The document discusses best practices for preparing data for open publication. It recommends thinking openly and planning early by creating detailed data management plans. It provides examples of repositories like GenBank, ClinicalTrials.gov, FlyBase, Figshare, and Dryad that accept different types of data. The document emphasizes documenting data thoroughly with metadata and standards and following ethical guidelines for sharing and preserving data in the long term.
Talk given at the “Shareable by Design: Making research data available for access” workshop, London School of Hygiene and Tropical Medicine, November 12 2014
Sustainable, Successful Open Data PublicationBrian Hole
Slides from a presentation given by Brian Hole from Ubiquity Press at the 9th International Digital Curation Conference, San Francisco, February 25 2014.
The Journal of Open Archaeology Data and PRIME: Incentivising Open Data Archi...Brian Hole
An introduction to the Journal of Open Archaeology Data (JOAD) and the Publisher, Repository and Institutional Metadata Exchange (PRIME) project, by Brian Hole. Presentation given at the 7th World Archaeological Congress (WAC 7), at the Dead Sea, Jordan, in 18 January 2013.
Talk given at the “Shareable by Design: Making research data available for access” workshop, London School of Hygiene and Tropical Medicine, November 12 2014
Sustainable, Successful Open Data PublicationBrian Hole
Slides from a presentation given by Brian Hole from Ubiquity Press at the 9th International Digital Curation Conference, San Francisco, February 25 2014.
The Journal of Open Archaeology Data and PRIME: Incentivising Open Data Archi...Brian Hole
An introduction to the Journal of Open Archaeology Data (JOAD) and the Publisher, Repository and Institutional Metadata Exchange (PRIME) project, by Brian Hole. Presentation given at the 7th World Archaeological Congress (WAC 7), at the Dead Sea, Jordan, in 18 January 2013.
Introducing PRIME:Publisher, Repository and Institutional Metadata ExchangeBrian Hole
"Introducing PRIME:Publisher, Repository and Institutional Metadata Exchange" – Brian Hole, Ubiquity Press.
OpenAIRE Interoperability Workshop - University of Minho, Braga, Portugal, 8 February 2013
Open Access: Advantages, Funding, Opportunities Brian Hole
"Open Access: Advantages, Funding, Opportunities" - talk given to the Oxford Publishing Society, Oxford Brookes University, by Brian Hole, October 24th 2012.
A talk from 11 Febrary 2013, part of the University College London “Research Programming in Practice” seminar series. Brian Hole, founder of Ubiquity Press and creator of the Journal of Open Research Software wspeaks about a thorny problem for computationally-focused researchers: how do you best build a publication record and enhance your academic reputation when your primary output as a researcher is software? The Journal of Open Research Software is one potential solution, associating a software entity with a peer-reviewed journal publication.
An short introduction to the PRIME (Publisher, Repository and Institutional Metadata Exchange) project, by Brian Hole, at the JISC Managing Research Data programme launch workshop in Nottingham, UK, October 25th 2012.
Introducing PRIME:Publisher, Repository and Institutional Metadata ExchangeBrian Hole
"Introducing PRIME:Publisher, Repository and Institutional Metadata Exchange" – Brian Hole, Ubiquity Press.
OpenAIRE Interoperability Workshop - University of Minho, Braga, Portugal, 8 February 2013
Open Access: Advantages, Funding, Opportunities Brian Hole
"Open Access: Advantages, Funding, Opportunities" - talk given to the Oxford Publishing Society, Oxford Brookes University, by Brian Hole, October 24th 2012.
A talk from 11 Febrary 2013, part of the University College London “Research Programming in Practice” seminar series. Brian Hole, founder of Ubiquity Press and creator of the Journal of Open Research Software wspeaks about a thorny problem for computationally-focused researchers: how do you best build a publication record and enhance your academic reputation when your primary output as a researcher is software? The Journal of Open Research Software is one potential solution, associating a software entity with a peer-reviewed journal publication.
An short introduction to the PRIME (Publisher, Repository and Institutional Metadata Exchange) project, by Brian Hole, at the JISC Managing Research Data programme launch workshop in Nottingham, UK, October 25th 2012.
Great selection of Promotional keyrings from the popular P5 plastic keyrings, or our metal trolley keyring through to the genuine 5mm thick leather keyring that we sell to the franchise motortrade dealers.
