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Improving the scientific record: data
    citation and publication by NERC’s
        environmental data centres

Sarah Callaghan and the NERC Data Citation and Publication Project
                              Team
                  [sarah.callaghan@stfc.ac.uk]
                          @sorcha.ni

                   EASE, Tallinn, 9th June 2012




                        VO Sandpit, November 2009
Who are we and why do we
                                    care about data?
The UK’s Natural Environment Research Council
(NERC) funds six data centres which between them
have responsibility for the long-term management of
NERC's environmental data holdings.

We deal with a variety of environmental measurements,
along with the results of model simulations.

As part of the NERC Science Information Strategy (SIS)
several projects have been created to provide the
framework for NERC to work more closely and
effectively with its scientific communities in delivering
data and information management services.

One of these is the Data Citation and Publication Project


                             VO Sandpit, November 2009
The Scientific Method
                                                             A key part of the scientific method is
                                                             that it should be reproducible – other
                                                             people doing the same experiments
                                                             in the same way should get the
                                                             same results.

                                                             Unfortunately observational data is
                                                             not reproducible (unless you have a
                                                             time machine!)

                                                             The way data is organised and
                                                             archived is crucial to the
                                                             reproducibility of science and our
                                                             ability to test conclusions.

                                                             This is often the only part of the
                                                             process that anyone other than the
                                                             originating scientist sees.
http://www.mrsaverettsclassroom.com/bio
2-scientific-method.php                                      We want to change this.

                                          VO Sandpit, November 2009
Historically speaking...
... data was hard to capture, but could be
    (relatively) easily published in image or table
    format

But now...
there’s simply too much information associated
   with everything we need to know about a
   scientific event
- whether that’s an observation, simulation,
   development of a theory, or any combination
   of these.

Data always has been the foundation of
  scientific progress – without it, we can’t test
  any of our assertions, or reproduce our
  findings!                                                Suber cells and mimosa
                                                           leaves. Robert Hooke, Micrographia,
                                                           1665

                               VO Sandpit, November 2009
The Data Deluge
 “the amount of data generated worldwide...is growing by 58%
 per year; in 2010 the world generated 1250 billion gigabytes
 of data”
The Digital Universe Decade – Are You
Ready?
IDCC White Paper, May 2010


A lot of people are
creating a lot of data, and
we’re only going to get
more of it.

If this is a data deluge –
time to start building arks!


                               VO Sandpit, November 2009
Will sharing our data help?

Benefits of sharing:
• Ability to discover and reuse data which
  has already been collected
• Avoid redundant data collection
• Save time and money
• Provide opportunities for collaboration.

Research funders are keen to encourage
  data sharing.                                            Data

For the most part, scientists are happy to
   share other scientists’ data, but...




                             VO Sandpit, November 2009
Knowledge is power!

Data may mean the difference between
  getting a grant and not.

There is (currently) no universally
  accepted mechanism for data
  creators to obtain academic credit for
  their dataset creation efforts.

Creators (understandably) prefer to
  hold the data until they have
  extracted all the possible publication
  value they can.                                 Reframing “sharing” as
                                                  “publication” might
This behaviour comes at a cost for the            encourage scientists to be
   wider scientific community.                    more open with their data.

                              VO Sandpit, November 2009
Why do we want to cite and
        publish data?
• Pressure from the UK government to make all data from
publicly funded research available to the public for free.
     • Scientists still want to receive attribution and credit for
         their work
     • General public want to know what the scientists are
         doing (Climategate...)

• Research funders want reassurance that they’re getting value
for money from their funding
     • Relies on peer-review of science publications (well
       established) and data (not done yet!)

• Allows the wider research community to find and use datasets
outside their immediate domain, confident that the data is of
reasonable quality

• From a strict data-centric point of view, citation and
publication provides an extra incentive for scientists to submit
their data to us in appropriate formats and with full metadata!


