Nature article on data sharing

Thank you for sharing

Initiatives to make genetic and medical data publicly available could improve diagnostics — but they lose value if they do not share with other projects.....

....The imperative to share data remains an esoteric issue for much of the public, and one that is easily obscured. Companies or researchers who talk the talk of sharing but do not actually walk the walk should be challenged. Data sharing is too important to be turned into meaningless marketing speak.

Nature

 

520,

 

585

 

(30 April 2015)

 

doi:10.1038/520585a

RECODE: Policy Recommendations for Open Access to Research Data

Policy Recommendations for Open Access to Research Data

https://blogs.openaire.eu/?p=198

The RECODE ten overarching recommendations:

1. Develop aligned and comprehensive policies for open access to research data.
2. Ensure appropriate funding for open access to research data.
3. Develop policies and initiatives that offer researchers rewards for providing open access to high quality data.
4. Identify key stakeholders and relevant networks and foster collaborative work for a sustainable ecosystem for open access to research data.
5. Plan for the long-term, sustainable curation and preservation of open access data.
6. Develop comprehensive and collaborative technical and infrastructure solutions that afford open access to and long-term preservation of high-quality research data.
7. Develop technical and scientific quality standards for research data.
8. Require the use of harmonized open licensing frameworks.
9. Systematically address legal and ethical issues arising from open access to research data.
10. Support the transition to open research data through curriculum-development and training.

DataOne DM Education modules online

https://www.dataone.org/education-modules

Education Modules

Below are links to education modules in powerpoint format that you can download and incorporate into your teaching materials. Materials are licensed as CC0 and you may enhance and reuse for your own purposes. All slides can be previewed in the embedded slideshare viewer below. We also provide 1 page synopses (with space for contact information) that can be used to promote Data Management training events at your institution.

The topics covered include:

Lesson 01: Why Data Management (.pptx)
Trends in data collection, storage and loss, the importance and benefits of data management, and an introduction to the data life cycle. Last update: May 2012.
One page handout (.pdf)
Supporting hands-on exercise (.pdf)

Lesson 02: Data Sharing (.pptx)
Data sharing in the context of the data life cycle, the value of sharing data, concerns about sharing data, and methods and best practices for sharing data. Last update: Jul 2012.
One page handout (.pdf)
Supporting hands-on exercise (.pdf)

Lesson 03: Data Management Planning (.pptx)
Benefits of a data management plan (DMP), DMP components, tools for creating a DMP, NSF DMP information, and a sample DMP. Last update: May 2012.
One page handout (.pdf)
Supporting hands-on exercise (.pdf)

Lesson 04: Data Entry and Manipulation (.pptx)
Best practices for data entry, data entry and data manipulation tools. Last update: Apr 2015.
One page handout (.pdf)
Supporting hands-on exercise (.pdf)
Supporting data for Exercises 04, 05, 07, 08 (.zip)

Lesson 05: Data Quality Control and Assurance (.pptx)
Types of data errors, best practices for data quality assurance and control to prevent and correct errors. Last update: May 2012.
One page handout (.pdf)
Supporting hands-on exercise (.pdf)
Supporting data for Exercises 04, 05, 07, 08 (.zip)

Lesson 06: Data Protection and Backups (.pptx)
The difference between data protection, backup, archiving and preservation, best practices for backing up and preserving data. Last update: Jul 2012.
One page handout (.pdf)
Supporting hands-on exercise (.pdf)

Lesson 07: Metadata (.pptx)
Metadata defined, information included in metadata, selection of metadata standards, the value and utility of metadata. Last update: May 2012.
One page handout (.pdf)
Supporting hands-on exercise (same for Lesson 07 and Lesson 08) (.pdf)
Supporting data for Exercises 04, 05, 07, 08 (.zip)

Lesson 08: How to Write Quality Metadata (.pptx)
Best practices for writing high quality metadata. Last update: May 2012.
One page handout (.pdf)
Supporting hands-on exercise (same for Lesson 07 and Lesson 08) (.pdf)
Supporting data for Exercises 04, 05, 07, 08 (.zip)

