The need of a data exchange format on IAS management

Transcript

1. IAS management
   The need for a data exchange format on IAS /
   wildlife management
   D. Oldoni, J. Hillaert, T. Adriaens
   

   View Slide

2. Table of content
   1. The IAS/wildlife management data landscape
   2. Data exchange format
   3. Draft of a data exchange format for IAS management
   4. The trajectory towards an adopted standard
   

   View Slide

3. Table of content
   1. The IAS/wildlife management data landscape
   2. Data exchange format
   3. Draft of a data exchange format for IAS management
   4. The trajectory towards an adopted standard
   

   View Slide

4. 1. The IAS/wildlife management data landscape
   1. The reporting demands of the EU IAS regulation
   2. What do management data look like?
   3. The LIFE RIPARIAS perspective
   

   View Slide

5. van Loon et al. 2017
   Cartuyvels et al. in pub
   EEA IAS dashboard
   

   View Slide

6. 1.1 The reporting demands of the EU IAS regulation
   

   View Slide

7. 1.1 The reporting demands of the EU IAS regulation
   Objective
   Method
   Effectiveness
   Non-target effects
   Comment box
   

   View Slide

8. 1.1 The reporting demands of the EU IAS regulation
   Objective ias.eea.europa.eu/
   

   View Slide

9. 1.1 The reporting demands of the EU IAS regulation
   Method
   https://cdr.eionet.europa.eu/help/ias_regulation/material/IAS-
   guidelines
   

   View Slide

10. 1.1 The reporting demands of the EU IAS regulation
    https://ias.eea.europa.eu/
    Effectiveness
    

    View Slide

11. 1.1 The reporting demands of the EU IAS regulation
    Non-target effects (on other species)
    https://cdr.eionet.europa.eu/help/ias_regulation/material/IAS-guidelines
    

    View Slide

12. 1.2 What do management data look like?
    1. No recording of management activities
    2. On personal laptop in spreadsheet
    

    View Slide

13. 1.2 What do management data look like?
    3. On personal laptop in GIS project
    

    View Slide

14. 1.2 What do management data look like?
    4. Database behind a (web) application
    

    View Slide

15. 1.2. Issues related to management data
    EU IAS
    regulation
    Data exchange format
    

    View Slide

16. 1.2. Issues related to management data
    EU IAS
    regulation
    

    View Slide

17. 1.2. Issues related to management data
    1. Management reporting is performed with different objectives and at different levels
    a. Within managerial organisations
    b. For project funders (e.g. Life)
    c. Upscaling needed for international reporting
    2. Not all management actions are recorded
    3. Not centrally stored within organisation
    4. No flexibility in recording management of different taxa
    5. Management data is not consistently recorded and prone to interpretation
    6. Management data is not interoperable within and between organisations
    7. Management data is not open
    

    View Slide

18. 1.3 The LIFE RIPARIAS perspective
    

    View Slide

19. 1.3 The LIFE RIPARIAS perspective
    Goals
    1. Improve data flows from surveillance systems
    2. Develop clear guidelines and objective criteria for prioritising
    management actions
    ○ rapid eradication
    ○ containment of populations
    ○ maintenance of pest free areas
    3. Improve data flows from management actions to policy-makers by
    monitoring and assessing IAS management effectiveness in support
    of the EU IAS reporting regulation
    4. Promote the replication of the evidence-based workflow for IAS
    management decision making in Europe
    

    View Slide

20. 1.3 The LIFE RIPARIAS perspective
    Action A.2 Improve data flow for management reporting
    1. A.2.1 Business analysis of IAS management reporting with managers
    2. A.2.2 Develop a system to report on management actions & effectiveness
    Survey of current field management data systems:
    Which species are managed?
    How are management methods described?
    management impact, non-target effects and management effort
    Which technology/application is used to enter and store field management data?
    What is the management data flow within the organization?
    Are the field management data compliant with international standards?
    Who has access to the management data?
    

    View Slide

21. 1.3 The LIFE RIPARIAS perspective
    Solution
    1. Start developing an open and community driven data exchange format
    2. Generic enough to fit most of the management registration needs
    3. Targeted enough to be fit-for-purpose for EU Reporting
    Issues
    1. Many managers use already a reporting system (typically expensive
    and closed): data model not present, ad hoc
    2. Are managers willing to change report system? Choice at organization
    level
    

    View Slide

22. 2. Data exchange format
    1. Data exchange format: concept
    2. Example 1: Darwin Core Archive
    3. Example 2: camtrapdp
    

    View Slide

23. 2.1 Data exchange format: concept
    1. Data can be shared between different entities
    2. A good exchange format: low information loss while (un)packaging
    format A standard
    packaging
    Format B standard
    unpackaging
    A B
    

    View Slide

24. 2.2 Example 1: Darwin Core Archive (DwC-A)
    1. Standard for packaging and
    publishing biodiversity data
    2. A DwC-A contains a number of text
    files, including data tables
    formatted as csv
    3. Star schema with a single core
    table and optional extension tables
    

    View Slide

25. 2.2 Example 1: Darwin Core Archive (DwC-A)
    1. It uses Darwin Core (DwC) terms. Examples: scientificName, estabilishmentMeans, pathway
    https://dwc.tdwg.org/terms/
    

    View Slide

26. 2.2 Example 1: Darwin Core Archive (DwC-A)
    DwC-A is the download format of GBIF and OBIS
    

