Transforming Earth Sciences Big Data into Actionable Products for Disaster Applications Part 2

Thanks to all who contributed to our definition of "Data-Driven Decision Making" exercise! Definitions for “Data-Driven Decision Making”
Contributors: Ross, Sean, Maggi, Karen, Dave, Chung-Lin, Brian, David, Dan
 
Data-Driven Decision Making –
Providing appropriate information
For decision makers to enable situational awareness, where
Appropriate = Standardized, Simplified, Easy Access
 
Data-Driven Decision Making –
A process where key managers (the decision makers) utilize various data assets and inputs from SME/staff to form courses of action (CoAs), then look at pros/cons of each CoA to whittle the list down to 2-3. A war-gaming takes place for each selected CoA, and ultimately a decision is made based on the outcome. The decision rests of the quality and quantity of data that is provided.
 
Data-Driven Decision Making –
Filling the data gaps so that you don’t have to guess. Finding out about unknown unknowns.
 
Data-Driven Decision Making –
Knowledge-based value added “bundle” of data provided in time for helping making adequate decisions timely.
 
Data-Driven Decision Making –
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 –
Allocating and directing resources based on a wider frame of context and information outside the immediate organizational “bubble” – whether human or from a range of sensors that operate on difference scales, and “see” different aspects of the environment. Essentially, expanding the range and scale of vision of those people coordinating response to situations, for the best possible outcome.
 
Data-Driven Decision Making –
Having awareness of a threat via use case then thinking through the use of data (any data) that can accelerate SA (system analysis?) and decision making.
What data is available to me?
How timely is it?
How can I access it and use it?
How can I use data to plan?
Let data lead my decision
 
Data-Driven Decision Making –
There can be good and bad Data-Driven Decision-Making.  Good DDDM is when you use data if expeditious and available and clearly connected to the problem at hand.  DDDM is good when done in conjunction with appropriate value judgments (for example, return on ‘investment’ in prioritizing the savings of certain assets as more important than other assets (e.g., hospitals vs office buildings)).
Bad DDDM is when the data are improperly interpreted or applied erroneously to a situation for which the data are poorly suited or insufficiently representative of the phenomena that need attention. Also trying to use data without rendering explicitly the underlying value assumptions is a case of bad DDDM.
 
Data-Driven Decision Making –
DDDM for disaster response = using existing data & re-tasked satellite impact data & airborne platform; integrate that data using a few selected templates where template may be:
Template1 = {population data gridded + raster image of target area + other stuff}
Template2= {population data gridded + infrastructure vector data + other stuff}
DDDM for disaster planning = using forecast info with uncertainties to populate a risk matrix, e.g., F1 thru F4 x I1 thru I4, where
F1 thru F4 = forecast of Forcing (e.g., precip levels, wind strength, height of storm surge), where F1 is, say, 0mm/r < Precip < 30mm/r, F2= 30 mm/r < Precip < 60 mm/r, etc. with probabilities; and I1 = 0 ft < river level < 3 ft, I2 = 3 ft <river level < 6 ft, etc., with probabilities. Where Fx and It are all model outputs, models are re-run with increasing frequency as disaster looks more likely.