Cal Poly - Data Management and the DMPTool

Carly Strasser | @carlystrasser California Digital Library

Cal Poly Oct 2013

From Flickr by OZinOH

DMPTool The Data Management Planning Tool

Background

Current DMP tools

A walkthrough of DMPTool

DMPTool2

Roadmap

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C. Strasser

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HOI

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Data management Documentation Reproducibility

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DMPs!

A document that describes what you will do with your

data both during your research

and after you complete your project

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What is a data management plan?

For funders: A short plan submitted alongside grant applications

But they all have different requirements and express them in

different ways

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An outline of –  what will be collected –  methods –  Standards –  Metadata –  sharing/access –  long-‐term storage

Includes how and why

•  Saves time •  Increases research efficiency

•  Satisfies requirements

Why prepare a DMP? From Flickr by natalinha

When do you plan?

Yes.

Plan

Collect

Assure

Describe

Preserve

Discover

Integrate

Analyze

Proposal writing

Research

Publication

Ideas

When do you plan?

Remember!

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•  Keep your plan current •  Incorporate changes •  Use as a guide for daily

activities

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Flickr by celikins

Where to start?

Small & Simple •  Document what you know now •  Share the plan with your team •  Avoid procrastination and immobilization

Where to start?

Unruly Data

Researcher

Research Support Office

Data Library / Repository

Computing Support

Faculty Ethics Committee Etc...

DMP?

Courtesy of Martin Donnelly

Who: Support Services & Collaborators

Plan section Support

Information about data PI, co-‐PIs, research staff

Metadata content & format Librarians, data repositories

Policies for access, sharing, reuse

Funder, institute, HIPPA, IRB, users

Long-‐term storage and data management

Librarians, IT staff, data repositories

Budget Sponsored programs office, funder

DMPs: A Short History

Liz Lyon: Dealing with Data 2008

UK funder expectations 2009

2009-‐10

Federal Funding Accountability and Transparency Act 2006

Across the Pond…

2010 2010 –present

DMPs: A Short History

DMP supplement may include: 1.  the types of data, samples, physical collections, software, curriculum

materials, and other materials to be produced in the course of the project

2.  the standards to be used for data and metadata format and content (where existing standards are absent or deemed inadequate, this should be documented along with any proposed solutions or remedies)

3.  policies for access and sharing including provisions for appropriate protection of privacy, confidentiality, security, intellectual property, or other rights or requirements

4.  policies and provisions for re-‐use, re-‐distribution, and the production of derivatives

5.  plans for archiving data, samples, and other research products, and for preservation of access to them

NSF DMP Requirements From Grant Proposal Guidelines:

•  Types of data produced

•  Relationship to existing data

•  How/when/where will the data be captured or created?

•  How will the data be processed?

•  Quality assurance & quality control measures

•  Security: version control, backing up

•  Who will be responsible for data management during/after project?

1.  Types of data & other information

biology.kenyon.edu

C. Strasser

From Flickr by Lazurite

Wired.com

•  What metadata are needed to make the data meaningful? •  How will you create or capture these metadata? •  Why have you chosen particular standards and approaches

for metadata?

2.  Data & metadata standards

•  Are you under any obligation to share data?

•  How, when, & where will you make the data available?

•  What is the process for gaining access to the data?

•  Who owns the copyright and/or intellectual property?

•  Will you retain rights before opening data to wider use? How long? •  Are permission restrictions necessary? •  Embargo periods for political/commercial/patent reasons? •  Ethical and privacy issues? •  Who are the foreseeable data users? •  How should your data be cited?

3.  Policies for access & sharing 4.  Policies for re-‐use & re-‐distribution

•  What data will be preserved for the long term? For how long?

•  Where will data be preserved?

•  What data transformations need to occur before preservation?

5.  Plans for archiving & preservation

From Flickr by theManWhoSurfedTooMuch

•  What metadata will be submitted alongside the datasets?

•  Who will be responsible for preparing data for preservation? Who will be the main contact person for the archived data?

Don’t forget: Budget

•  Costs of data preparation & documentation Hardware, software Personnel Archive fees

•  How costs will be paid Request funding!

dorrvs.com

NSF’s Vision*

DMPs and their evaluation will grow & change over time

Peer review will determine next steps

Community-‐driven guidelines

Evaluation will vary with directorate, division, & program officer

*Unofficially

•  Project name: Effects of temperature and salinity on population growth of the estuarine copepod, Eurytemora affinis

•  Project participants and affiliations: Carly Strasser (University of Alberta and Dalhousie University) Mark Lewis (University of Alberta) Claudio DiBacco (Dalhousie University and Bedford Institute of Oceanography)

•  Funding agency: CAISN (Canadian Aquatic Invasive Species Network) •  •  Description of project aims and purpose: •  We will rear populations of E. affinis in the laboratory at three temperatures and three

salinities (9 treatments total). We will document the population from hatching to death, noting the proportion of individuals in each stage over time. The data collected will be used to parameterize population models of E. affinis. We will build a model of population growth as a function of temperature and salinity. This will be useful for studies of invasive copepod populations in the Northeast Pacific.

