Registration Open for Data Rights & Data Wrongs workshop, 12/10 at #UCDavis

Data Rights & Data Wrongs

A workshop organized by
Innovating Communication in Scholarship (ICIS)

University of California, Davis

Date & Time: December 10, 2014 from 9:00 am – 5:00 pm

Location: MPR, Student Community Center, UC Davis

Register: https://www.eventbrite.com/e/data-rights-data-wrongs-tickets-14079810091

Full Agenda: http://icis.ucdavis.edu/?page_id=329

Keynote talks:
Dr. Christine Borgman, Professor & Presidential Chair, iSchool, UCLA
John Wilbanks, Chief Commons Officer, Sage Bionetworks

Scholars are increasingly subject to pressures from funding bodies, disciplinary norms, professional and personal ethics, and institutional directives to share their research data and make it available for reuse. There is, however, a great deal of heterogeneity across the research enterprise with respect to what is meant by ‘data’ and ‘data sharing,’ why data sharing is deemed important, and what data management strategies are considered most effective. Moreover, data are often difficult and costly to produce and share. Therefore, many scholars view these as a significant product of their intellectual labor for which they should receive some sort of credit towards tenure and promotion, authorial recognition through citation, or financial compensation. While balancing all of these considerations is desirable to promote increased access to data, it is difficult to guarantee that the concerns of all research stakeholders will be met given (1) the diverse forms that data can take, as well as the mobility and malleability of data given widespread access to new information technologies, (2) the complex and variable legal status of data as not-quite/not-always property, and (3) the ethical considerations and legal restrictions implicated in the sharing and reuse of data related to sensitive topics such as personal health information, national security, and vulnerable populations. This workshop will address theoretical concerns and pragmatic solutions that can be harnessed to help researchers comply with requirements or desires to share their data in ways they deem appropriate for their goals.

11_07 Data Rights flyer.pdf

NIH Announces Revised Genome Data Release Policies

Just got notified of this by the UC Davis Med. School grants administration: NOT-OD-14-124: NIH Genomic Data Sharing Policy.  Lots of interesting things in here including a summary of the comments that they received on the draft policy.

I have copied some of the more interesting and relevant bits below:

  • Sharing research data supports the NIH mission and is essential to facilitate the translation of research results into knowledge, products, and procedures that improve human health.  NIH has longstanding policies to make a broad range of research data, in addition to genomic data, publicly available in a timely manner from the research activities that it funds. 
  • The public comments have been posted on the NIH GDS website. http://gds.nih.gov/pdf/GDS_Policy_Public_Comments.PDF
  • The statement of scope remains intentionally general enough to accommodate the evolving nature of genomic technologies and the broad range of research that generates genomic data.
  • Several comments were submitted by representatives or members of tribal organizations about data access.  Tribal groups expressed concerns about the ability of DACs to represent tribal preferences in the review of requests for tribal data.
  • The GDS Policy expects that basic sequence and certain related data made available through NIH-designated data repositories and all conclusions derived from them will be freely available.  It discourages patenting of “upstream” discoveries, which are considered pre-competitive, while it encourages the patenting of “downstream” applications appropriate for intellectual property.  
  • NIH expects investigators and their institutions to provide basic plans for following this Policy in the “Genomic Data Sharing Plan” located in the Resource Sharing Plan section of funding applications and proposals.  Any resources that may be needed to support a proposed genomic data sharing plan (e.g., preparation of data for submission) should be included in the project’s budget. 
  • Large-scale non-human genomic data, including data from microbes, microbiomes, and model organisms, as well as relevant associated data (e.g., phenotype and exposure data), are to be shared in a timely manner. 

Victoria Schlesinger in Al Jazeera America on Open Data Pros and Cons

Got interviewed last week by Victoria Schlesinger about open science and open data issues and she has now posted her article: Scientists threatened by demands to share data | Al Jazeera America.  The article includes a discussion primarily about the push for more open release of data (and also a bit about papers) and some of the challenges associated with this push.  There are some good quotes in the article both from Schlesinger’s text and from some key players in the field of data access including:

  • Christopher Lortie:  “There will be fantastic discoveries, and that’s all that really matters,” says Lortie.
  • From Schlesigner (a quote I do not agree with all of but some may like the metaphor): Sharing the results of scientific research is a bit like unveiling a newly built house, and scientists generally want it widely viewed, so the growth in open access publishing is a boon for most. Sharing data, on the other hand, is comparable to handing over the architectural plans and building materials used to construct the house. Others can scrutinize the quality of work and reuse the basic components to build their own house. That raises fears about discovery of errors and theft of future research ideas.
  • Heather Piwowar: “I think the public thinks that we’re all learning from everyone else’s work. That’s not true, and furthermore, it’s not true in ways that are even worse than you might think,” says Piwowar=
  • Me: “People are busy,” says Jonathan Eisen, a genetics professor at the University of California, Davis. “Everyone is overwhelmed with life and email and, in academia, trying to get funding and write papers. Whether something is open or not open is not highest on the priority list. There’s still need for making people aware of open science issues and making it easy for them to participate if they want to.”
  • Titus Brown: “My general attitude about open science is that I’d much rather be relevant. In science, that’s harder than anything else,” says Titus Brown, an assistant professor at Michigan State University who runs a genomics, evolution and development lab and practices open science. “If I make my work available, I have a higher chance of being relevant.” 
  • It has transformed the way we do science across biological scales, from the molecular all the way up to studying whole ecosystems,” says Carl Boettiger, a postdoctoral student at UC Santa Cruz. “The value is in enabling science to progress faster.”
The article is worth a look …