    View Slide

27. 2.3 Example 2: Camtrap DP
    1. “Camera Trap Data Package”
    2. Designed to capture all essential data and metadata of a
    single camera trap study
    3. Model to exchange camera trapping data
    4. Format to exchange camera trapping data
    https://bit.ly/3JvdPB4
    

    View Slide

28. 2.3 Example 2: Camtrap DP
    https://bit.ly/3JvdPB4
    gbif.org/occurrence/3045046810
    gbif.org/occurrence/3045043163
    Model
    1. Metadata about project
    2. Deployments: start/end date, location, camera info
    3. Media: file path/url, timestamp, sequence
    4. Observations: blank, or animal of certain species, count,
    sex, ...
    Project / Study
    img 1 grey heron
    img 2 grey heron
    img 3 blank
    seq 1 moorhen
    seq 1 coot
    

    View Slide

29. https://bit.ly/3JvdPB4
    Format
    1. Metadata as datapackage.json
    ○ Project metadata
    ○ Package structure
    2. Deployments as csv
    3. Media as csv
    4. Observations as csv
    2.3 Example 2: Camtrap DP
    datapackage
    .json
    media.csv observations
    .csv
    deployments
    .csv
    sequenceID
    mediaID
    deploymentID
    deploymentID
    

    View Slide

30. https://bit.ly/3JvdPB4
    Using Frictionless Standards
    1. Developed by Frictionless Data
    2. Set of open specifications (JSON schemas) that can
    be combined:
    3. Data Package for datasets
    4. Data Resource for data files
    5. Table Schema for table fields
    6. Simple, machine-usable & extensible
    2.3 Example 2: Camtrap DP
    

    View Slide

31. Table of content
    1. The IAS/wildlife management data landscape
    2. Data exchange format
    3. Draft of a data exchange format for IAS management
    4. The trajectory towards an adopted standard
    

    View Slide

32. 3. Draft of a data exchange format for IAS management
    1. Data model and format
    2. Details
    

    View Slide

33. 3.1 Data model and format
    Tabular data (tables)
    Model
    1. Metadata about project: project title, organizations, start,
    end, target taxa, …
    2. Actions: type, start/end datetime, organism target,
    organism quantity (removed)
    3. Evaluations: datetime, descriptive evaluation, organism
    target, organism quantity (present)
    4. Persons: name, email, organization, role,
    

    View Slide

34. 3.2 Model and format overview
    Format
    1. Metadata as datapackage.json
    ○ Project metadata
    ○ Package structure
    2. Locations as csv
    3. Actions as csv
    4. Evaluations as csv
    5. Persons as csv
    actions.csv evaluations.csv
    locations
    .csv
    locationID
    locationID
    persons
    .csv
    fieldManagerID
    fieldExectuorID
    evaluatorID
    taxa.csv
    taxonID taxonID
    Datapackage
    .json
    

    View Slide

35. 3.3 Details
    https://bit.ly/3qBjazw
    

    View Slide

36. 3.3 Details
    Table Mandatory field Controlled vocabulary field
    Locations locationName
    locationType
    locationWKT
    Actions mainType
    taxonID
    locationID
    startDate
    endDate
    organismTarget
    organismQuantityType
    organismQuantity
    organismQuantityUnit
    mainType
    subType
    organismTarget
    organismQuantityType
    organismQuantityUnit
    

    View Slide

37. 3.3 Details
    Table Mandatory Controlled vocabulary
    Evaluations evaluationID
    taxonID
    locationID
    evaluationDate
    evaluation
    evaluationTime
    evaluatorID
    organismTarget
    organismQuantityType
    organismQuantity
    organismQuantityUnit
    organismTarget
    organismQuantityType
    organismQuantityUnit
    Taxa taxonID
    scientificName
    taxonRank
    taxonRank
    Persons email
    organizationShortName
    organizationLongName
    role
    

    View Slide

38. Table of content
    1. The IAS/wildlife management data landscape
    2. Data exchange format
    3. Draft of a data exchange format for IAS management
    4. The trajectory towards an adopted standard
    

    View Slide

39. 4. The trajectory towards an adopted standard
    1. Community building
    2. The “use case” circle
    3. TDWG 2022
    

    View Slide

40. 4.1 Community building
    1. This kick-off workshop
    2. Nota about this workshop
    3. 2nd LIFE MICA - RIPARIAS workshop (13/07/2022)
    4. Take to TDWG 2022 session
    

    View Slide

41. 4.2 The “use case” circle
    1. Share your own use case
    2. Mapping exercise
    3. Improve data exchange format
    Share Map
    Improve
    

    View Slide

42. 4.3 TDWG 2022
    1. Slogan: “Stronger Together: Standards for linking biodiversity data”
    2. When: 17–21 October 2022
    3. Where: Sofia, Bulgaria
    4. Call for organized sessions: deadline 15 April 2022
    

    View Slide

43. Thank you
    Damiano Oldoni
    Jasmijn Hillaert
    Tim Adriaens
    0000-0003-3445-7562
    0000-0002-3761-8846
    0000-0001-7268-4200
    Oldoni, Hillaert & Adriaens (2022)
    The need for a data exchange format on IAS / wildlife management.
    Presentation.
    https://bit.ly/3NkmNn8
    

    View Slide