OA: A large-scale analysis of the prevalence and impact of Open Access articles. PeerJ, 2018(2). DOI: 10.7717/peerj.4375
-
80
Piwowar,
H. A., &
Vision, T.
J. (2013). Data
reuse and the open data citation advantage.
PeerJ, 2013(1),
e175 . DOI: 10.7717/peerj.175 - 81 Prinz, F., Schlange, T., & Asadullah, K. (2011). Believe it or not: How much can we rely on published data on potential drug targets? Nature Reviews Drug Discovery, 10, 712–713. DOI: 10.1038/nrd3439-c1
- 82 Rosenthal, R. (1979). The file drawer problem and tolerance for null results. Psychological Bulletin, 86(3), 638–641. DOI: 10.1037/0033-2909.86.3.638
- 83 Saha, B., & Srivastava, D. (2014). Data quality: The other face of big data. Proceedings of the International Conference on Data Engineering, 1294–1297. DOI: 10.1109/ICDE.2014.6816764
- 84 Schloss, P. D. (2018). Identifying and overcoming threats to reproducibility, replicability, robustness, and generalizability in microbiome research. MBio, 9(3). DOI: 10.1128/mBio.00525-18
- 85 Schulz, K. F., Altman, D. G., & Moher, D. (2010). CONSORT 2010 Statement: Updated guidelines for reporting parallel group randomised trials. BMJ (Online), 340(7748), 698–702. DOI: 10.1136/bmj.c332
- 86 Sheldon, T. (2018). Preprints could promote confusion and distortion. Nature, 559, 445. DOI: 10.1038/d41586-018-05789-4
- 87 Simera, I., Moher, D., Hirst, A., Hoey, J., Schulz, K. F., & Altman, D. G. (2010). Transparent and accurate reporting increases reliability, utility, and impact of your research: Reporting guidelines and the EQUATOR Network. BMC Medicine, 8, 24. DOI: 10.1186/1741-7015-8-24
- 88 Simmons, J. P., Nelson, L. D., & Simonsohn, U. (2011). False-positive psychology: Undisclosed flexibility in data collection and analysis allows presenting anything as significant. Psychological Science, 22(11), 1359–1366. DOI: 10.1177/0956797611417632
- 89 Smith, R. (2006). Peer review: A flawed process at the heart of science and journals. Journal of the Royal Society of Medicine, 99, 178–182. DOI: 10.1258/jrsm.99.4.178
- 90 Sovacool, B. K. (2014). What are we doing here? Analyzing fifteen years of energy scholarship and proposing a social science research agenda. Energy Research and Social Science, 1, 1–29. DOI: 10.1016/j.erss.2014.02.003
- 91 Sovacool, B. K., Axsen, J., & Sorrell, S. (2018). Promoting novelty, rigor, and style in energy social science: Towards codes of practice for appropriate methods and research design. Energy Research and Social Science, 45, 12–42. DOI: 10.1016/j.erss.2018.07.007
- 92 Stroebe, W., Postmes, T., & Spears, R. (2012). Scientific misconduct and the myth of self-correction in science. Perspectives on Psychological Science: Journal of the Association for Psychological Science, 7(6), 670–688. DOI: 10.1177/1745691612460687
-
93
Suber,
P. (2013).
Open Access. MIT Press.
Retrieved from
https://mitpress.mit.edu/books/open-access . DOI: 10.7551/mitpress/9286.001.0001 - 94 Tennant, J. P., Waldner, F., Jacques, D. C., Masuzzo, P., Collister, L. B., & Hartgerink, C. H. J. (2016). The academic, economic and societal impacts of Open Access: An evidence-based review. F1000Research, 5, 632. DOI: 10.12688/f1000research.8460.3
- 95 Tong, A., Sainsbury, P., & Craig, J. (2007). Consolidated criteria for reporting qualitative research (COREQ): A 32-item checklist for interviews and focus groups. International Journal for Quality in Health Care, 19(6), 349–357. DOI: 10.1093/intqhc/mzm042
-
96
UK Data Service. (n.d.).
Anonymisation. Retrieved June 6, 2020, from
https://www.ukdataservice.ac.uk/manage-data/legal-ethical/anonymisation.aspx - 97 UKCCIS. (2015). What is good quality research? UKCCIS Evidence Group, 151(July), 10–17. DOI: 10.1145/3132847.3132886
-
98
UKRI. (n.d.).
Making research data open. UK Research and
Innovation (UKRI). Retrieved November 5, 2020, from
https://www.ukri.org/apply-for-funding/before-you-apply/your-responsibilities-if-you-get-funding/making-research-data-open/ -
99
University of Cambridge.
(n.d.). Good research practice|Research integrity.
Retrieved October 1, 2020, from
https://www.research-integrity.admin.cam.ac.uk/research-integrity/good-research-practice -
100
Vaganay,
A. (2018).
To save the research literature, let’s make literature reviews
reproducible|Impact of Social Sciences. Retrieved November 5,
2020, from
https://blogs.lse.ac.uk/impactofsocialsciences/2018/06/19/to-save-the-research-literature-lets-make-literature-reviews-reproducible/ - 101 van ’t Veer, A. E., & Giner-Sorolla, R. (2016). Pre-registration in social psychology—A discussion and suggested template. Journal of Experimental Social Psychology, 67, 2–12. DOI: 10.1016/j.jesp.2016.03.004
-
102
Van den
Eynden, V.,
Corti,
L.,
Woollard,
M.,
Bishop,
L., &
Horton,
L. (2009).
Managing and sharing data best practice for researchers.
Retrieved from
https://ukdataservice.ac.uk/media/622417/managingsharing.pdf - 103 Vandewalle, P. (2012). Code sharing is associated with research impact in image processing. Computing in Science and Engineering, 14, 42–47. DOI: 10.1109/MCSE.2012.63
- 104 Wagenmakers, E.-J., & Dutilh, G. (2016). Seven selfish reasons for preregistration. APS Observer, 29(9), 13–14.
- 105 Warren, M. (2018). First analysis of ‘pre-registered’ studies shows sharp rise in null findings. Nature. DOI: 10.1038/d41586-018-07118-1
-
106
Wells,
J. A., &
Titus,
S. (2006). The
Gallup Organization for final report: Observing and reporting suspected
misconduct in biomedical research. Retrieved from
https://ori.hhs.gov/sites/default/files/gallup_finalreport.pdf - 107 Wilkinson, M. D., Dumontier, M., Aalbersberg, Ij. J., Appleton, G., Axton, M., Baak, A., … Mons, B. (2016). Comment: The FAIR Guiding Principles for scientific data management and stewardship. Scientific Data, 3. DOI: 10.1038/sdata.2016.18