Unleashing the BIG in small Science Data (NY Scientific Data Summit)

UNLEASHING THE BIG IN small SCIENCE DATA

Vision and Reality in the Geosciences

Kerstin Lehnert Lamont -Doherty Earth Observatory of Columbia UniversityPalisades, NY, 10964

NYSDS 2015: "Unleashing the BIG in small Science Data"

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Small Science Data have BIG Potential

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Long Tail: Environmental and Earth sciences

The Head: Astronomy, Climate,High Energy Physics, Genomics

“The long tail is a breeding ground for new ideas and never before attempted science.”

(Heidorn, B. 2008: “Shedding Light on the Dark Data in the Long Tail of

Science”)


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• 4 scientists going to Alaska• 5 weeks on remote islands• a boat (with crew)• a helicopter

Small Data, BIG Investment

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2

3GS

Unalaska, fly camp site priorities 1-3; if the helicopter can stay with us for part of the day, we would make local moves within each area, and we would make ground stops at the alternate sites labeled “GS”. We are flexible. We can probably arrange some charter boat support to visit shoreline sites.

GS enroute to Umnak? … just a thought

GS

GS

GS

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NYSDS 2015: "Unleashing the BIG in small Science Data" 4

Collected Samples

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Data Acquisition in the Lab


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Rock crushing

Sample chemistry

Sample analysis

Anticipated Outcomes• Samples

• ~ 250 rock samples• Data

• ~ 200 major element analyses (Lamont-Doherty Earth Observatory)• ~ 150 trace element analyses (University of South Carolina)• 50 U/Pb zircon geochronology (University of Santa Barbara)• 30 Ar-Ar ages (Lamont-Doherty Earth Observatory)• 80 Sr, Nd, Hf and Pb isotope analyses (Lamont-Doherty Earth

Observatory)• Scientific papers

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Small Data “Sharing”


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Monday’s Musings: Beyond The Three V’s of Big Data – Viscosity and ViralityFebruary 27, 2012 by R "Ray" Wanghttp://blog.softwareinsider.org/2012/02/27/mondays-musings-beyond-the-three-vs-of-big-data-viscosity-and-virality/

What Makes Data BIG?


ValueThe sixth ‘V’:

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accessible

small data

findableidentification,

persistence

protection,protocols

context,provenance

re-usableharmonized,

machine-readable

interoperable

BIG DATA

Value

How to Unleash the BIG in Small Data

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accessible

small data

findableidentification,

persistence

protection,protocols

context,provenance

re-usableharmonized,

machine-readable

interoperable

BIG DATA

Value

Domain Repositories8/3/2015


Data Curation Standards

Discipline-specific Data Standards

Domain-specific Data Facilities


Science Community

Domain specific Data facility

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Libraries Archives

CI, Computer Science

Publishers, editors

Discipline-specific data services• Context & provenance metadata

• Semantics• Workflows

Funding Agencies

Data Facilities

Registries

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Data curation servicesCI development


Domain-specific Data Facilities

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Domain Expertise

Community Responsiveness

Operational Reliability

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Quality Utility

Trust

IEDA: A “Long-Tail” Data Facility

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www.iedadata.org

• Multiple core disciplines (focus: solid earth)• High-T Geochemistry• Low-T Geochemistry• Petrology• Marine Geophysics & Geology• Geochronology

• Cross-disciplinary tools & services• Sample registry SESAR• IEDA Data Browser• Portals (GeoPRISMs, USAP-DCC, etc.)• GeoMapApp• Data management support

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Impact of IEDA Services

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from a NSF proposal’s Data Management Plan

Geochemical Observations• Hundreds of chemical properties of different Earth

materials• elemental or oxide concentrations• isotopes and isotopic ratios

• Large diversity of materials• Samples & sub-samples• Chemical & physical preparations

• Wide range of analytical methods• Customized & optimized configurations• Local data reduction code• Data quality measures relevant

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EarthChem: BIG Data for Geochemistry• EarthChem Library (File repository & metadata catalog)

• DOI registration• Long-term archiving• CC license• Data templates & guidelines for data documentation• QC by data managers

• Synthesis Databases (PetDB, EarthChem Portal)• QA/QC by data managers• Data & metadata harmonization• Standards-compliant data model• Service Oriented Architecture

• Sample Registry SESAR• Persistent Unique Identifiers for Samples• Searchable metadata catalog


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EarthChem Data Systems

Metadata

Data Data Data Data Data

EarthChem Library

Data Data Data

Search

Investigators

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Repository

Long-term archiving at CU Libraries

Data templates, review by data curators

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Geochemical Data Standards

Metadata for geochemical methods & samples• Sample location, sampling method, sample preparation, analytical method,

instrument settings, lab, reproducibility measures (standards), normalization• EarthChem XML schema

Geochronology metadata standards Unique sample identifiers (IGSN = International Geo Sample

