[Esip-disasters] Special "Trusted Data" Discussion this 5th Thursday March 30, 1pm PDT/4pm EDT

[Moe, Karen (GSFC-407.0)[EMERITUS]]

Please join us for a special web meeting to discuss the characteristics and features of a proposed ESIP “trusted data” designation for data sets, focusing on disasters-related support. Our session will be at our normal Thursday time on the 5th Thursday for this special session. Please note that we will have our regular telecom next week, April 6.

Below are my notes from the 2017 Winter Meeting, provided as a starting point. The goal for this special session is to define what we mean by “trusted data.”  We need a working definition for ESIP, as we pursue what you might call a new ESIP service. Your ideas and contributions are needed! I anticipate this will be a highly interactive working session.

Thanks,
Karen


Please join my meeting from your computer, tablet or smartphone.
https://www.gotomeeting.com/join/691265765

You can also dial in using your phone.

United States: +1 (872) 240-3311

Access Code: 691-265-765


ESIP Disasters Lifecycle Cluster and Information Quality

Our key driver for information quality is associated with our goal to define and develop “ESIP-certified” trusted data products to support Data-Driven Decision Making for disasters applications.

Trusted Data concepts (source: tdwi.org)

·      People use data that they trust, leading to greater consistency, compliance and accuracy in their data-driven processes

·      People want to feel confident that their data is in the best condition possible because such trusted data makes their jobs easier and their actions more accurate, timely, effective, and compliant (conforming to their requirements).

·      Trusted data should come from carefully selected sources, be transformed in accordance with data’s intended use, and be delivered in formats and time frames that are appropriate to specific consumers.

·      Trusted data will meet conditions of completeness, quality, age, schema, profile, and documentation.

·      From https://tdwi.org/articles/2011/05/18/the-six-cs-of-trusted-data.aspx

o   Complete – for decision making

o   Current – freshness, speed of delivery

o   Consistent – Metadata management can improve consistency by documenting data’s origins and meanings.

o   Clean – This is typically the result of data quality techniques, such as standardization, verification, matching, and ‘de-duplication’. Users’ perceptions of data quality are probably the biggest challenge to trust, which is why data quality techniques are critical. Quality decisions and operational excellence both depend on clean data.

o   Compliant – meets required standards (e.g., quality, security, privacy, also federal regulations)

o   Collaborative – collaboration over data helps ensure that data management and business management goals are aligned.



Trusted Data – some characteristics driving the need for trusted data in disasters applications (ESIP Winter 2016)


·      Provide actionable information

·      Sharable / technology interoperability

·      Common operational data / common view

·      Sensitive information sharing framework / trusted location

·      Expedited access


Data-Driven Decision Making defined (ESIP Summer 2016, a sample)


·      Providing appropriate information for decision makers to enable situational awareness; where appropriate, data is: standardized, simplified, easy to access.

·      Knowledge-based value added “bundle” of data provided in time for helping to make adequate, timely decisions.

·      Integrated data & information in easily recognized formats—by the decision makers; easily incorporated in the decision makers’ Common Operation Picture; relevant to the decision makers’ task at hand.

·      Data-Driven Decision Making is when you use data if expeditious and available, and clearly connected to the problem at hand.


Drivers for the Disasters Response User Community (ESIP Winter 2017)


·      Need to capture user feedback to measure data usefulness (productivity); OGC is addressing feedback mechanisms

·      Determine pathway for generating collection level metadata for NASA systematic data

·      Trust, safety and speed are key drivers for Data-Driven Decision Making


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