   VO Sandpit, November 2009
Data Citation and Publication Project
• To implement publication and citation of datasets held Aims
within the NERC data centres.
• To increase NERC’s influence on work to provide and
cite data outputs from scientific work in similar ways to
scientific papers.
• To demonstrate to the NERC community that data
citation and publication is both personally and scientifically
advantageous.
• To form partnerships with other organisations with the
same goal of data publication to exploit common activities
and achieve a wider community buy-in. To this end,
project team members are involved with both the
SCOR/IODE/MBL WHOI Library Data Publication Working
Group, the CODATA-ICSTI Task Group on Data Citation
Standards and Practises and the DataCite Working Group
on Criteria for Datacentres.

 • Provide a reward to scientists who create data for all their efforts in
 putting their data in one of our data centres.

                                       VO Sandpit, November 2009
“Publishing” versus “publishing” and
                                           “Open” versus “Closed”
We draw a clear distinction
  between:

publishing/serving = making
   available for consumption (e.g.
   on the web), and

Publishing = publishing after some
   formal process which adds value
   for the consumer:
• e.g. PloS ONE type review, or
• EGU journal type public review,
   or
• More traditional peer review.
AND
• provides commitment to
   persistence

                                VO Sandpit, November 2009
We want to:

                      Encourage scientists to
                          move away from
                          storing their data on
                          CDs in their locked
                          filing cabinets...
                      ....or on hard disks with
                          no backups....

                      And get them to put their
                        data in a place where
                        it’ll be archived and
                        looked after for the
                        future properly.

VO Sandpit, November 2009
So why data centres? Can’t we just put
                        everything in the cloud? Or on a webpage?




                                                                 • Will you be able to find it again?
                                                                 • How do you know it hasn’t changed?
                                                                 • How can someone else trust it?
By David Fletcher
http://www.cloudtweaks.com/2011/05/the-lighter-side-of-the-
cloud-data-transfer/


                                              VO Sandpit, November 2009
Data preservation isn’t enough




                                                           Phaistos Disk, 1700BC

The writers of these documents did a brilliant job of preserving for thousands of years
the bits-and-bytes of their time!
But they’ve both been translated many times, and it’s a shame the meanings are
different.

Data Preservation is not enough, we need “Active Curation” to preserve
Information

                               VO Sandpit, November 2009
“publishing” on the web
To a scientist, there is little benefit from making
   their dataset available as a free download
   from a webpage.

Reputational risk of doing so:
• others might find errors, or
• take advantage of the dataset to earn new
   research funding

Even when sharing is mandated, there are
   simple ways of stopping people from using
   data openly posted on-line (e.g.
   incomprehensible filenames…)

There’s extra effort involved in preparing a
   dataset for use by others.

Data centres know this extra work is needed,
  and we want to make sure the dataset
  author gets credit!

                                        VO Sandpit, November 2009
How we’re going to cite
                                                       (and publish) data
We using digital object identifiers
  (DOIs) as part of our dataset
  citation because:

•   They are actionable, interoperable,
    persistent links for (digital) objects
•   Scientists are already used to citing
    papers using DOIs (and they trust
    them)
•   There are moves by academic
    journal publishers (e.g. Nature) to
    require data sets to be cited in a
    stable way, i.e. using DOIs.
•   The British Library and DataCite
    gave us an allocation of 500 DOIs
    to assign to datasets (we got to
    define what a dataset is).

                                      VO Sandpit, November 2009
What sort of data can we/will we cite?
Dataset has to be:
• Stable (i.e. not going to be modified)
• Complete (i.e. not going to be updated)
• Permanent – by assigning a DOI we’re committing to make the dataset available
   for posterity
• Good quality – by assigning a DOI we’re giving it our data centre stamp of
   approval, saying that it’s complete and all the metadata is available
When a dataset is cited that means:
   • There will be bitwise fixity
   • With no additions or deletions of files
   • No changes to the directory structure in the dataset
      “bundle”

A DOI should point to a html representation of some
   record which describes a data object – i.e. a landing
   page.

Upgrades to versions of data formats will result in new editions
   of datasets.

