ClouD Dataverse
Mercè Crosas, Institute for Quantitative Social Science, Harvard University
@mercecrosas
MOC Workshop, October 3, 2017, Boston University
Our Institute provides a technology Solution to Data Sharing
Institute for Quantitative Social Science, Harvard University
@IQSS
An open-source software to share, cite, and find data.
Developed at Harvard's Institute for Quantitative Social Science
with the contribution of an active and growing community.
2006 (we started)
2017
dataverse.org
26 Dataverse installations serving hundreds of institutions
HOW Researchers SHare & Use data with dataverse
Harvard Dataverse Repository
A public repository for research data
> 70,000 datasets total
> 49,000 datasets uploaded to Harvard Dataverse repository
200 datasets/month
> 340,000 files
4,000 files/month
> 2.5 M downloads
60,000 downloads/month
Datasets Added
Downloads
dataverse.harvard.edu
King, 1995, Replication, Replication
Altman and King, 2007, A Proposed Standard for the Scholarly Citation of Quantitative Data
Altman et al, 2001, A Digital Library for the Dissemination and Replication of Quantitative Social Science
King, 2007, An Introduction to the Dataverse Network as an Infrastructure for Data Sharing
Crosas, Honaker, King, Sweeney, 2015, Automating Open Science for Big Data
Crosas, 2012, The Dataverse Network: an open source application for sharing, discovering, and preserving research data
Altman and Crosas, 2013, The Evolution to Data Citation: from principles to implementation
Crosas, 2013, A Data Sharing Story
2014, Joint Declaration of Data Citation Principles
Pepe et al, 2014, How Do Astronomers Share Data?
Goodman et al, 2014, Ten Simple Rules for the Care and Feeding of Scientific Data
Castro et al, 2015, Achieving Human and Machine Accessibility of Cited Data
Sweeney, Crosas, Bar-Sinai, 2015, Sharing Sensitive Data with Confidence: The DataTags System
Meyer et al. 2016, Data Publication with the Structural Biology Data Grid Supports Live Analysis
Wilkinson et al, 2016, The FAIR Guiding Principles for Scientific Data Management and Stewardship
Bierer, Crosas, Pierce, 2017, Data Authorship as an Incentive to Data Sharing
Our Contributions to Enhance data sharing
2017
Findable
Accessible
Interpoperable
Reusable
Data should be ...
Wilkinson et al. , 2016, "The FAIR Guiding Principles for Scientific Data Management and Stewardship" Nature Scientific Data
FAIR DATA in Dataverse
Data Files
Metadata
Data Licenses, User Agreements,
Restrictions
Data Citation with Persistent Identifier
Versions
APIs
+
Cloud Dataverse combines the power of cloud computing and storage with access to thousands of datasets from a feature-rich data repository platform
Why Cloud Dataverse?
- Big Data should also be FAIR Data
- Datasets are replicated to the Cloud for efficient access and reuse
- Computing on a dataset is enabled directly from any repository
What we have built
- Dataverse integration with Swift storage
- Compute access to MOC from a dataset page in Dataverse
- Temporary url to access restricted files in MOC
In progress
- Replicate data from any Dataverse to Cloud Dataverse
- Upload data directly in Swift; publish dataset from Swift to Dataverse
NEXT
- Implement Swift Access Control List (ACL) for file restriction
- Support InCommon for MOC to use same credentials as in Dataverse
InTegration with other ProJects
Billion Object Platform
BIG GEODATA exploration and analytics
Data Provenance
track the original source of a Dataset
Pasquier, Lau, Trisovic, Boose, Coutierer, Crosas, Ellison, GIbson, Jones, Seltzer, 2017, If These Data Could Talk, Nature Scientific Data (Data Provenance examples from CERN and Harvard Forest)
Data Privacy
classify and handle datasets based on Their privacy level
Harvard Data Privacy Tools Project: privacytools.seas.harvard.edu
DataTags Project: datatags.org
Text
Thanks
@mercecrosas
@iqss
scholar.harvard.edu/mercecrosas
dataverse.org
MOC Workshop - Cloud Dataverse
By Mercè Crosas