Cal Poly - Data Management and the DMPToolCarly Strasser
October 17, 2013 @ Robert E. Kennedy Library, Data Studio, California Polytechnic State University.
Many funders now require researchers to submit a Data Management Plan alongside their project proposals. The DMPTool is a free, online wizard that helps you create a data management plan specific to your project, and provides you with links and resources for ensuring your plan is successful.
Presentation given by Sarah Jones at a seminar run by LSHTM on 6th November 2012. http://www.lshtm.ac.uk/newsevents/events/2012/11/developing-data-management-expertise-in-research---half-day-event
Meeting Federal Research Requirements for Data Management Plans, Public Acces...ICPSR
These slides cover evolving federal research requirements for sharing scientific data. Provided are updates on federal agency responses to the 2013 OSTP memo, guidance on data management plans, resources for data management and curation training for staff/researchers, and tips for evaluating public data-sharing services. ICPSR's public data-sharing service, openICPSR, is also presented. Recording of this presentation is here: https://www.youtube.com/watch?v=2_erMkASSv4&feature=youtu.be
This slide deck provides an overview and resources to respond to the OSTP memo with the subject: Increasing Access to the Results of Federally Funded Scientific Research issued by John P. Holdren in February 2013. It provides resources and information agencies, foundations, and research projects can use to assemble achieve public access to scientific data in digital formats.
Data and Donuts: How to write a data management planC. Tobin Magle
This presentation describes best practices for how to write a data management plan for your research data. Additionally, it provides information about finding funder requirements, metadata standards, and repositories.
Are you interesting in offering data management services at your library but aren’t sure where to start? Then this class is for you! During this session, we will
• Outline the data management topics that are commonly offered in libraries
• Present strategies for how to determine what services might be most useful on your campus and create synergistic partnerships with other university entities
• Dive into how to offer support with data management plans
• Present a case study for using an institutional repository to archive and share research data
• Identify additional training opportunities and open educational resources you can use to develop robust DM services
The class will consist of a mix of presentations, hands on activities, and discussion. So come ready to participate!
This presentation introduced participants to the DC 101 course and was given at the Digital Curation and Preservation Outreach and Capacity Building Workshop in Belfast on September 14-15 2009.
http://www.dcc.ac.uk/events/workshops/digital-curation-and-preservation-outreach-and-capacity-building-workshop
Presentation given at the Consorcio Madrono conference on Data Management Plans in Horizon 2020 http://www.consorciomadrono.es/info/web/blogs/formacion/217.php
Introduction to Data Management PlanningErin Owens
Data management planning is an essential step of preparing to launch a research project, but it's often not given the robust consideration it deserves. External funders are increasingly requiring research funding proposals to include detailed plans for how data will be accurately and effectively collected, maintained, preserved, and shared. Even without a funder requirement, sound data management planning improves accuracy and efficiency of research data collection. This session from the Scholarly Communications Librarian at Sam Houston State University will walk step by step through the process of data management planning; participants will leave with an outline of their own plan and a list of useful resources.
Datat and donuts: how to write a data management planC. Tobin Magle
Good data management practices are becoming increasingly important in the digital age. Because we now have the technology to freely share research data and also because funding agencies want to do more with decreasing research funds, many funding agencies and journals require authors and grantees to share their research data. To provide training in this area, Tobin Magle, the Morgan Library's Cyberinfrastructure Facilitator, is putting on a series of data management workshops called "Data and Donuts". The first session of Data and Donuts will discuss the importance of data management and how to write a data management plan.
This is an update on the status of federal requirements for data sharing in 2015. These slides were presented at ACRL in Portland in March 2015, by Linda Detterman and Jared Lyle of ICPSR, based at the University of Michigan. The session includes overviews of federal requirements, data curation, data management plans, data sharing services, and lots of fun!
On November 21st 2014 at the Tufts University Medford campus and November 25th 2014 at the campus of the University of Massachusetts Medical School in Worcester, the BLC and Digital Science hosted a workshop focused on better understanding the research information management landscape.
Mark Hahnel, CEO of Figshare discussed more specific aspects of the research data management landscape and various approaches to address the growing suite of mandates.