                                   VO Sandpit, November 2009
What data centres can do and what
                                                      we can’t
Doi:10232/123ro
                                      The scientific quality of a dataset has to be
              2.                      evaluated by peer-review by scientists with domain
     Publication of data              knowledge. This peer-review process has already
            sets                      been set up by academic publishers, so it makes
     (scientific quality)             sense to collaborate with them for peer-review
                                      publishing of data.
Doi:10232/123
              1.                      When we cite (i.e. assign a DOI to) a dataset, we’re
       Data set Citation              confirming that, in our opinion, the dataset meets a
      (technical quality)             level of technical quality (metadata and format)
                                      and that we will make it available and keep it frozen
                                      for the forseeable future.

             0.
                                      The day job – take in data and metadata supplied
    Serving of data sets              by scientists (often on a on-going basis). Make sure
                                      that there is adequate metadata and that the data
                                      files are appropriate format. Make it available to
                                      other interested parties.




                             VO Sandpit, November 2009
Publishing data for the scholarly
• Scientific journal publication mainly
                                           record
focuses on the analysis, interpretation and
conclusions drawn from a given dataset.

• Examining the raw data that forms the
dataset is more difficult, as datasets are
usually stored in digital media, in a variety of
(proprietary or non-standard) formats.

• Peer-review is generally only applied to
the methodology and final conclusions of a
piece of work, and not the underlying data
itself. But if the conclusions are to stand, the
data must be of good quality.

• A process of data publication, involving
peer-review of datasets would be of benefit
to many sectors of the academic                         http://libguides.luc.edu/content.php?pid=5464&sid=164619
community.


                                       VO Sandpit, November 2009
(Scientific) Communication
                                                        through the ages
Journals have been the traditional route
   for disseminating scientific
   knowledge. Papers work but...

...it’s now becoming more important to
     ensure that the data that underpin a
     specific scientific result are available
     and that the conclusions arising from
     it can be tested.

If the data’s lost/locked away/stored on                    http://www.intoon.com/#68559
    obsolete media/in arcane
    formats/without documentation, how               “On-line journals are essentially
    can we do that?                                  paper journals, delivered by faster
                                                     horses”, Jason Priem, DataCite
Technology has given us new tools, but               Summer meeting 2011
  it’s also provided new challenges
                                VO Sandpit, November 2009
Data journals and scientific publication
                                                             of data
•   Now we can cite our datasets using DOIs, we can give academic credit to those scientists
    who get cited – making them more likely to give us good quality data to archive.

•   Publication – and scientific peer-review – is the next step
•   We are working with the Royal Meteorological Society and Wiley-Blackwell to operate a
    new data journal.




•   Data journals already exist:
•   Earth System Science Data
    (http://earth-system-science-
    data.net/)
•   Geochemistry, Geophysics,
    Geosystems (G3
    http://www.agu.org/journals/
    gc/ )


                                    VO Sandpit, November 2009
Geoscience Data Journal
                                  Wiley-Blackwell and the Royal Meteorological
                                                    Society

•   Partnership formed between Royal
    Meteorological Society & academic
    publishers Wiley-Blackwell
      • develop a mechanism for the formal
         publication of data in the Open Access
         Geoscience Data Journal (GDJ)

•    GDJ is an online-only, Open Access journal,
    publishing short data papers cross-linked to –
    and citing – datasets that have been deposited
    in approved data centres and awarded DOIs.




                                   VO Sandpit, November 2009
Operating a data journal will be more
complicated than a traditional
journal, and will require close linking
with partnering data repositories.

Figure shows the (potential)
steps/workflow required for a
researcher to publish a data paper

•Items in orange refer to areas where
further work is required and
technologies developed.