Lesson 09: Data Citation (.pptx)
Data citation defined, benefits of data citation, examples and best practices for data citation. Last update: Apr 2015.
One page handout (.pdf)
Supporting hands-on exercise (.pdf)

Lesson 10: Analysis and Workflows (.pptx)
Types of data analyses, introduction to reproducibility, provenance, and workflows, informal (conceptual) and formal (executable) workflows. Last update: May 2012.
One page handout (.pdf)
Supporting hands-on exercise (.pdf)

Lesson 01-10: A complete set of all 10 modules (.pptx)

Slide previews

NHMRC Statement on Data Sharing

http://www.nhmrc.gov.au/grants-funding/policy/nhmrc-statement-data-sharing

Covers:

How to share research data – Practice and limitations
When to plan for sharing research data – A life-cycle approach
When to plan for sharing research data – A life-cycle approach
Data accessibility and quality

Western Australian Whole of Government Open Data Policy

The Western Australian Government is one of the largest collectors of data in the State as a result of conducting its business.  This data remains a relatively untapped resource that could be used by other agencies or sectors to develop new or better products or services that meet citizens' needs.  It can also lead to better policy decisions and business practices in government and improve public sector accountability and transparency.

The Western Australian Whole of Government Open Data Policy (the Policy) aims to facilitate greater release of government data to the public in appropriate and useful ways to generate value and productivity.

A draft of the Policy was released for consultation:

• HTML
• PDF (164 KB)
• DOC (42 KB)

Thank you for your interest in the WA Government open data policy.  The comment period has now closed.

For further information, please email coag-wa@dpc.wa.gov.au or telephone (08) 6552 5444.

Full info

NHMRC Statement on Data Sharing

http://www.nhmrc.gov.au/grants-funding/policy/nhmrc-statement-data-sharing

One of NHMRC’s primary roles is to fund high quality health and medical research and ensure that the Australian community receives the health and economic benefits from that investment. An important part of this responsibility includes enabling researchers and members of the community to access the outputs of research.

NHMRC acknowledges the importance of making data publicly accessible.

NHMRC encourages data sharing and providing access to data and other research outputs (metadata, analysis code, study protocols, study materials and other collected data) arising from NHMRC supported research.

This aligns with researchers’ responsibilities under the Australian Code for the Responsible Conduct of Research (2007), which provides advice on the storage, management and privacy of research data (section 2.5-2.7) and states: “Research data should be made available for use by the other researchers unless this is prevented by ethical, privacy or confidentiality matters.”

Below is a general guide for researchers to consider data and metadata management when planning and conducting research. This document will be updated periodically to reflect new input and information.

Comment by Karen Visser: This is an excellent representation of how to plan for data fits within funding obligations Figure 1 – Data during the research life-cycle. In the lifecycle diagram above, stages essential for all health and medical research are represented in blue, whilst additional research type specific processes are indicated in green. 

Data Stories - bringing data to life

For those who haven’t seen this yet, the DCC has been collaborating with the RDA Engagement Interest group to create the Your Data Stories blog to share examples of good and 'not-so-good' practice in research and scholarly data management, and demonstrate the benefits of data sharing and reuse. 

There are some wonderful stories there already - check them out at

http://datastories.jiscinvolve.org/wp/?utm_source=Pipeline+Newsletter&utm_campaign=cb527f71b2-Pipeline_April_201504&utm_medium=email&utm_term=0_a11772394f-cb527f71b2-323365553

