Data Management Needs and Challenges for Telemetry Scientists Josh M London Wildlife Biologist, Polar Ecosystems Program National Marine Mammal Laboratory NOAA NMFS Alaska Fisheries Science Center

Temptation to identify biologists as the source for the raw data

The Tip of a Complex Iceberg hypothesisagency needs/mandatesfunding initiatives opportunistic vs. planned tag design/vendortag programming Deployment of tags (location, age/sex, time) Data Management data quality control synthesis movement model Publications Contract reports Status/Listing Review derived products Field Work and Study Design Narrowing Bottleneck Many biologists lack the skills and training for effective, scalable database design and data management practices

Field Work & Tag Deployment  When? Where?  Which Tag/Vendor?  Which Age? Which Sex? (Do we have a choice?)  Tag Programming  Deployment Length (attachment type)

Limited Tools for Managing Raw Telemetry Data ‘raw’ data  via Argos as CSV/Text  Process w/ Vendor Software (behavior data)  Typically output as CSV  Field data about animal (e.g. ID, species, sex, age, health) needs  Explore ‘raw’ data  Address hypotheses  Visualize movement/use  Synthesize w/ dependent (e.g. health, age) and independent data (e.g. other animals, remote sensed)

Biologists Not Trained in Large Scale Data Management Biologists  Excel and/or Access  ESRI ArcMap (shapefiles)  Google Earth  Mouse Click Interaction  Programming (visual basic, R, python) recipe driven … not developers Data Manager  Postgres/PostGIS, Oracle, MySQL, SQL Server  Normalization and Efficient Design  Scripting, Jobs, Transactions  Data Integrity  Automation, Reproducible

My Perspective To address complex questions related to marine mammal telemetry and understanding animal ecology, I had to become more of a data manager …And, in the process, I’ve become less of a biologist Start (2006)  Argos Monthly CDs  SatPack Access Database  Excel Files (limited to 56k)  Large, Flat Tables  No Central Repository Current System  Nightly FTP Argos Push  Nightly Data Processing  CSV/External Oracle Table  PL/SQL Procedures  Developed/Designed with Training via Google Search

My Perspective Current Limitations  Data access requires a minimum level of technical skills (basic SQL, Oracle framework, Oracle APEX, R spatial tools, ArcMap)  Single Point of Access/Failure (me)  Limited Documentation of Design  Design May Not be Optimal/Appropriate  Main Objective to Provide Data to Analysts – Not necessarily designed for providing data to public

My Perspective Greatest Needs – Research Program  Data Management and Design Consultation  Data Design & Documentation Portal (user-friendly metadata)  Low Tech Exploration Tools  Database and Application Developers (data flow and data input)  Training Opportunities

My Perspective Greatest Needs – External to Program?  Provide Meaningful Public Access to Data  A Clear Data Sharing Policy w/ Best Practices  Encourage/Facilitate Scientific Collaboration  Meet Agency Needs and Requirements  How to Communicate Scientific Knowledge in the Modern/Digital Age–sharing knowledge/expertise just as important as sharing data  Publish Data Once

My Perspective Challenges / Road Blocks  Limited Funds and Priorities – appropriate resources for doing the priority analysis and science not available, let alone the resources to distribute data responsibly  Database design/management often in the hands of the least skilled users  IT Policies, Investments, and Infrastructure Varied Across Institutions  No standard(s) for communicating and sharing ‘raw’ animal telemetry data. What is ‘raw’ data?