•Division of area of responsibilities
between
     • repository controlled
         processes
     • journal controlled processes




                                     VO Sandpit, November 2009
PREPARDE: Peer REview for Publication &
                               Accreditation of Research Data in the Earth
                                                sciences
Funded by JISC

Lead Institution: University of Leicester
Partners
     British Atmospheric Data Centre (BADC)
     US National Centre for Atmospheric Research (NCAR)
     California Digital Library (CDL)
     Digital Curation Centre (DCC)
     University of Reading
     Wiley-Blackwell
     Faculty of 1000 Ltd
Project Lead:         Dr Jonathan Tedds (University of
    Leicester, jat26@le.ac.uk)
Project Manager: Dr Sarah Callaghan (BADC,
    sarah.callaghan@stfc.ac.uk )
Length of Project: 12 months
Project Start Date: 1st July 2012
Project End Date: 31st June 2013



                                    VO Sandpit, November 2009
PREPARDE objectives
•   capture and manage workflows required to operate the
    Geoscience Data Journal
      • from submission of a new data paper and dataset,
          through review and to publication
•   develop procedures and policies for authors, reviewers
    and editors
      • allow the Geoscience Data Journal to accept data
          papers as submissions for publication
      • focus on guidelines for scientific reviewers who will
          review the datasets
•   incorporate some technical developments at the point of
    submission
      • data visualisation checks
      • interface improvements
      • enhance the resulting data publications
•   put in place procedures needed for data publication in
    the California Digital Library
•   interact with the wider scientific and data community
      • provide recommendations on accreditation
          requirements for data repositories
•   engage the user and stakeholder community                       Engraving of printer using the early Gutenberg
                                                                    letter press during the 15th century.
      • promote long-term sustainability and governance of          Date unknown - estimate 16th - 19th century
          data journals                                             http://commons.wikimedia.org/wiki/File:Gutenberg_pres



                                        VO Sandpit, November 2009
Conclusions
•   The NERC data centres now have the ability to mint
    DOIs and assign them to datasets in their archives.
    We have also produced:
        • guidelines for the data centre on what is an
           appropriate dataset to cite
        • guidelines for data providers about data
           citation and the sort of datasets we will cite
        • text that will go into the NERC grants
           handbook telling grant applicants about
           data citation

•   We’ve already had users coming to us requesting
    DOIs for their datasets.
•   We’re progressing well with data publication through
    our partnership with Wiley-Blackwell, and
    discussions with Elsevier and Thompson-Reuters.
•   The next big step is tackling the thorny issue of
    peer-review of data – PREPARDE.

“We share because we do science, not alchemy.”                    http://www.keepcalm-o-matic.co.uk/default.aspx#c
Jason Priem (Datacite Summer meeting, August 2011)


                                      VO Sandpit, November 2009
Thanks!

Any questions?

                             Image credit: Borepatch http://borepatch.blogspot.com/2010/06/its-
                             not-what-you-dont-know-that-hurts.html




             VO Sandpit, November 2009
A short digression: Citation vs.
                                                               referencing
•   Citation – data centre commitment regarding fixity, stability, permanence etc. of a
    dataset. Demonstrated by assignment of DOI
     • e.g. Darwin, Charles Robert. The Origin of Species. Vol. XI. The Harvard
        Classics. New York: P.F. Collier & Son, 1909–14;

•   Referencing – no data centre commitment regarding fixity, stability, permanence etc.
    of a dataset. Dataset can still be referenced by URL – but link might be broken
     • e.g. Paragraph 3, page 42, Darwin, Charles Robert. The Origin of Species, 1859

•   We want to be able to reference the individual part of the dataset
    (word/line/paragraph) without having to commit to assigning a DOI to everything but
    the dataset (book)

•   If the dataset is properly frozen, then the reference to a part of it should work fine.

•   People citing the dataset might want to reference a part of it, and we should make this
    possible. But we don’t want to commit to DOI-ing every single bit of a dataset!

