Dr. Todd Vision - Bringing Data into the Fold of Scholarly Communication

Bringing data into the fold of scholarly communication
Todd Vision, University of North Carolina at Chapel Hill http://orcid.org/0000-‐0002-‐6133-‐2581, @tjvision 17-‐Jul-‐2014 You may reuse any of the original content in these slides as you wish, provided you attribute the source Science Bootcamp 1 CC-‐BY-‐NC-‐SA nic221 http://www.ﬂickr.com/ photos/ nic221/391536867/

Traditional roles of a journal o Registration o Certiﬁcation
o Dissemination o Archiving 17-‐Jul-‐2014 Science Bootcamp 2

New York Public Library, CC-‐BY-‐NC-‐SA 2006 Elena Romera http://www.ﬂickr.com/photos/elenaromera/353826561/
Some aspects of scholarly communication have adapted more quickly than others to the internet 17-‐Jul-‐2014 Science Bootcamp 3

Outline o  Challenges of availability for diﬀerent kinds of
research data o  How to achieve archiving of long-‐tail data associated with the scientiﬁc literature o  How to make data archives interoperate with the rest of the scholarly communications infrastructure o  How to educate yourself and others about the data landscape o  I will use Dryad (and DataONE) as models 17-‐Jul-‐2014 Science Bootcamp 4

What are research outputs? o  Traditional publications (articles, monographs)
and their supplements o  Datasets o  Software (including scripts, models, workﬂows) o  Presentations (slides, video) o  Grant proposals o  Reviews o  Other digital content (e.g. wikis, blogs, ontologies) o  Materials, reagants, equipment o  Lab notebooks o  etc… 17-‐Jul-‐2014 Science Bootcamp 5

4-‐June-‐2014 British Library 6 http://amandamlawrence.wordpress.com/

Public Participation in Scientiﬁc Research Conference: 4-‐5 August 2012 in
Portland, Oregon USA prior to Ecological Society of America meeting (6-‐10 Aug.): http://www.birds.cornell.edu/citscitoolkit/conference/2012 8

Data papers and data journals 17-‐Jul-‐2014 Science Bootcamp
9

Source: Publishing Research Consortium, http://publishingresearch.net n=3824 10
Ease of access vs. importance 17-‐Jul-‐2014 Science Bootcamp

Protein Data Bank 28-‐May-‐2014 Dryad-‐Dataverse Community Meeting –
Cambridge, MA 11

Natl. Snow and Ice Data Center 28-‐May-‐2014 Dryad-‐Dataverse
Community Meeting – Cambridge, MA 12

The long tail of orphan data in “small science”
Bumpus HC (1898) The Elimination of the Unﬁt as Illustrated by the Introduced Sparrow, Passer domesticus. Biological Lectures from the Marine Biological Laboratory: 209-226.

Over 1M research articles published annually 14 Nature
480, 426–429 (2011) http://doi.org/10.1038/480426a

15 What happens to all the data underlying
the millions of articles published every year?

Science Bootcamp Data Volume Intellectual complexity Genbank,
PDB, ClinVar, etc. Long tail data (e.g. much statistical data) Graphic from B. Heidorn 17-‐Jul-‐2014 16

Science Bootcamp Data Volume Intellectual complexity Genbank,
PDB, ClinVar, etc. Long tail data (e.g. much statistical data) Graphic from B. Heidorn 17-‐Jul-‐2014 17 “Most of the bytes are at the high end, but most of the datasets are at the low end” – Jim Gray

18 http://www.stm-‐assoc.org/2011_12_5_ODE_Report_On_Integration_of_Data_and_Publications.pdf

As needed data sharing policies Wicherts and colleagues requested
data from from 141 articles in American Psychological Association journals. “6 months later, after … 400 emails, [sending] detailed descriptions of our study aims, approvals of our ethical committee, signed assurances not to share data with others, and even our full resumes…” only 27% of authors complied •  Wicherts, J.M., Borsboom, D., Kats, J., & Molenaar, D. (2006). The poor availability of psychological research data for reanalysis. American Psychologist, 61, 726-728. •  Wicherts JM, Bakker M, Molenaar D (2011) Willingness to Share Research Data Is Related to the Strength of the Evidence and the Quality of Reporting of Statistical Results. PLoS ONE 6(11):e26828 17-‐Jul-‐2014 Science Bootcamp 19

4-‐June-‐2014 British Library 20 theconversation.com

Quantifying data loss 17-‐Jul-‐2014 Science Bootcamp 21
Vines TH et al. (2013) Current Biology DOI:10.1016/j.cub.2013.11.014

Outline o Challenges of availability for diﬀerent kinds of
research data o How to achieve archiving of long-‐tail data associated with the scientiﬁc literature o How to make data archives interoperate with the rest of the scholarly communications infrastructure o How to educate yourself and others about the data landscape 17-‐Jul-‐2014 Science Bootcamp 22

Data Management Planning

Why encourage data archiving at the time of publication
24 Plan Collect Assure Describe Preserve Discover Integrate Analyze Proposal wri9ng Research Publica9on Ideas ? ?