Workshop - finding and accessing data - Cambridge August 22 2016Fiona Nielsen
Finding and accessing human genomic data for research
University of Cambridge, United Kingdom | Seminar Room G
Monday, 22 August 2016 from 10:00 to 12:00 (BST)
Charlotte, Nadia and Fiona presented an overview of data sources around the world where you can find genomics data for your research and gave examples of the data access application for dbGaP and EGA with specific details relevant for University of Cambridge researchers.
Responsible Conduct of Research: Data ManagementKristin Briney
This presentation was given by myself and Brad Houston (http://www.slideshare.net/herodotusjr), for UWM's Responsible Conduct of Research (RCR) series in Fall of 2013. It covers data management plans and practical data management tips. The corresponding handout is also available on Slideshare: http://www.slideshare.net/kbriney/rcr-data-management-handout
Agencies such as the NSF and NIH require data management plans as part of research proposals and the Office of Science and Technology Policy (OSTP) is requiring federal agencies to develop plans to increase public access to results of federally funded scientific research. These slides explore sustainable data sharing models, including models for sharing restricted-use data. Demos of these models and tips for accessing public data access services are provided as well as resources for creating data management plans for grant applications.
Similar to Preparing Data for (Open) Publication (20)
Open Scholarship: more important than ever. OA week 2018Brian Hole
Overview of the Ubiquity Press approach to Open Access and Open Scholarship for Open Access Week 2018. Presentation given at the Levy Library at the Icahn School of Medicine at Mt Sinai, New York, October 24th 2018.
Slide 1: Title Slide
Extrachromosomal Inheritance
Slide 2: Introduction to Extrachromosomal Inheritance
Definition: Extrachromosomal inheritance refers to the transmission of genetic material that is not found within the nucleus.
Key Components: Involves genes located in mitochondria, chloroplasts, and plasmids.
Slide 3: Mitochondrial Inheritance
Mitochondria: Organelles responsible for energy production.
Mitochondrial DNA (mtDNA): Circular DNA molecule found in mitochondria.
Inheritance Pattern: Maternally inherited, meaning it is passed from mothers to all their offspring.
Diseases: Examples include Leber’s hereditary optic neuropathy (LHON) and mitochondrial myopathy.
Slide 4: Chloroplast Inheritance
Chloroplasts: Organelles responsible for photosynthesis in plants.
Chloroplast DNA (cpDNA): Circular DNA molecule found in chloroplasts.
Inheritance Pattern: Often maternally inherited in most plants, but can vary in some species.
Examples: Variegation in plants, where leaf color patterns are determined by chloroplast DNA.
Slide 5: Plasmid Inheritance
Plasmids: Small, circular DNA molecules found in bacteria and some eukaryotes.
Features: Can carry antibiotic resistance genes and can be transferred between cells through processes like conjugation.
Significance: Important in biotechnology for gene cloning and genetic engineering.
Slide 6: Mechanisms of Extrachromosomal Inheritance
Non-Mendelian Patterns: Do not follow Mendel’s laws of inheritance.
Cytoplasmic Segregation: During cell division, organelles like mitochondria and chloroplasts are randomly distributed to daughter cells.
Heteroplasmy: Presence of more than one type of organellar genome within a cell, leading to variation in expression.
Slide 7: Examples of Extrachromosomal Inheritance
Four O’clock Plant (Mirabilis jalapa): Shows variegated leaves due to different cpDNA in leaf cells.
Petite Mutants in Yeast: Result from mutations in mitochondrial DNA affecting respiration.
Slide 8: Importance of Extrachromosomal Inheritance
Evolution: Provides insight into the evolution of eukaryotic cells.
Medicine: Understanding mitochondrial inheritance helps in diagnosing and treating mitochondrial diseases.
Agriculture: Chloroplast inheritance can be used in plant breeding and genetic modification.
Slide 9: Recent Research and Advances
Gene Editing: Techniques like CRISPR-Cas9 are being used to edit mitochondrial and chloroplast DNA.
Therapies: Development of mitochondrial replacement therapy (MRT) for preventing mitochondrial diseases.
Slide 10: Conclusion
Summary: Extrachromosomal inheritance involves the transmission of genetic material outside the nucleus and plays a crucial role in genetics, medicine, and biotechnology.
Future Directions: Continued research and technological advancements hold promise for new treatments and applications.