•   And just because someone can (and will) reference something in a dataset that’s not
    DOI-ready – this act should not trigger a DOI-citation


                                    VO Sandpit, November 2009
Journals – a 17th century technology

The first scientific journal, Journal des
    sçavans (later renamed Journal des
    savants), was first published on Monday, 5
    January 1665.
It also carried a proportion of material that
    would not now be considered scientific,
    such as obituaries of famous men, church
    history, and legal reports.
It still exists, but is more of a literary journal

The first edition of the Philosophical
  Transactions of the Royal Society of
  London was on 6 March 1665. That still
  exists, and continues to publish scientific
  information to this day.


                               VO Sandpit, November 2009
Step XX: Get occasionally side-tracked
searching for data specific comics on the
                                 internet




VO Sandpit, November 2009
Censormatic picture from:
                            http://scienceblogs.com/clock/2007/04/framing_politics_bas




VO Sandpit, November 2009

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Presentation to EASE, Tallinn, June 2012

  • 1. Improving the scientific record: data citation and publication by NERC’s environmental data centres Sarah Callaghan and the NERC Data Citation and Publication Project Team [sarah.callaghan@stfc.ac.uk] @sorcha.ni EASE, Tallinn, 9th June 2012 VO Sandpit, November 2009
  • 2. Who are we and why do we care about data? The UK’s Natural Environment Research Council (NERC) funds six data centres which between them have responsibility for the long-term management of NERC's environmental data holdings. We deal with a variety of environmental measurements, along with the results of model simulations. As part of the NERC Science Information Strategy (SIS) several projects have been created to provide the framework for NERC to work more closely and effectively with its scientific communities in delivering data and information management services. One of these is the Data Citation and Publication Project VO Sandpit, November 2009
  • 3. The Scientific Method A key part of the scientific method is that it should be reproducible – other people doing the same experiments in the same way should get the same results. Unfortunately observational data is not reproducible (unless you have a time machine!) The way data is organised and archived is crucial to the reproducibility of science and our ability to test conclusions. This is often the only part of the process that anyone other than the originating scientist sees. http://www.mrsaverettsclassroom.com/bio 2-scientific-method.php We want to change this. VO Sandpit, November 2009
  • 4. Historically speaking... ... data was hard to capture, but could be (relatively) easily published in image or table format But now... there’s simply too much information associated with everything we need to know about a scientific event - whether that’s an observation, simulation, development of a theory, or any combination of these. Data always has been the foundation of scientific progress – without it, we can’t test any of our assertions, or reproduce our findings! Suber cells and mimosa leaves. Robert Hooke, Micrographia, 1665 VO Sandpit, November 2009
  • 5. The Data Deluge “the amount of data generated worldwide...is growing by 58% per year; in 2010 the world generated 1250 billion gigabytes of data” The Digital Universe Decade – Are You Ready? IDCC White Paper, May 2010 A lot of people are creating a lot of data, and we’re only going to get more of it. If this is a data deluge – time to start building arks! VO Sandpit, November 2009
  • 6. Will sharing our data help? Benefits of sharing: • Ability to discover and reuse data which has already been collected • Avoid redundant data collection • Save time and money • Provide opportunities for collaboration. Research funders are keen to encourage data sharing. Data For the most part, scientists are happy to share other scientists’ data, but... VO Sandpit, November 2009
  • 7. Knowledge is power! Data may mean the difference between getting a grant and not. There is (currently) no universally accepted mechanism for data creators to obtain academic credit for their dataset creation efforts. Creators (understandably) prefer to hold the data until they have extracted all the possible publication value they can. Reframing “sharing” as “publication” might This behaviour comes at a cost for the encourage scientists to be wider scientific community. more open with their data. VO Sandpit, November 2009