•  Video Source: Plankton Copepods. Video. Encyclopædia Britannica Online. Web. 13 Jun. 2011

A DMP Example (1)

•  1. Information about data •  Every two days, we will subsample E. affinis populations growing at our

treatment conditions. We will use a microscope to identify the stage and sex of the subsampled individuals. We will document the information first in a laboratory notebook, then copy the data into an Excel spreadsheet. For quality control, values will be entered separately by two different people to ensure accuracy. The Excel spreadsheet will be saved as a comma-‐separated value (.csv) file daily and backed up to a server. After all data are collected, the Excel spreadsheet will be saved as a .csv file and imported into the program R for statistical analysis. Strasser will be responsible for all data management during and after data collection.

•  Our short-‐term data storage plan, which will be used during the experiment, will be to save copies of 1) the .txt metadata file and 2) the Excel spreadsheet as .csv files to an external drive, and to take the external drive off site nightly. We will use the Subversion version control system to update our data and metadata files daily on the University of Alberta Mathematics Department server. We will also have the laboratory notebook as a hard copy backup.

A DMP Example (2)

•  2. Metadata format & content •  We will first document our metadata by taking careful notes in the laboratory

notebook that refer to specific data files and describe all columns, units, abbreviations, and missing value identifiers. These notes will be transcribed into a .txt document that will be stored with the data file. After all of the data are collected, we will then use EML (Ecological Metadata Language) to digitize our metadata. EML is on of the accepted formats used in Ecology, and works well for the type of data we will be producing. We will create these metadata using Morpho software, available through the Knowledge Network for Biocomplexity (KNB). The documentation and metadata will describe the data files and the context of the measurements.

A DMP Example (3)

3. Policies for access, sharing & reuse •  We are required to share our data with the CAISN network after all data

have been collected and metadata have been generated. This should be no more than 6 months after the experiments are completed. In order to gain access to CAISN data, interested parties must contact the CAISN data manager ([email protected]) or the authors and explain their intended use. Data requests will be approved by the authors after review of the proposed use.

•  The authors will retain rights to the data until the resulting publication is produced, within two years of data production. After publication (or after two years, whichever is first), the authors will open data to public use. After publication, we will submit our data to the KNB allowing discovery and use by the wider scientific community. Interested parties will be able to download the data directly from KNB without contacting the authors, but will still be encouraged to give credit to the authors for the data used by citing a KNB accession number either in the publication’s text or in the references list.

A DMP Example (4)

4. Long-‐term storage and data management The data set will be submitted to KNB for long-‐term preservation and storage. The authors will submit metadata in EML format along with the data to facilitate its reuse. Strasser will be responsible for updating metadata and data author contact information in the KNB.

•  5. Budget •  A tablet computer will be used for data collection in the field, which

will cost approximately $500. Data documentation and preparation for reuse and storage will require approximately one month of salary for one technician. The technician will be responsible for data entry, quality control and assurance, and metadata generation. These costs are included in the budget in lines 12-‐16.

A DMP Example (5)

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matt

Background

Current DMP tools


DMPTool2

Roadmap

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From Flickr by Max Chu

dmptool.org

DMPTool Project

•  Partners started working in January 2011 •  Developed requirements, divided work •  Self-‐funded / In-‐kind

•  Free •  Guides through creating a DMP •  Helps meet funder requirements

•  Supplies questions •  Includes explanation/context provided by

the agency •  Provides links to the agency website

dmptool.org

Wait!

Data management planning is complex & requires dialog

Range of support & understanding

Our focus: •  simplify & scale the common parts •  develop community •  provide incremental improvement

in functionality

From Flickr by ChrisGoldNY

Background

Current DMP tools


DMPTool2

Roadmap

From

Flickr by (L

uciano

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From Flickr by Clonny

Researchers like it here

DMPTool can be added to campus single sign-‐on service

Researchers use campus login to access tool

Access

Customized Resources

Institution-‐specific… •  Help text •  Links to resources & services •  Suggested answers …at different levels •  All DMPs •  All DMPs for a particular

funding agency •  Question within a data

management plan

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From Flickr by OZinOH

DMPTool2

DMPTool Uptake

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Unique Users Plans Institutions

DMPTool 2: Responding to the Community

Coming

Soon!

Plan Creators & Plan

Administrators

2

•  Collaborative plan creation •  Role-‐based user authorization & access •  Better plan templates & resources

Improvements for Plan Creators

2

•  Template creation: •  Better plan template granularity discipline, funder, question •  Better institution granularity

department, college, lab group, … •  Enhanced search and browse of plans •  Access to metrics for reporting & follow-‐up

New administrator Interface

2

What this means for plan creators: •  Better plans •  More granular help •  Local input & assistance

2 Open RESTful API

?

Yelp

Google Maps

APIs

DMPTool

•  Carefully thought out code •  Invisible to user •  Expose specific functionality and/or data

•  Other functionality/data protected

Other stuff

API

Interactions Popularity

API Benefits

Improve functionality Add more functionality

Combine with their services

IMLS Grant

Improving Data Stewardship with the DMPTool

Provide librarians with the tools and resources

to claim the data management education space

blog.dmptool.org

facebook.com/dmptool

Email Tweet me My slides

[email protected] @carlystrasser slideshare.net/carlystrasser

Questions? Website Twitter

Blog

dmptool.org @TheDMPTool blog.dmptool.org

Cal Poly - Data Management and the DMPTool

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Transcript of Cal Poly - Data Management and the DMPTool