Slide 11: Questions and Discussion
Invite Audience: Open the floor for any questions or further discussion on the topic.
Introduction:
RNA interference (RNAi) or Post-Transcriptional Gene Silencing (PTGS) is an important biological process for modulating eukaryotic gene expression.
It is highly conserved process of posttranscriptional gene silencing by which double stranded RNA (dsRNA) causes sequence-specific degradation of mRNA sequences.
dsRNA-induced gene silencing (RNAi) is reported in a wide range of eukaryotes ranging from worms, insects, mammals and plants.
This process mediates resistance to both endogenous parasitic and exogenous pathogenic nucleic acids, and regulates the expression of protein-coding genes.
What are small ncRNAs?
micro RNA (miRNA)
short interfering RNA (siRNA)
Properties of small non-coding RNA:
Involved in silencing mRNA transcripts.
Called “small” because they are usually only about 21-24 nucleotides long.
Synthesized by first cutting up longer precursor sequences (like the 61nt one that Lee discovered).
Silence an mRNA by base pairing with some sequence on the mRNA.
Discovery of siRNA?
The first small RNA:
In 1993 Rosalind Lee (Victor Ambros lab) was studying a non- coding gene in C. elegans, lin-4, that was involved in silencing of another gene, lin-14, at the appropriate time in the
development of the worm C. elegans.
Two small transcripts of lin-4 (22nt and 61nt) were found to be complementary to a sequence in the 3' UTR of lin-14.
Because lin-4 encoded no protein, she deduced that it must be these transcripts that are causing the silencing by RNA-RNA interactions.
Types of RNAi ( non coding RNA)
MiRNA
Length (23-25 nt)
Trans acting
Binds with target MRNA in mismatch
Translation inhibition
Si RNA
Length 21 nt.
Cis acting
Bind with target Mrna in perfect complementary sequence
Piwi-RNA
Length ; 25 to 36 nt.
Expressed in Germ Cells
Regulates trnasposomes activity
MECHANISM OF RNAI:
First the double-stranded RNA teams up with a protein complex named Dicer, which cuts the long RNA into short pieces.
Then another protein complex called RISC (RNA-induced silencing complex) discards one of the two RNA strands.
The RISC-docked, single-stranded RNA then pairs with the homologous mRNA and destroys it.
THE RISC COMPLEX:
RISC is large(>500kD) RNA multi- protein Binding complex which triggers MRNA degradation in response to MRNA
Unwinding of double stranded Si RNA by ATP independent Helicase
Active component of RISC is Ago proteins( ENDONUCLEASE) which cleave target MRNA.
DICER: endonuclease (RNase Family III)
Argonaute: Central Component of the RNA-Induced Silencing Complex (RISC)
One strand of the dsRNA produced by Dicer is retained in the RISC complex in association with Argonaute
ARGONAUTE PROTEIN :
1.PAZ(PIWI/Argonaute/ Zwille)- Recognition of target MRNA
2.PIWI (p-element induced wimpy Testis)- breaks Phosphodiester bond of mRNA.)RNAse H activity.
MiRNA:
The Double-stranded RNAs are naturally produced in eukaryotic cells during development, and they have a key role in regulating gene expression .
Richard's entangled aventures in wonderlandRichard Gill
Since the loophole-free Bell experiments of 2020 and the Nobel prizes in physics of 2022, critics of Bell's work have retreated to the fortress of super-determinism. Now, super-determinism is a derogatory word - it just means "determinism". Palmer, Hance and Hossenfelder argue that quantum mechanics and determinism are not incompatible, using a sophisticated mathematical construction based on a subtle thinning of allowed states and measurements in quantum mechanics, such that what is left appears to make Bell's argument fail, without altering the empirical predictions of quantum mechanics. I think however that it is a smoke screen, and the slogan "lost in math" comes to my mind. I will discuss some other recent disproofs of Bell's theorem using the language of causality based on causal graphs. Causal thinking is also central to law and justice. I will mention surprising connections to my work on serial killer nurse cases, in particular the Dutch case of Lucia de Berk and the current UK case of Lucy Letby.