  • 8. Why do we want to cite and publish data? • Pressure from the UK government to make all data from publicly funded research available to the public for free. • Scientists still want to receive attribution and credit for their work • General public want to know what the scientists are doing (Climategate...) • Research funders want reassurance that they’re getting value for money from their funding • Relies on peer-review of science publications (well established) and data (not done yet!) • Allows the wider research community to find and use datasets outside their immediate domain, confident that the data is of reasonable quality • From a strict data-centric point of view, citation and publication provides an extra incentive for scientists to submit their data to us in appropriate formats and with full metadata! VO Sandpit, November 2009
  • 9. Data Citation and Publication Project • To implement publication and citation of datasets held Aims within the NERC data centres. • To increase NERC’s influence on work to provide and cite data outputs from scientific work in similar ways to scientific papers. • To demonstrate to the NERC community that data citation and publication is both personally and scientifically advantageous. • To form partnerships with other organisations with the same goal of data publication to exploit common activities and achieve a wider community buy-in. To this end, project team members are involved with both the SCOR/IODE/MBL WHOI Library Data Publication Working Group, the CODATA-ICSTI Task Group on Data Citation Standards and Practises and the DataCite Working Group on Criteria for Datacentres. • Provide a reward to scientists who create data for all their efforts in putting their data in one of our data centres. VO Sandpit, November 2009
  • 10. “Publishing” versus “publishing” and “Open” versus “Closed” We draw a clear distinction between: publishing/serving = making available for consumption (e.g. on the web), and Publishing = publishing after some formal process which adds value for the consumer: • e.g. PloS ONE type review, or • EGU journal type public review, or • More traditional peer review. AND • provides commitment to persistence VO Sandpit, November 2009
  • 11. We want to: Encourage scientists to move away from storing their data on CDs in their locked filing cabinets... ....or on hard disks with no backups.... And get them to put their data in a place where it’ll be archived and looked after for the future properly. VO Sandpit, November 2009
  • 12. So why data centres? Can’t we just put everything in the cloud? Or on a webpage? • Will you be able to find it again? • How do you know it hasn’t changed? • How can someone else trust it? By David Fletcher http://www.cloudtweaks.com/2011/05/the-lighter-side-of-the- cloud-data-transfer/ VO Sandpit, November 2009
  • 13. Data preservation isn’t enough Phaistos Disk, 1700BC The writers of these documents did a brilliant job of preserving for thousands of years the bits-and-bytes of their time! But they’ve both been translated many times, and it’s a shame the meanings are different. Data Preservation is not enough, we need “Active Curation” to preserve Information VO Sandpit, November 2009
  • 14. “publishing” on the web To a scientist, there is little benefit from making their dataset available as a free download from a webpage. Reputational risk of doing so: • others might find errors, or • take advantage of the dataset to earn new research funding Even when sharing is mandated, there are simple ways of stopping people from using data openly posted on-line (e.g. incomprehensible filenames…) There’s extra effort involved in preparing a dataset for use by others. Data centres know this extra work is needed, and we want to make sure the dataset author gets credit! VO Sandpit, November 2009
  • 15. How we’re going to cite (and publish) data We using digital object identifiers (DOIs) as part of our dataset citation because: • They are actionable, interoperable, persistent links for (digital) objects • Scientists are already used to citing papers using DOIs (and they trust them) • There are moves by academic journal publishers (e.g. Nature) to require data sets to be cited in a stable way, i.e. using DOIs. • The British Library and DataCite gave us an allocation of 500 DOIs to assign to datasets (we got to define what a dataset is). VO Sandpit, November 2009
  • 16. What sort of data can we/will we cite? Dataset has to be: • Stable (i.e. not going to be modified) • Complete (i.e. not going to be updated) • Permanent – by assigning a DOI we’re committing to make the dataset available for posterity • Good quality – by assigning a DOI we’re giving it our data centre stamp of approval, saying that it’s complete and all the metadata is available When a dataset is cited that means: • There will be bitwise fixity • With no additions or deletions of files • No changes to the directory structure in the dataset “bundle” A DOI should point to a html representation of some record which describes a data object – i.e. a landing page. Upgrades to versions of data formats will result in new editions of datasets. VO Sandpit, November 2009
