Data Systems Integration Committee of the Earth Science Data System Working Group (ESDSWG) on Data Quality

Robert R. Downs1 Yaxing Wei2, and David F Moroni3

1 rdowns@ciesin.columbia.eduNASA Socioeconomic Data and Applications Center (SEDAC), CIESIN, Columbia University

2 weiy@ornl.gov Oak Ridge National Laboratory, Oak Ridge, TN,

3 david.f.moroni@jpl.nasa.gov NASA Jet Propulsion Laboratory, Pasadena, CA

2016 Winter ESIP MeetingWashington, DC January 6-8, 2016

Information Quality Cluster: Introduction, Reporting, and Use Case Tutorial Friday, 8 January 2016, 11:00 - 12:30.

Government support is acknowledged for the authors’ work. R. R. Downs: NASA contract NNG13HQ04C for the Socioeconomic Data and Applications Distributed Active Archive Center (DAAC);

Y. Wei: NASA contract NNG14HH39I for the Oak Ridge National Laboratory (ORNL) DAAC;D. F. Moroni: NASA contract with the Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA.

Data Systems Integration within the Data Quality Working Group

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Usability Recommendations

Accuracy, Precision and

Uncertainty (APU) Recommendations

DistinguishabilityRecommendations

Applicability Recommendations

Prioritized Recommendations

Data Systems Integration

Recommendations

Science and Applications

Recommendations

Low Hanging FruitRecommendations

Implementation Strategies & Solutions to Address LHF Recommendations

Sixteen Use Cases Relevant to the NASA Earth Science Data and Information System

Data Systems Integration Committee: Mission, Goals, and Objectives

• Mission– Identify and document implementation strategies for selected

recommendations for DAACs to Capture and Describe data quality, Facilitate Discovery and Enable Use of scientific data.

• Goals and Objectives:– For each of the 4 LHF Recommendations:– Identify corresponding relevance to committee.– Identify corresponding Stakeholders.– Identify and document an implementation strategy (with examples).– Assess operational maturity in terms of both Software/Technology and

Standards/Documentation

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• Data Producers – Improved capabilities for preparing data with good quality

information for archiving and dissemination• Data Distributors

– Improved capabilities for capturing and managing data quality information

• Data Users– Improved capabilities for finding and using data of interest

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Data Systems Integration Committee: Targeted Stakeholder Benefits of Planned Activities

Selecting Capabilities as Potential Implementation Solutions* for Data Systems Integration

• Address one or more prioritized recommendations• Identified benefits to improve data usage • Implemented at one or more data centers• Limited implementation time requirements• Modest implementation and maintenance costs

*Low Hanging Fruit

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Data Center Science TeamCapturing Data Quality Information

request documentation from investigators on the extent of error introduced into data products ...

develop capabilities for investigators to describe the extent of error introduced …

Describing Data Quality Information

provide enough publicly available information so users do not need to contact the data center

describe quality flags in the data documentation and in the FAQs

Discovery of Data Quality Information

develop capabilities for users to refine search query results by selecting among choices of quantifiable data quality criteria, such as confidence levels ...

identify quantifiable data quality criteria, such as confidence levels and the values of quality flags, that can be used as criteria for refining search queries.

Enabling Use of Data Quality Information

provide users with a tool to identify inputs, …, that contributed to each pixel.

create tools to capture into a variable, sensor inputs, … that contributed to each pixel.

Source: Downs, Peng, Wei, Ramapriyan, Moroni. 2015. Enabling the Usability of Earth Science Data Productsand Services by Evaluating, Describing, and Improving Data Quality throughout the Data Lifecycle.

Sample Recommendations for Improving the Usability of Data Quality Information throughout the Data Lifecycle

Sample Inventory of Current Implementation Strategies and Solutions for Data Systems Integration

Potential Implementation Solutions

Data Center - Investigator Communication

Metadata Creation & validation

Guidance & Instruction

Reference / Help Desk

Metadata Compliance Checker

X

Data Quality Guide Document

X X

Science Data Working Group

X

Data Quality Section in Data Management Plan

X X

Data Management Plan / Guidelines

X X

FAQ Development and Analysis

X

7Source: Downs, Peng, Wei, Ramapriyan, Moroni. 2015. Enabling the Usability of Earth Science Data Productsand Services by Evaluating, Describing, and Improving Data Quality throughout the Data Lifecycle.

Data Quality Concepts for Further Discussion

• Characteristics of Data Quality Reviews– Process, facilitator, reviewer representation, focus

• Attributes of Data quality– Null Values, Error, Noise, procedure or instrument

deviation, corrections, etc. • Data quality for a specific purpose

– Conditions for data integration, disciplinary analysis, longitudinal comparison, environmental planning, etc.

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• We very much appreciate the contributions of the members of the Data Systems Integration Committee of the Earth Science Data Systems Working Group on Data Quality!

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