Nutraceutical market, scope and growth: Herbal drug technologyLokesh Patil
As consumer awareness of health and wellness rises, the nutraceutical market—which includes goods like functional meals, drinks, and dietary supplements that provide health advantages beyond basic nutrition—is growing significantly. As healthcare expenses rise, the population ages, and people want natural and preventative health solutions more and more, this industry is increasing quickly. Further driving market expansion are product formulation innovations and the use of cutting-edge technology for customized nutrition. With its worldwide reach, the nutraceutical industry is expected to keep growing and provide significant chances for research and investment in a number of categories, including vitamins, minerals, probiotics, and herbal supplements.
Seminar of U.V. Spectroscopy by SAMIR PANDASAMIR PANDA
Spectroscopy is a branch of science dealing the study of interaction of electromagnetic radiation with matter.
Ultraviolet-visible spectroscopy refers to absorption spectroscopy or reflect spectroscopy in the UV-VIS spectral region.
Ultraviolet-visible spectroscopy is an analytical method that can measure the amount of light received by the analyte.
What is greenhouse gasses and how many gasses are there to affect the Earth.moosaasad1975
What are greenhouse gasses how they affect the earth and its environment what is the future of the environment and earth how the weather and the climate effects.
Multi-source connectivity as the driver of solar wind variability in the heli...Sérgio Sacani
The ambient solar wind that flls the heliosphere originates from multiple
sources in the solar corona and is highly structured. It is often described
as high-speed, relatively homogeneous, plasma streams from coronal
holes and slow-speed, highly variable, streams whose source regions are
under debate. A key goal of ESA/NASA’s Solar Orbiter mission is to identify
solar wind sources and understand what drives the complexity seen in the
heliosphere. By combining magnetic feld modelling and spectroscopic
techniques with high-resolution observations and measurements, we show
that the solar wind variability detected in situ by Solar Orbiter in March
2022 is driven by spatio-temporal changes in the magnetic connectivity to
multiple sources in the solar atmosphere. The magnetic feld footpoints
connected to the spacecraft moved from the boundaries of a coronal hole
to one active region (12961) and then across to another region (12957). This
is refected in the in situ measurements, which show the transition from fast
to highly Alfvénic then to slow solar wind that is disrupted by the arrival of
a coronal mass ejection. Our results describe solar wind variability at 0.5 au
but are applicable to near-Earth observatories.
THE IMPORTANCE OF MARTIAN ATMOSPHERE SAMPLE RETURN.Sérgio Sacani
The return of a sample of near-surface atmosphere from Mars would facilitate answers to several first-order science questions surrounding the formation and evolution of the planet. One of the important aspects of terrestrial planet formation in general is the role that primary atmospheres played in influencing the chemistry and structure of the planets and their antecedents. Studies of the martian atmosphere can be used to investigate the role of a primary atmosphere in its history. Atmosphere samples would also inform our understanding of the near-surface chemistry of the planet, and ultimately the prospects for life. High-precision isotopic analyses of constituent gases are needed to address these questions, requiring that the analyses are made on returned samples rather than in situ.
6. brian.hole@ubiquitypress.com www.ubiquitypress.com / @ubiquitypress
Data management plans
• US:
• National Science Foundation (NSF)
• National Endowment for the Humanities (NEH)
• National Aeronautics and Space Administration (NASA)
• National Oceanic and Atmospheric Administration (NOAA)
• Institute of Museum and Library Services (IMLS)
• Agency for Healthcare Research and Quality (AHRQ)
• Gordon & Betty Moore Foundation
• Alfred P. Sloan Foundation
• UK: Economic and Social Research Council (ESRC)
• Encourage that best practices are followed
• Provide a structured approach to data throughout its
lifecycle
• Now mandated by many funders
• Europe: Horizon 2020
• Other international mandates: http://www.sherpa.ac.uk
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DMP structure
5. Storage and backup
6. Selection and preservation
3. Documentation and metadata
1. Administrative data
4. Ethics and legal compliance
2. Data collection
7. Data sharing
8. Responsibilities and resources
Source: DCC. (2013). Checklist for a Data Management Plan. v.4.0. Edinburgh: Digital Curation Centre.
