Take home message Metadata Standardize data formats Separate data storage and analysis utilities...

Take home message

• Metadata

• Standardize data formats

• Separate data storage and analysis utilities

• Adaptive software development

Challenges

• Broad spatial and temporal requirements

• Aquatic ecology is an emerging discipline

• Topic is highly technical

• BiOp Workflows are in development

• Professional norms

Broad Spatial and Temporal Requirements

Ecology as an Emerging Discipline

Nadkarni 2001. Enhancement of forest canopy research, education, and conservation in the new millennium. Plant Ecology. 153: 361-367.

“Because informatics activity ultimately reflects the science, we concluded that a database cannot become an effective integrative tool until the science itself is integrated. Paradoxically, the science cannot easily become integrated without the use of database tools.”

Ecology as Emerging Discipline

Nadkarni 2001. Enhancement of forest canopy research, education, and conservation in the new millennium. Plant Ecology. 153: 361-367.

Ecology as Emerging Discipline

“Our reviews of tools applicable to canopy science discovered a wealth of software tools used in other disciplines for displaying information about complex structures, processes, and datasets, but the best of these were not easily portable to other disciplines.”

Nadkarni 2001. Enhancement of forest canopy research, education, and conservation in the new millennium. Plant Ecology. 153: 361-367.

Topic is highly technical

• Habitat condition

• Population sampling

• Survival and growth

• Genetics

BiOp Workflows In Development

Cartoon from UC RTT Analysis workshop

The cartoon shows a blackboard with the equations that describe Einstein's grand unifying theory. The caption was modified to say “RME Simplified”.

Professional Norms

• Ecology is exploratory and independent– Analysis is highly iterative– Trained as independent researchers– Rewarded for innovation

• Database developers design, then build– Trained within engineering programs– Has worked well for business applications– Rewarded for meeting requirements on time

Approaches

• Dissect into components– Monitoring type– Integration of Monitoring– Historic / future– Requirements / design solutions / implementation

• Manage for uncertainty– Broaden scope of information to be managed– Metadata-driven– Standardize data formats– Separate storage from analysis

• Adaptive software development

• Monitoring Type– Status and Trend– Implementation– Effectiveness

• Site specific• Watershed scale • Process oriented or mechanistic

Dissect Into Components

• Integration– High-level discuss– Should not impede progress on other

components

Dissect Into Components

• Historic– Summary or reporting metrics– Evaluate cost/benefit ratio for field-level

observations (Tetra Tech, 2008)

• Future– Field-level observations– Standardized format – Full metadata

Dissect Into Components

• Requirements– Scientists, managers, data stewards

• Design solutions– Developers, programmers, and data stewards– Feedback from scientists and managers

• Implementation– all

Dissect Into Components

Manage for Uncertainty

• Broaden scope of information– Resource management questions– Monitoring program design and evaluation

• Metadata-driven Applications– Smart tools (lessons from social networking)

• Standardize data formats

• Separate data storage and analysis utilities

Broaden Scope of Information

Resource Management

Questions

Monitoring Program Design and Evaluation

MetadataField

ObservationsWhoWhenWhereHowWhy

>0 and <=1500>60 and <=250>3 and <=90 >3 and <=250 >60 and <=1000

Metadata-driven Applications

Metadata-driven Applications

Standardize Data Formats

• Data Exchange Network• Survey Type Specific• Metadata Standard

Growth of the Aquatic Resources Schema

0

200

400

600

800

1000

1200

1400

1600

Oct 2005 Nov 2006 Apr 2007 Sept 2007 Apr 2008 May 2009

Cumulative AttributesNumber of Attributes

Growth of the Aquatic Resources Schema

Separate Data Storage and Analysis Utilities

Adaptive Software Development

• Waterfall approach– Requirements driven– Well defined workflows– Learned in training programs

• Adaptive approach– Mission focused, risk driven, feature based– Adaptation to emergent state of the project– Deliverable specifications defined broadly– Normal state of affairs

Adaptive Software Development

• http://en.wikipedia.org/wiki/Adaptive_Software_Development• http://en.wikipedia.org/wiki/Agile_software_development• http://en.wikipedia.org/wiki/Scrum_(development)

Take home message

• Metadata

• Standardize data formats

• Separate data storage and analysis utilities

• Adaptive software development