Not sure what to make of this new "Datasets.Com" effort from Hindawi

Just got this email and I thought I would share.  Not sure what to make of this effort.  I do support the sharing of data sets but I am think we probably do not need a whole new cadre of data journals to handle this data.

But there is a spread of what some have called “Predatory” open access publishers (see http://metadata.posterous.com/83235355 for example).  Hindawi, who is behind this, seems to have a mix of good and predatory tendencies and this seems like it may fit into the more predatory categorization.  And I just thought it would be good to bring this a bit more into the open to discuss it.

Dear Dr. Eisen,

My name is Safa Tahoon and I am a Journal Developer for the Hindawi Publishing Corporation. We are in the process of launching a new peer-reviewed, open access journal titled Dataset Papers in Genetics, which will publish Dataset Papers in all areas of genetics research, and I am writing to invite you to join the Editorial Board of this new journal.

Dataset Papers in Genetics is part of a new journal platform that Hindawi is developing called Datasets International (http://www.datasets.com). The main objective of Datasets International is to help researchers in all academic disciplines archive, document, and distribute the datasets produced in their research to the entire academic community. In addition to publishing a series of journals devoted to the dissemination of Dataset Papers, Datasets International hosts the underlying data behind these Dataset Papers and makes it accessible to all researchers worldwide.

The journal will be run using a collaborative editorial model which is designed to provide a fast peer review process for all submitted manuscripts. The journal will be edited by a distributed Editorial Board, and it aims for an average review time of 4 weeks from submission until a final decision has been reached.

Manuscripts that are submitted to the journal will be sent to a number of Editorial Board Members (typically each manuscript will be sent to at least 5 Editors), who will have two weeks to provide either a recommendation for the publication of the manuscript, along with a written commentary detailing any improvements that the authors should make to their manuscript, or a written critique of why the manuscript should not be published.

After the two-week period has elapsed, if the majority of the editorial evaluations recommend the manuscript be rejected, the manuscript will be rejected. If all the editorial evaluations that are received recommend that the manuscript be accepted for publication, the manuscript will be accepted. Otherwise, the editorial evaluations will be anonymously communicated to all of the Editors who participated in the peer review process. Each Editor will be given an additional week to review the feedback of the other Editors and to either confirm or revise their earlier editorial recommendations. If the majority of the editorial evaluations that are received by the end of this second round of review recommend the manuscript be accepted for publication, the manuscript will be accepted. Otherwise, the manuscript will be rejected. If the manuscript is accepted for publication, the names of the Editors who recommended the publication of the manuscript will be published alongside the ma!
nuscript. More information on the journal is available on the following web pages:

http://www.datasets.com/ (Datasets International Home Page)
http://www.datasets.com/journals/genetics/ (Journal Home Page)
http://www.datasets.com/journals/genetics/workflow/ (Editorial Workflow)
http://www.datasets.com/journals/genetics/editors/ (Editorial Board)

The journal will be published using an open access model, which allows disseminating scholarly articles by removing the access barriers imposed by the subscription model, in order to make the full-text of all published articles freely available for any interested reader. In this model the publication costs of an article are covered in the form of Article Processing Charges, which are publication fees paid from the research budget of accepted authors. In this model authors retain the copyright of their work, and we make every possible effort to ensure that the full-text of every published article is both visible and accessible to all potential readers.

Manuscripts that are submitted by the members of the Editorial Board of Dataset Papers in Genetics to the journal will automatically receive a 50% reduction in their Article Processing Charges.

Please do visit the web pages above and let me know if you have any questions or comments. We hope you will accept to join the Editorial Board of the journal and I will be looking forward to hearing from you soon.

Best regards,

Safa Tahoon

——————————
Safa Tahoon
Journal Developer
Hindawi Publishing Corporation
http://www.hindawi.com/
——————————

Draft post cleanup #3: The Open Knowledge Foundation

Yet another post in my “draft blog post cleanup” series.  Here is #3 from just a few weeks ago:

Interesting article in PLoS Biology:  PLoS Biology: The Open Knowledge Foundation: Open Data Means Better Science.  It discusses many issues in open science especially as they relate to open data.

Some links from this paper are worth checking out

This article reminds me that I keep meaning to push for the development of a “Datawatch” system much like the “RetractionWatch” systems of Ivan Oransky. I have discussed this with Ivan but we have not yet gotten around to doing it …