Benefits of archiving data Modified from Beagrie et al.
(2009) Keeping Research Data Safe 2 Direct Verification of published research Preserving accessibility to data Allowing reuse and repurposing of data Discoverability of data Indirect (costs avoided) Redundant data collection Inefficient legacy data curation Burden of sharing-upon-request Opportunity cost of science not done Near term Protection against personnel turnover Availability for review and validation Long term Secure long-term stewardship Increased impact per publication Private Increased citations New collaborations New research opportunities Fulfilling funding mandates Public More efficient use of research dollars Public trust in science Educational opportunities Improved methodologies More informed policy

Open data citation advantage 17-‐Jul-‐2014 Science Bootcamp
26 Piwowar and Vision (2013) doi:10.7717/peerj.175

Piwowar HA, Chapman WW (2008) A review of journal policies
for sharing research data. Presented at ELPUB2008, Nature Precedings hdl:10101/npre.2008.1700.1 Data policies among bioscience journals n=70 IF=3.6 IF=4.5 IF=6.0

Joint Data Archiving Policy for journals Data are important
products of the scientiﬁc enterprise, and they should be preserved and usable for decades in the future. As a condition for publication, data supporting the results in the article should be deposited in an appropriate public archive. Authors may elect to embargo access to the data for a period up to a year after publication. Exceptions may be granted at the discretion of the editor, especially for sensitive information. http://datadryad.org/pages/jdap 17-‐Jul-‐2014 Science Bootcamp 28

17-‐Jul-‐2014 Science Bootcamp 29

Submission integration of publications & data 17-‐Jul-‐2014
Science Bootcamp 30

4-‐June-‐2014 British Library 32

Content and usage in Dryad As of mid-‐May
o Data packages 5,469 o Data ﬁles 16,436 o Journals 329 o Authors 19,857 o Downloads 490,448 28-‐May-‐2014 Dryad-‐Dataverse Community Meeting – Cambridge, MA 33

Eﬀects of JDAP since 2011 17-‐Jul-‐2014 Science Bootcamp
34 Magee et al. (2014) Dawn of open access to phylogenetic data. arXiv:14.1405.6623.v1

Embargoes are the exception, not the rule 28-‐May-‐2014
Dryad-‐Dataverse Community Meeting – Cambridge, MA 35 A. Embargo selections of Dryad data authors for the 10,108 files in Dryad deposited from inception to September 20, 2013. Data include only datasets related to articles published in journals for which the authors had the option of selecting an embargo. B. Long-‐term embargoes (>1 year) by journal that granted them. Data: Vision TJ , Scherle R, Mannheimer S (2013) Embargo selections of Dryad data authors. FigShare. http://doi.org/10.6084/ m9.figshare.805946. Article: Roche DG, Lanfear R, Binning SA, Haff TM, et al. (2014) Troubleshooting Public Data Archiving: Suggestions to Increase Participation. PLoS Biol 12(1): e1001779

Piwowar and Vision, unpublished

Data from books 28-‐May-‐2014 Dryad-‐Dataverse Community Meeting –
Cambridge, MA 37

It is not all tabular data I 28-‐May-‐2014
Dryad-‐Dataverse Community Meeting – Cambridge, MA 38

It is not all tabular data II 17-‐Jul-‐2014
Science Bootcamp 39

Even data on monsters Levy J, Foulsham T, Kingstone
A (2012) Data from: Monsters are people too. Dryad Digital Repository. doi:10.5061/dryad.4rk06 Levy J, Foulsham T, Kingstone A (2012) Monsters are people too. Biology Letters 9(1): 20120850. doi:10.1098/rsbl.2012.0850 Beholder image from Dungeons & Dragons Monster Manual via Discover Magazine blog

Reusability requires timely documentation 41 Information Content
Time Time of publication Speciﬁc details General details Accident Retirement or career change Death (Michener et al. 1997)

Documentation: ReadMe ﬁles

Science Bootcamp 45 17-‐Jul-‐2014

28-‐May-‐2014 Dryad-‐Dataverse Community Meeting – Cambridge, MA
52 Self-‐advertising

IDs linking researchers and data in the wild 4-‐June-‐2014
British Library 54

To learn more o http://datadryad.org o http://blog.datadryad.org o http://datadryad.org/wiki o http://code.google.com/p/dryad o [email protected] o 
@datadryad o  Dryad 4-‐June-‐2014 British Library 58

Data archiving landscape There are so many data repositories
that we need directories of them: o  http://re3data.org o  http://DataBib.org These repositories vary along many dimensions: o  Datatype focus o  Community focus o  Allowed ﬁle sizes o  Curation policies o  Data access policies o  Funding model 17-‐Jul-‐2014 Science Bootcamp 60

62 Training resources www.dataone.org/dataonepedia

How to enable the diﬀerent stakeholders to bring data
into the fold of scholarly communication? 17-‐Jul-‐2014 Science Bootcamp 63 CC-‐BY-‐SA Hyougushi, ﬂickr

publishers educators &students researchers funders
research networks universities & libraries societies Journals How to enable the diﬀerent stakeholders to bring data into the fold of scholarly communication? 17-‐Jul-‐2014 Science Bootcamp 64

Dr. Todd Vision - Bringing Data into the Fold of Scholarly Communication

Dr. Todd Vision - Bringing Data into the Fold of Scholarly Communication

More Decks by Science Boot Camp for Librarians Southeast 2014

Other Decks in Science

Featured

Transcript