  • 17. What data centres can do and what we can’t Doi:10232/123ro The scientific quality of a dataset has to be 2. evaluated by peer-review by scientists with domain Publication of data knowledge. This peer-review process has already sets been set up by academic publishers, so it makes (scientific quality) sense to collaborate with them for peer-review publishing of data. Doi:10232/123 1. When we cite (i.e. assign a DOI to) a dataset, we’re Data set Citation confirming that, in our opinion, the dataset meets a (technical quality) level of technical quality (metadata and format) and that we will make it available and keep it frozen for the forseeable future. 0. The day job – take in data and metadata supplied Serving of data sets by scientists (often on a on-going basis). Make sure that there is adequate metadata and that the data files are appropriate format. Make it available to other interested parties. VO Sandpit, November 2009
  • 18. Publishing data for the scholarly • Scientific journal publication mainly record focuses on the analysis, interpretation and conclusions drawn from a given dataset. • Examining the raw data that forms the dataset is more difficult, as datasets are usually stored in digital media, in a variety of (proprietary or non-standard) formats. • Peer-review is generally only applied to the methodology and final conclusions of a piece of work, and not the underlying data itself. But if the conclusions are to stand, the data must be of good quality. • A process of data publication, involving peer-review of datasets would be of benefit to many sectors of the academic http://libguides.luc.edu/content.php?pid=5464&sid=164619 community. VO Sandpit, November 2009
  • 19. (Scientific) Communication through the ages Journals have been the traditional route for disseminating scientific knowledge. Papers work but... ...it’s now becoming more important to ensure that the data that underpin a specific scientific result are available and that the conclusions arising from it can be tested. If the data’s lost/locked away/stored on http://www.intoon.com/#68559 obsolete media/in arcane formats/without documentation, how “On-line journals are essentially can we do that? paper journals, delivered by faster horses”, Jason Priem, DataCite Technology has given us new tools, but Summer meeting 2011 it’s also provided new challenges VO Sandpit, November 2009
  • 20. Data journals and scientific publication of data • Now we can cite our datasets using DOIs, we can give academic credit to those scientists who get cited – making them more likely to give us good quality data to archive. • Publication – and scientific peer-review – is the next step • We are working with the Royal Meteorological Society and Wiley-Blackwell to operate a new data journal. • Data journals already exist: • Earth System Science Data (http://earth-system-science- data.net/) • Geochemistry, Geophysics, Geosystems (G3 http://www.agu.org/journals/ gc/ ) VO Sandpit, November 2009
  • 21. Geoscience Data Journal Wiley-Blackwell and the Royal Meteorological Society • Partnership formed between Royal Meteorological Society & academic publishers Wiley-Blackwell • develop a mechanism for the formal publication of data in the Open Access Geoscience Data Journal (GDJ) • GDJ is an online-only, Open Access journal, publishing short data papers cross-linked to – and citing – datasets that have been deposited in approved data centres and awarded DOIs. VO Sandpit, November 2009
  • 22. Operating a data journal will be more complicated than a traditional journal, and will require close linking with partnering data repositories. Figure shows the (potential) steps/workflow required for a researcher to publish a data paper •Items in orange refer to areas where further work is required and technologies developed. •Division of area of responsibilities between • repository controlled processes • journal controlled processes VO Sandpit, November 2009
  • 23. PREPARDE: Peer REview for Publication & Accreditation of Research Data in the Earth sciences Funded by JISC Lead Institution: University of Leicester Partners British Atmospheric Data Centre (BADC) US National Centre for Atmospheric Research (NCAR) California Digital Library (CDL) Digital Curation Centre (DCC) University of Reading Wiley-Blackwell Faculty of 1000 Ltd Project Lead: Dr Jonathan Tedds (University of Leicester, jat26@le.ac.uk) Project Manager: Dr Sarah Callaghan (BADC, sarah.callaghan@stfc.ac.uk ) Length of Project: 12 months Project Start Date: 1st July 2012 Project End Date: 31st June 2013 VO Sandpit, November 2009