Available online: http://www.dcc.ac.uk/resources/data-management-plans
8. brian.hole@ubiquitypress.com www.ubiquitypress.com / @ubiquitypress
1. Administrative data
• Basic information e.g. project
title, your name, contact details,
reference numbers / IDs
Here you should record basic information to identify and
contextualise your plan. Identifiers may help to link your DMP
with information held in other systems. You should include:
• A summary of the research to
explain the purpose for which
data are being collected
• Details of related policies and
procedures e.g. institutional data
policy or departmental guidelines
Source: XKCD, http://xkcd.com/97/
9. brian.hole@ubiquitypress.com www.ubiquitypress.com / @ubiquitypress
2. Data collection
• How will you structure and name your folders and files?
• What quality assurance processes will you adopt?
• What standards or
methodologies will you
use to create data?
Here you should consider what data you will collect and how.
• Do your chosen formats and
software enable sharing and
long-term access to the data?
• Are there any existing data
that you can reuse?
Source: SMBC, http://smbc-comics.com/
index.php?db=comics&id=1849
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3. Documentation and metadata
• How will you capture / create this
documentation and metadata?
• What documentation and
metadata will accompany the data?
Here you should consider what
information is needed for the data
to be to be read and interpreted in
the future. Estimate how much
time and effort will be needed to
create this supporting
documentation and ensure that you
allow for sufficient resource.
• What metadata standards will you
use and why?
Source: Gary Larson
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4. Ethics and metadata
• How will you protect the identity of participants if required?
e.g. via anonymisation
• Will data sharing be postponed / restricted? e.g. to publish
or seek patents
Here you should consider any
ethical or legal issues,
particularly in terms of
restrictions they may place on
data sharing.
• Have you gained consent for
data sharing and preservation?
• How will the data be licensed for reuse?
Source: SMBC, http://smbc-comics.com/
index.php?db=comics&id=1957
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5. Storage and backup
• What are the risks to data security
and how will these be managed?
Here you should consider where
the data will be stored and any
implications this has for backup,
access and security.
• Who will be responsible for backup
and recovery?
• Do you have sufficient storage or
will you need to include charges for
additional services?
• How will you ensure that
collaborators can access your data
securely?
Source: SMBC, http://smbc-comics.com/
index.php?db=comics&id=2237
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6. Selection and preservation
• What are the foreseeable research uses for your data?
• Which data should be preserved and potentially shared?
• Which data must be retained or
destroyed for contractual, legal,
or regulatory purposes?
Here you should determine which data
are of long-term value and should be
preserved. Decide how best to preserve
those data, for example by depositing in
repositories.
• What is the long-term preservation plan for the dataset?
• Have you costed in the time and effort required to prepare
the data for preservation and sharing?
Source: XKCD, http://xkcd.com/309/
14. brian.hole@ubiquitypress.com www.ubiquitypress.com / @ubiquitypress
7. Data sharing
• When will you make the data
available?
• Are any restrictions on data sharing required?
Here you should consider which data
you will share and how. The methods
used will depend on a number of
factors such as the type, size,
complexity and sensitivity of the data.
Also consider how people might
acknowledge the reuse of your data
(e.g. via citations) so you gain impact.
• With whom will you share the data,
and under what conditions?
• What action will you take to overcome or minimise restrictions?
• How will potential users find out about your data?
Source: SMBC, http://smbc-comics.com/
index.php?db=comics&id=100
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7. Responsibilities and resources
• Who is responsible for implementing the
DMP, and ensuring it is reviewed and
revised?
• How will responsibilities be split across
partner sites in collaborative research projects?
Here you should assign roles and
responsibilities for all data management
activities. Also carefully consider any
resources needed to deliver your plan.
These costs can usually be written into
grant applications but need to be clearly
outlined and justified.
• What resources will you require to deliver your plan?
• Is additional specialist expertise or equipment required?
