DCO-DS: Moving Forward DCO Synthesis Meeting. Oct. 29-30, 2015 - PowerPoint Presentation

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DCO-DS: Moving Forward

DCO Synthesis Meeting. Oct. 29-30, 2015

DCO-DS = DCO Data Science

Vision…

“Our vision is to develop, facilitate, and maintain sustained multi-way engagement of carbon scientists in multi-scale local to global networks” [for the transformation of our understanding of carbon in Earth].

Organization is required so

participants

can carry out their mission(s)

Those participants (by

defn

.) may never be in a single organization -> virtual

organization

Virtual Organizations as Socio-Technical Systems

‘ …a geographically distributed organization whose members are bound by a long-term common interest or goal, and who communicate and coordinate their work through information technology’ (

Ahuja

)

‘These members assume well defined roles and status relationships within the context of the virtual group that may be

independent of their role and status in the organization employing them’

(

Ahuja

et al., 1998)

Technology

Communication Patterns

Organizational

Structure

Virtual Organization

Feature:

Outcomes/ values

Dynamic versus static

Evolvable/ ecosystem-like

Heterogenetic tolerance

Attributes of the organization

Roles/ responsibilities

Scale or scalability

Strategy…

Mapping…

goal -> use case

participation -> team(s), vetting, acceptance

outcomes/ value -> goals, metrics, evaluation, incentives, data/information/ knowledge projects, responses, decisions

dynamic -> agile working format, small iterations

evolution -> rapid development, evaluation and iteration (open)

Methodology…

DCO-DS Evaluation

Form as key input to DCO-DS

Focused on the evaluation of Deep Carbon v

irtual

Observatory

Evaluation questions will help determine

DC

vO's role inIncreasing members, activity and awareness of DCO activitiesEnabling search, access, exchange and use of data & information for DCO scientific and educational needsNeeds to further integrate with DCO Members' essential technologiesPhased roll-out to begin early OctWave 1: Executive Committee, Secretariat, Community leads, selected othersWave 2: DCO SSCs, EngagementWaves 3, 4, 5, 6: DCO Communities

Value Philosophy

Value focuses on organizational outputs (or outcomes) rather than inputs

For example: Deployed knowledge and skills vs research budgetsValue relates to benefit of outcomes, rather than outcomes themselvesProducts and services enabled by knowledge and skills

Value implies relative, useful, and usable outcomes

Beneficiaries have to understand and

appreciate

Credit: B. Rouse (BEVO) 2008

Leveraging

existing data resources

Interface between DCO Data Portal and other data repositories – key part of post-2019 efforts (e.g. Spring 2015 effort with CoDL/ MBL)

Incorporate specific metadata requirements into the DCO Knowledge Store

Extend DCO Ontology for incorporation of other repository data,

and/or

u

tilize existing schemaProvide data in a variety of formats for use (non-specialists)Populate the metadata and data repository for DCO projects that do not already have their own portalWork on and develop new boundary activities

DCO-DS Boundary Activities

Moving Forward

A technology refresh for major platform components for the DCO network, and a “network” succession plan Prioritized efforts based on evaluations (Nov-Dec)

Inputs from DCO synthesis discussions and post-2019 committees/ task groupsSignificant efforts on data registration and data legaciesAnd continue to work on existing and develop new boundary activities

Questions?Comments?

Patrick West, westp@rpi.edu, Peter Fox,

pfox@cs.rpi.edu The Team: Lead: Peter Fox, Staff: Patrick West, Stephan Zednik and John Erickson, Post Doc: Marshall Ma, Graduate Students: Han Wang, Hao Zhong, Ahmed Eleish

DCO Knowledge Graph Analytics

Identified key areas of DCO for analysis and

visualization

, initially:

Publications and publication keywords

User registrations

DCO Member areas of expertise

Instance Creation statistics: who is creating what and associated with what communities.What would you like to see?

DCO Knowledge Graph Analytics

Publication Subject Area Word Cloud

Current Work:

Thermodynamic

Data Rescue

A large number of geoscience publications contain publication

datasets

that are not expressed external to the publication text

Extracting, organizing, and reusing these datasets is valuable

Data Science Team and Extreme Physics and Chemistry community member Mark Ghiorso identified thermodynamic datasets about the enthalpy and entropy of chemicals

Current

Work: Geo Sample curation and IGSN

Have

GeoSample

as a class in DCO ontology and collect the core metadata items for sample registration in the DCO data portal;

Interface between the

DCO IGSN Allocation

Agent and the IGSN registry agent, with two potential functionalities:Assign IGSN to a sample record through the DCO data portal in collaboration with UT funded activityUse IGSN to import sample records from existing repositories to the DCO data portal, if there is a mature IGSN metadata API

Future Work: Instrument Reporting and

Browsing*

Progress to-date:

Reporting on DCO-funded Instrument use by Projects and Field Studies

Referencing DCO Instrument use within Grant Summary Reports

within Instrument grants and related project/field study grants

Future work: The Instrument Browser

Dynamically generated instrument list and instrument summary pageA faceted search interface for instrumentsInstrument discovery based on nature of use, data collected, projects and point of contact* Outcome from the DCO Data Science day at RPI in 2014!!!

Future Work: Deep Carbon Science Trend Analysis

Natural Language Processing (NLP) based analysis of Deep Carbon publication corpus

Extracts entities and relations from the corpus

Constructs a Deep Carbon Knowledge Base consisting of unified entities and relations

Provides structured knowledge for downstreaming applications and analysis

Includes retrieval of authoritative metadata into DCO Knowledge Graph

Includes Deep Carbon Science Visualization Dashboard