Research Data Explored: Citations versus Altmetrics

The study explores the citedness of research data, its distribution over time and how it is related to the availability of a DOI (Digital Object Identifier) in Thomson Reuters' DCI (Data Citation Index). We investigate if cited research data "impact" the (social) web, reflected by altmetrics scores, and if there is any relationship between the number of citations and the sum of altmetrics scores from various social media-platforms. Three tools are used to collect and compare altmetrics scores, i.e. PlumX, ImpactStory, and Altmetric.com. In terms of coverage, PlumX is the most helpful altmetrics tool. While research data remain mostly uncited (about 85%), there has been a growing trend in citing data sets published since 2007. Surprisingly, the percentage of the number of cited research data with a DOI in DCI has decreased in the last years. Only nine repositories account for research data with DOIs and two or more citations. The number of cited research data with altmetrics scores is even lower (4 to 9%) but shows a higher coverage of research data from the last decade. However, no correlation between the number of citations and the total number of altmetrics scores is observable. Certain data types (i.e. survey, aggregate data, and sequence data) are more often cited and receive higher altmetrics scores.

Download the full article at http://arxiv.org/abs/1501.03342  (submitted on 14 Jan 2015)

National Oceanic and Atmospheric Administration Releases Plan for Public Access to NOAA-Funded Research

In early April 2015, the US National Oceanic and Atmospheric Administration (NOAA) released the, “NOAA Plan for Increasing Public Access to Research Results” (PDF). The plan details the extensive, long-term investments that NOAA has made in the preservation of and access to digital data and how the plan will build upon the existing data and publication policies, infrastructure, and ongoing work of the NOAA Library. The plan notes that administrative and reporting requirements for researchers will be minimized.

<snip>

NOAA will continue and possibly enhance its ongoing data-management training and workforce development activities. NOAA will also look to external activities to supplement its efforts in this area.

Finally, NOAA is also working with other federal agencies in support of a “Research Data Commons,” a shared space for federally funded extramural research output.

Read more at: http://www.arl.org/news/community-updates/3576-national-oceanic-and-atmospheric-administration-releases-plan-for-public-access-to-noaa-funded-research#.VSxSmKMiPcu

National Institute of Standards and Technology Releases Plan for Public Access to NIST-Funded Research

The US National Institute of Standards and Technology (NIST) released on April 3, 2015, a “Plan for Providing Public Access to the Results of Federally Funded Research” (PDF). The NIST plan calls for making peer-reviewed scholarly publications and associated data that result from NIST funding publicly accessible. The plan applies to both NIST employees and grantees.
<snip>
As of October 2015, there will be standard language regarding public access to data and publications in the terms and conditions for grants and contracts.
<snip>
NIST approaches access to digital data in three ways: through data management plans (DMPs), an Enterprise Data Inventory (EDI), and a Common Access Platform (CAP) that is the public access infrastructure.  Some of these efforts build on earlier work underway in response to the May 2013 Obama Administration memorandum on “Open Data Policy—Managing Information as an Asset.”

Data management plans in NIST grant proposals must contain (1) a summary of grant activities that lead to the generation of data, (2) data types that are generated by grant activities, (3) how data will be stored and preserved, and (4) how data will be reviewed and made publicly available. The DMP may also include an explanation of why data sharing and preservation are not included of the plan. “Reasonable costs” for data sharing and preservation may be included in the DMP as well. As of October 2014, DMPs are required for all NIST-funded research.

The Enterprise Data Inventory is a catalog of the data sets that result from NIST-funded research as well as metadata and information about how and where the data sets can be accessed. The Common Access Platform will be a production-level infrastructure that will include persistent identifiers and metadata for publicly available NIST data. The NIST plan notes that the CAP will be interoperable within NIST and possibly with other federal agencies.

Finally, the NIST plan includes a list of metrics that will be used to evaluate compliance with the NIST Public Access Policy. The plan also includes a series of timelines regarding development and implementation of the policy, infrastructure, processes, and outreach and education, all specified for both data and publications.

More at: http://www.arl.org/news/community-updates/3574-national-institute-of-standards-and-technology-releases-plan-for-public-access-to-nist-funded-research#.VSr99KMiPcu

PLoS One. 2015 Feb 23;10(2):e0117619. doi: 10.1371/journal.pone.0117619. eCollection 2015.

Researcher perspectives on publication and peer review of data.

Kratz JE1, Strasser C1.

