1. Developing a Conservation Data
Sharing Network for the Island of
Maui, Hawai„i
Samuel N.R. Aruch
Natural Resource Data Solutions LLC
Penn State MGIS- Capstone

2. • Background
• Conservation partner relationships and needs
• Maui Data Hui
• Partner data infrastructure
• Data sharing implementation
• Benefits of data sharing
• Lessons learned
• Next steps

3. Background
Terrestrial conservation implementation in Hawaiʻi
• Many challenges
• Ecosystem level threats
• Management across land owner boundaries

4. Partner relationships
The Nature
Conservancy
Maui
Program
West Maui East Maui
Mountains Watershed
Logistics Goals
Watershed Logistics Partnership
Partnership
Maui
Invasive
Species
Committee

5. Partner relationships

6. Needs – Extreme and costly logistics in remote areas

7. Needs - Track the status of work performed

8. Needs – Measure effectiveness and share accomplishments

9. Needs- Locate and share threat information
Treated
Observed
Misidentified

10. Maui Data Hui (group)
• A bottom up approach
• Informal group of mid-level on the ground managers
• Meeting since 2008
• 2 - 4 x per year
• Sharing tools and ideas
• Voluntary collaborative standards

11. Collaborative standards- Fences
• Fence Name
• Fence Section
• Status (complete, partial, proposed, unmaintained, removed)
• Source (hand-drawn, GPS)
• Agency Built (TNC, EMWP, NPS, etc…)
• Agency Managed (TNC, EMWP, NPS, etc…)
• Purpose (pig, deer, dirt bike, cattle, etc…)
• Material (hogwire, mesh, barb, hog panels, etc…)
• Apron (yes, no, partial)
• Height ( # in feet)
• Length (from GIS)
• Last Check (from database)
• Condition (from database)

12. Individual partner database infrastructure
• Local data management via linked MS Access & ArcGIS desktop
• Each program has unique needs (i.e. sensitive data, capacity, and
work flows)
• Standards are implemented when developing

13. Partner infrastructure - “Real time” local data management

14. Partner infrastructure - “Real time” local data management

15. Partner infrastructure - “Real time” local data management

16. The next step: developing a data sharing infastructure:
ool
Enterprise level data sharing structure for conservation partners on
the island of Maui.
Working with two examples of shared data sets
• Ungulate exclosure fences (cows, pigs, deer, goats)
• Weed control

17. Data sharing infrastructure
• Retrofit existing workflow (do not create more work)
• Participants have access to raw data
• Data can be served over the web
• Prototyped with UH – CCRT infrastructure
• VPN to connect local access database to SQLServer
• MS SQLServer and ArcGIS Server to store and serve data
• Still under development / testing

18. Data sharing implementation – 3 different scenarios
Check Local user
in/ Out interface and
data tables
Shared
data server
Hosted
User
interface only
Aggregated/ Aggregated/
Filtered filtered data
Local user
Export interface and
data tables

19. Sharing workflow
Local database
User chooses to log in to server

20. Initiate sync on existing database

21. Login to server

22. Status message
Local database
User chooses to log in to server
Status message alerts user to new data to send

23. Status message

24. Sending data
Local database
User chooses to log in to server
Status message alerts user to new data to send
User chooses to send data to server

25. User sends data to the server

26. Sharing workflow
Local database
User chooses to log in to server
Status message alerts user of new data to send
User chooses to send data to server
Server
Data is aggregated and served

27. Master data can be imported or linked to user's database

28. Sharing workflow
Local database
User chooses to log in to server
Status message alerts user of new data to send
User chooses to send data to server
Server
Data is aggregated and served
Web

29. Data as a service

30. Data as a service

31. Benefits of data sharing
• Watershed to archipelago scale decision support tools
• Communication with funders, managers, and partners
• Enhance strategy, efficiency, and collaboration
• Accountability
• Continuity in perpetuity

32. Products– Watershed management and resource analysis
* Sample data for illustration only

33. Products – Landscape scale status assessments
* Sample data for illustration only

34. Products – Strategy, efficiency, and collaboration

35. Maui Data Hui lessons learned
• Build momentum, collaboration, and relationships
• Work from the bottom up and top down
• Data compatibility and consistency
• Information security and trust
• Don‟t reinvent the wheel
• Usability
• Time

36. Long term goals
• More partners / more data / more fun
• Experiment with more sharing tools
• Mobile tools for managers
• Build long term support

37. Potential for partnership data sharing

38. Summary
• Hawaiʻihas landscape scale ecosystem threats
• Conservation partnerships have shared goals and logistics
• Conservation partnerships need to share data
• The Maui Data Hui is facilitating data sharing from the bottom up
• Building momentum and collaboration
• Measurable benefits of collaboration
• Open to new ideas and tools

39. Maui Data Hui collaborators and contributors
• East Maui Watershed Partnership (EMWP)
• West Maui Mountains Watershed Partnership (WMMWP)
• Maui Invasive Species Committee (MISC)
• The Nature Conservancy of Hawaiʻi – Maui Program (TNC- Maui)
• Puʻu Kukui Watershed Preserve (PKW)
• Plant Extinction Prevention Program – Maui (PEP)
• Leeward Haleakalā Watershed Restoration Project (LHWRP)
• USGS – Pacific Basin Information Node (USGS- PBIN)
• Maui Forest Bird Recovery Project (MFBRP)
• Department of Land and Natural Resources Natural Area Reserves
System - Maui (Maui NARS)
• Haleakalā National Park
• University of Hawaiʻi- Center for Conservation Research and
Training (UH - CCRT)
• Hawaiʻi Conservation Alliance (HCA)

40. Sam Aruch
Natural Resource Data Solutions
808-895-4542
samaruch@gmail.com