  • 24. PREPARDE objectives • capture and manage workflows required to operate the Geoscience Data Journal • from submission of a new data paper and dataset, through review and to publication • develop procedures and policies for authors, reviewers and editors • allow the Geoscience Data Journal to accept data papers as submissions for publication • focus on guidelines for scientific reviewers who will review the datasets • incorporate some technical developments at the point of submission • data visualisation checks • interface improvements • enhance the resulting data publications • put in place procedures needed for data publication in the California Digital Library • interact with the wider scientific and data community • provide recommendations on accreditation requirements for data repositories • engage the user and stakeholder community Engraving of printer using the early Gutenberg letter press during the 15th century. • promote long-term sustainability and governance of Date unknown - estimate 16th - 19th century data journals http://commons.wikimedia.org/wiki/File:Gutenberg_pres VO Sandpit, November 2009
  • 25. Conclusions • The NERC data centres now have the ability to mint DOIs and assign them to datasets in their archives. We have also produced: • guidelines for the data centre on what is an appropriate dataset to cite • guidelines for data providers about data citation and the sort of datasets we will cite • text that will go into the NERC grants handbook telling grant applicants about data citation • We’ve already had users coming to us requesting DOIs for their datasets. • We’re progressing well with data publication through our partnership with Wiley-Blackwell, and discussions with Elsevier and Thompson-Reuters. • The next big step is tackling the thorny issue of peer-review of data – PREPARDE. “We share because we do science, not alchemy.” http://www.keepcalm-o-matic.co.uk/default.aspx#c Jason Priem (Datacite Summer meeting, August 2011) VO Sandpit, November 2009
  • 26. Thanks! Any questions? Image credit: Borepatch http://borepatch.blogspot.com/2010/06/its- not-what-you-dont-know-that-hurts.html VO Sandpit, November 2009
  • 27. A short digression: Citation vs. referencing • Citation – data centre commitment regarding fixity, stability, permanence etc. of a dataset. Demonstrated by assignment of DOI • e.g. Darwin, Charles Robert. The Origin of Species. Vol. XI. The Harvard Classics. New York: P.F. Collier & Son, 1909–14; • Referencing – no data centre commitment regarding fixity, stability, permanence etc. of a dataset. Dataset can still be referenced by URL – but link might be broken • e.g. Paragraph 3, page 42, Darwin, Charles Robert. The Origin of Species, 1859 • We want to be able to reference the individual part of the dataset (word/line/paragraph) without having to commit to assigning a DOI to everything but the dataset (book) • If the dataset is properly frozen, then the reference to a part of it should work fine. • People citing the dataset might want to reference a part of it, and we should make this possible. But we don’t want to commit to DOI-ing every single bit of a dataset! • And just because someone can (and will) reference something in a dataset that’s not DOI-ready – this act should not trigger a DOI-citation VO Sandpit, November 2009
  • 28. Journals – a 17th century technology The first scientific journal, Journal des sçavans (later renamed Journal des savants), was first published on Monday, 5 January 1665. It also carried a proportion of material that would not now be considered scientific, such as obituaries of famous men, church history, and legal reports. It still exists, but is more of a literary journal The first edition of the Philosophical Transactions of the Royal Society of London was on 6 March 1665. That still exists, and continues to publish scientific information to this day. VO Sandpit, November 2009
  • 29. Step XX: Get occasionally side-tracked searching for data specific comics on the internet VO Sandpit, November 2009
  • 30. Censormatic picture from: http://scienceblogs.com/clock/2007/04/framing_politics_bas VO Sandpit, November 2009

Editor's Notes

  1. From http://www.ukoln.ac.uk/ukoln/staff/e.j.lyon/liz-lyon-dcc-roadshow-sheffield-day-1.ppt Evolution or revolution? The changing data landscape  Dr Liz Lyon, Director, UKOLN, University of Bath, UK Associate Director, UK Digital Curation Centre 2nd DCC Regional Roadshow, Sheffield, March 2011
  2. Evolution of communication from http://www.intoon.com/#68559
  3. Note that Wiley-Blackwell and Faculty of 1000 are commercial partners
  4. Landing page picture from http://www.blogkori.com/2009/lets-create-an-effecting-landing-page-to-welcome-new-visitors