Abstract

Data "publication" seeks to appropriate the prestige of authorship in the peer-reviewed literature to reward researchers who create useful and well-documented datasets. The scholarly communication community has embraced data publication as an incentive to document and share data. But, numerous new and ongoing experiments in implementation have not yet resolved what a data publication should be, when data should be peer-reviewed, or how data peer review should work. While researchers have been surveyed extensively regarding data management and sharing, their perceptions and expectations of data publication are largely unknown. To bring this important yet neglected perspective into the conversation, we surveyed ∼ 250 researchers across the sciences and social sciences- asking what expectations"data publication" raises and what features would be useful to evaluate the trustworthiness, evaluate the impact, and enhance the prestige of a data publication. We found that researcher expectations of data publication center on availability, generally through an open database or repository. Few respondents expected published data to be peer-reviewed, but peer-reviewed data enjoyed much greater trust and prestige. The importance of adequate metadata was acknowledged, in that almost all respondents expected data peer review to include evaluation of the data's documentation. Formal citation in the reference list was affirmed by most respondents as the proper way to credit dataset creators. Citation count was viewed as the most useful measure of impact, but download count was seen as nearly as valuable. These results offer practical guidance for data publishers seeking to meet researcher expectations and enhance the value of published data.

Open Inform - Information about open education and openness

Open Inform will support a community in generating conversation and information about open education, and more broadly openness. This is an opportunity to promote engagement in a range of openness topics such as OSS, OpenEd, OER, Open Governance, Open Access research and data,Open Textbooks, Open Standards, Open Content, Licensing and so on. The goal … to build capacity and provide information about Open Education.

See: http://open-inform.info

Scientific Data approves UK Data Service as recommended data depository

The UK Data Service is delighted to be the first UK-based social science repository to be listed as a recommended repository by Scientific Data.

Scientific Data, the open-access data journal of Nature Publishing Group, publishes the Data Descriptor article type and recommends that datasets accompanying manuscripts be deposited in established and trusted repositories, such as the UK Data Service ReShare. This ensures that these datasets are stably preserved for the longer-term, thoroughly peer-reviewed, and will be easily accessible to the research community after publication.

Using the UK Data Service’s ReShare repository, researchers can easily upload data collections in the social sciences, humanities and medical research, describe these collections and select the access conditions and licences that are best suited to their data. Researchers can then decide whether to publish these data either as fully open data or as safeguarded data that are made available under the UK Data Service’s End User Licence. Safeguarded data may be selected when anonymised data have been collected from human participants (via surveys or interviews), but where there is a risk of participant de-identification resulting from potential linkage to other data. The ReShare repository has inbuilt safeguards, such as requiring registration in order to access safeguarded datasets. This allows social science data to be shared and made available for research as openly as possible. The UK Data Service also reviews these data before their release, so researchers can be confident that they meet with the necessary ethical and legal requirements.

The UK Data Service fully supports the concept of scientific transparency and is increasingly working with journals to help support their policies. The collaboration with Scientific Data gives social science and humanities researchers the opportunity to increase the discoverability of their data via submission of a Data Descriptor, whilst maintaining UK Data Service’s safeguarding of sensitive data.

See: http://ukdataservice.ac.uk/news-and-events/newsitem/?id=4046 

UK Data Service releases guidelines for data purchase

Data purchase – guidelines for researchers

The UK Data Service has produced guidelines for researchers who are considering purchasing data for research.

These guidelines provide a set of generic guiding principles and questions to pose when planning data purchases. Prepared by the UK Data Service team, whose experts advise depositors and help researchers plan pathways to data access, the aim of these guidelines is to help researchers plan their data access requirements more effectively and to reduce the amount of time spent on legal and contractual issues. By following the guidelines, researchers will also ensure that they comply with the relevant research data policies and accountability, especially for ESRC-funded research.

The guidelines were initially developed to support the ESRC's Big Data Network Phase 2 Business and Local Government Data Research Centres, but they are now being released to the wider data research community for the benefit of all researchers.

Data Purchase Guidelines

Collections Development Selection and Appraisal Criteria

Collections Development Policy