Number) & metadata profiles

• EarthChem engaged community in development• Worked with publishers on data policies to advance implementation• Provided incentives, tools, & user support to community to

facilitate adoption8/3/2015


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• > 80,000 samples• > 1,660 field programs• > 3 million measurements• > 2,000 references

global compilation of geochemical data for volcanic rocks from the ocean floor & mantle xenoliths

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Data Mining: Search & Filter


Filter by method or concentration

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PetDB Impact• 500 - 800 downloads per quarter• >550 citations in the literature• many fundamental new

discoveries & insights• Disciplinary• Multi-disciplinary• Unanticipated purposes

• new scientific approaches• Statistical rather than hypothetical

reservoirs


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Even BIGGER Geochemical Data

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• Data visualization• Interoperability with modeling databases & software

Inventory:~ 20 million analytical values

for > 850,000 samples

EarthChem PortalAccess to federated geochemical databases

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SESAR (www.geosamples.org)

System for Earth Sample Registration

• Integrating physical samples in the Earth Sciences with CI• Persistent unique identifiers for samples

• IGSN = International Geo Sample Number• Citation and credit for samples!

• Preservation & persistent access of sample metadata• tools and services for users to catalog and manage sample metadata

• APIs• register sample metadata & obtain IGSNs• access to IGSN metadata

• Linking data, publications, and physical samples

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http://www.geosamples.org/

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How can we grow small data across all Geoscience domains?

EarthCube COPDESS

The BIG Question

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EarthCube’s VisionA future state of geosciences cyberinfrastructure that serves the

entire academic geosciences community• facilitates science on the Earth System• simple and easy access to data and information• seamless connection to tools and services• flexible and community-driven development

Partnership between CISE/ACI and GEO: NSF 13-529

Slide provided by Eva Zanzerkia, NSF8/3/2015


EarthCube’s Strategy• Open science

• encourage the publication of all science products so they are discoverable and accessible and can be adapted to solve new problems.

• enable reproducibility• Knowledge-rich components

• ensure rich metadata for scientific resources and products to enable others to understand and reuse them.

• develop advanced analysis techniques and automated learning techniques from for the effective, mining, fusion, and assimilation of data into sophisticated inference models.

• Federated organization• contribute resources designed to interoperate through agreed standards.• coordinate by fostering standards and integration.

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EarthCube Foci That Help Small Data Grow

• Fostering new data communitiesDomain end-user workshopsResearch Coordination Networks

• Developing and adapting new technologies to structure, transform, integrate, document, harmonize data & metadataBuilding Blocks

• Advancing coordination, collaboration, and integration• Community governance• Integrative Activities

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RCN: The Internet of Samples in the Earth Sciences (iSamples)• Build consensus among diverse stakeholders working with physical

samples and their digital representation• investigators, curators, data managers, publishers

• To develop, promote, and implement best practices for sample identification, documentation, citation, and sharing.


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Toward BIG Data for Samples

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EarthCube Technologies

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Projects Data AccessData

DiscoveryData

IntegrationData

Management Modeling Semantics

BCube √ √ √ √CINERGI √ √ √ √DisConBB √ √ √ √ √ √Earth System Bridge √ √ √GeoDeepDive √ √ √ √GeoSoft √ √ √GeoWS √ √ √ √ODSIP √ √ √ √ √GeoLink √ √ √ √ √ √CyberConnector √ √ √ √ √CHORDS √ √ √ √ √Digital Crust √ √ √ √ √EarthCollab √ √GeoDataSpace √ √ √Geosemantics for Long-Tail √ √ √ √

2013

2014

Slide provided by Ilya Zaslavsky, SDSC

EarthCube Integrative Activity:

Partnership to Leverage Existing Repository Services


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EarthCube Integrative Activity: “Interdisciplinary Earth Data Alliance as a Model for Integrating EC Technology Resources and Engaging the Broad Community” (start 9/1/2015)

Coalition for Publishing Data in the Earth & Space Sciences (COPDESS)• Joint initiative of Earth Science publishers and Data Facilities to

better help translate the aspirations of open, available, and useful data from policy into practice.• Reaffirm and ensure adherence to existing journal and publishing policies

and society position statements regarding open data sharing and archiving of data, tools, and models.

• Ensure that Earth science data will, to the greatest extent possible, be stored in community approved repositories that can provide additional data services.

• Statement of Commitment signed by all major Earth & Space Science publishers

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www.copdess.org8/3/2015


Conclusions• Small data grows BIG when properly curated, documented, harmonized,

and integrated.• Domain-specific data facilities are essential to ensure quality of data for

trusted re-use & community engagement.• Integration with publications will augment the flow of data into

repositories and data products.• Partnerships among long-tail data communities allow sharing of

data publication & preservation infrastructure while supporting domain-specific data curation.• Community-wide initiatives such as EarthCube help solve the

entire range of social, technical, and organizational challenges.


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Unleashing the BIG in small Science Data (NY Scientific Data Summit)

Data & Analytics

Transcript of Unleashing the BIG in small Science Data (NY Scientific Data Summit)