Protocol Deployment Challenges

1. Protocol Deployment Challenges from a Data Manager’s perspective Gordon DicusUCBN, Moscow ID

2. Presentation Overview • Identify primary protocol deployment challenges • Discuss challenges, including some examples • Briefly contrast small Network vs large Network • Draw some conclusions

3. Primary Challenges • Communication on protocol data needs and solutions • Flexibility in responding to protocol changes (variables, data collection tools, analysis, etc.) • Smooth procedures for getting data into protocol DB • Data summaries and analyses/reports that are useful to Protocol Leads, Park Managers, Network staff, and Cooperators • Fitting core data management roles/responsibilities to individual protocol staff and Network staff/time [“Get the data out!”] [“HELP!”]

4. Communication on protocol data needs • Imperative that Data Manager is well informed on protocol data needs and data collection strategies • Complex protocols may require postponing some DB components until Protocol Lead refines methods & analysis • Data Managers must adequately convey time required to develop (and to modify!) DB components • Manage expectations regarding data management roles (consider skills of Protocol Lead and staff, if any, and workload of Network Data Manager and staff, if any) • Protocol Leads must understand and meet Network requirements for data products and documentation (Project Tracking and/or annual Close Out/Review process)

5. Flexibility in DB for protocol changes • Minimize changes to data variables ! • NRDT table structure standards help ease burden of design modifications • Big headache – how to maintain old data in revised DB to serve multi-year summary and analysis ? • Digital data collection strategies and data analysis requirements will change, so DB revisions are an on-going need

6. Procedures for getting data into DB • Paper field datasheets are simple and some folks desire a paper archive record, but… • Digital data collection is efficient and can eliminate transcription errors Some basic examples…

7. Aspen monitoring (UCBN) • Using MS Access database running on tablet PC (Samsung Q1) • allows robust Access data integrity rules and validation procedures to control data entry • data entry accomplished in one process • tablets put in “Otter boxes” on rainy field days • must accept that no paper record exists for vegetation plot data

8. Sagebrush-steppe monitoring (UCBN) • Abandoned data collection on tablet PCs • difficulty seeing tablet PC screen in bright sunlight • weight and durability concerns for crews traversing long distances over rough terrain • Currently using PDA devices (Archer) running Data Plus software • less robust data integrity and validation capability • relatively quick data entry on small, durable PDAs • must accept additional processes to transfer field data into protocol MS Access database

9. Benthic Marine monitoring (PACN) • Using photo analysis to determine benthic cover on coral reefs and presence/absence of disease symptoms • Reef “rugosity” and marked coral colony measurements recorded on paper datasheets • Recruitment tiles, deployed for 6 months, analyzed in lab to identify coral species and count number of juveniles • Photo analysis results are processed for transfer into protocol MS Access database; other data is manually entered into database • manual data entry components require careful QA/QC procedures to minimize and document transcription errors • photo analysis component requires attention to detail in managing digital photos and PhotoGrid output files

10. Water quality monitoring (UCBN) • Using Hydrolab data loggers to collect water chemistry data • Aquatic macroinvertebrate sampling work uses paper field datasheets; results come back from lab in MS Excel format • Using Aquarius Time-Series software to process and analyze water chemistry data • Output from Aquarius Time-Series (raw and corrected data) and macroinvert lab results are processed for transfer into protocol MS Access database • still in development; will facilitate export of data to NPStoret and sharing/posting of annual and multi-year datasets • requires considerable processing to transfer data into protocol MS Access database

11. Getting out Protocol data/summaries • Annual Reports, Resource Briefs, and Network website used to share protocol data and analyses • Science Advisory Committee meetings are another opportunity for sharing protocol findings • Frequent communication and emailing of data files meets more immediate data needs • NPS Data Store for certified Protocol data products • VSIMS has promise for dynamic sharing of Protocol data (ability to download selected data?)

12. Data Management roles – Considerations… • Who is Protocol Lead and staff ? • (Cooperator, Network staff, Park staff, Contractor) • How fit data management roles to skill/time constraints of Protocol staff vs Network staff ? • (allocating sample points, loading points on GPS, preparing field maps and datasheets, file management for PDA/Data logger files and photos, QA/QC, certifying data, etc.)

13. Staffing – Large vs Small Network • Large Network • Data Manager • DB Developer • GIS Specialist • Data Management Assistant • NPS IT support • Small Network • Data Manager • Part-time, temp-hire assistant • minimal NPS IT support

14. Data Management roles – Creative Solutions • Assign more to Protocol Lead • pre-field prep (sample points, GPS loading, field maps & datasheets) • annual file management (file naming and organizing within file directory structure) • Find new ways to meet Network data mng needs • organize for quarterly website updates by contractor • organize for annual updates to NBib and NPSpp • share GIS staff among Networks and/or with Parks

15. Conclusions • Be FLEXIBLE • Keep it SIMPLE ! • COMMUNICATE • Support Network ACCOUNTABILITY