Source: SMBC, http://smbc-comics.com/
index.php?db=comics&id=1893
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Online tools
• DMPOnline (UK Digital Curation Centre)
https://dmponline.dcc.ac.uk/
• DMPTool (California Digital Library)
https://dmp.cdlib.org/
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GenBank
• Two upload tools – Bankit for short sequences, Sequin for complex or multiple
sequences
• Sequence data uploaded as a FASTA file
• Immediate or future release instruction
• Citation of a reference paper
• Names of source organisms and any related descriptive data
• Sequence features (e.g. CDS, gene, rRNA, tRNA, with nucleotide intervals and
product names) and topology
• Organism name, applicable source modifiers, location
• Genus and species names (if not previously provided in FASTA file)
• If name is new or unrecognized, provide best known taxonomic lineage
• If genus and/or species names are not known, provide most specific name known
(for example:Bacillus sp., Uncultured bacterium, Uncultured archaeon)
• Most complete name for any synthetic vector (for example: Cloning vector
pAB234, Transfer vector p789Abc)
• Source modifiers include: strain, clone, isolate, specimen-voucher, isolation-
source, country
• Location: organelle (mitochondrion, chloroplast, etc); map and/or chromosome
20. brian.hole@ubiquitypress.com www.ubiquitypress.com / @ubiquitypress
ClinicalTrials.gov
• Web-based data entry system called the Protocol Registration and Results System
(PRS)
• Section 801 of the US Food and Drug Administration Amendments Act of 2007
requires clinical trial registration and the submission of results
• Standard format
• Study Type: ‘Observational’ or ‘Interventional’
• Outcome Measures: The Primary and Secondary Outcome Measure Titles and
Descriptions
• Outcome Measure Time Frame
• Conditions or Focus of the Study
• Intervention Information: Each intervention is entered separately using the
Intervention Type, Name, and Description data elements
• Eligibility: List of key inclusion and exclusion criteria
• Locations
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FlyBase
• FlyBase contains a complete annotation of the Drosophila melanogaster genome
• It also includes a searchable bibliography of research on Drosophila genetics
• Detail which genes feature in
your paper, and FB will link
your paper to those genes for
the next release cycle.
• Provide additional
information during the
submission process about
your publication and help the
Curators to speed up your
curation.
• The whole process takes
about 5mins!
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Dryad
Typical process:
• Authors submit their manuscripts to the journal for consideration.
• Journal provides information about manuscripts to Dryad through automated notices
from the manuscript processing system, which creates a provisional Dryad record for the
data.
• Journal invites authors to archive data in Dryad, through a custom submission link that
brings the author to the provisional record.
• Authors upload their files to Dryad through the submission link supplied by the journal; no
redundant information need be entered and the article details are correct.
• Dryad Curators process and approve the data files and register the Digital Object Identifier
(DOI), a permanent identifier that allows the data to be cited and tracked; curators convey
the DOI to the journal.
• Journal and publisher add the Dryad DOI to all forms of the final article, enabling readers
of the article to access the data.
• Dryad can also provide links to data in other repositories, including sequences in GenBank
and phylogenetic trees in TreeBASE.
• License: CC0
• Cost: $80 / ₹5,000
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Nature Scientific Data
• Papers are called
“data descriptors”
• Fill out and submit a
paper template
• Requires an ISA-tab
metadata file
• Quality of data a major
focus.
• CC-BY/NC
• APC £890 / ₹84,000
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Ubiquity Press
1. The paper contents
a. The methods section of the paper must provide
sufficient detail that a reader can understand how
the resource was created.
b. The resource must be correctly described.
c. The reuse section must provide concrete and useful
suggestions for reuse of the reuse.
2. The deposited resource
a. The repository must be suitable for resource
and have a sustainability model.
b. Open license permits unrestricted access (e.g. CC0),
or access guaranteed if criteria met (must qualify)
c. A version in an open, non-proprietary format.
d. Labeled in such a way that a 3rd party can make
sense of it.
e. Must be actionable.
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The basics of the model
Data papers are short
1) Low barrier data publication
Peer review is quick and objective
2) Online authoring
Low APC: £100 / ₹1,000
Lower cost (straight to XML)
Encourages shorter form
3) Open access only (CC-BY)
4) The publisher is not the repository
No-questions-asked waivers
30. brian.hole@ubiquitypress.com www.ubiquitypress.com / @ubiquitypress
11 Best practices for data publication
• Record your methodology well – think about reproducibility
• Make sure you can export to open formats
• Record your selection and QA processes well
• Choose appropriate metadata standards, record from the beginning
• Ensure you obtain proper consent, and that it allows for open
publication if possible
• Consider the timing of data publication – e.g. to coincide with research
papers
• Consider potential reuse scenarios from the start
• Choose an appropriate repository
• Think about possible restrictions and access conditions early – justify
and seek to minimise
• Plan to publish with maximum dissemination – data paper?
• Allocate time and funding for data publication in grant proposals
