1. OBIS

2. Current situation Working on new IT platform Present technology 8 years old Data ingestion going fine Including data quality Position, time Taxonomy Web site well visited

3. Number of records (M)

4. Number of datasets

5. Average size dataset (K)

6. Web statistics

7. Data statistics

8. Analysis of content First preliminary analyses Has to take into account huge bias Geography Mostly coastal Mostly northern hemisphere Taxonomy Presence-only ‘Safety in numbers’

9. Number of records For known species most important to your project, what major discoveries have been made about their range or distribution? What is least known with regards to their distribution that you would like to know?

10. Number of species

11. Hurlbert’s index (es(50))

12. Large marine ecosystems

13. ‘Age’ of record – trends study

14. Latitudinal gradient ES(50)

15. Marine fish to be discovered Mora et al (2007). The completeness of taxonomic inventories for describing the global diversity and distribution of marine fishes. Proc. R. Soc. B, published on line Percentage completeness 1 100

16. How good is the data? Data are from many sources Inconsistent become apparent Differences in names used Mistakes in transformations Decimalising lat/lon Needs quality control Data collection driven by priorities Sampling bias; resolution

17. Quality control Check formal record structure Check date/time Check position In the ocean? In dataset bounding box? Check taxonomy Problem: no reference list

18. New species are discovered Data from http://marinespecies.org

19. Problems with taxonomic names Misspellings Misspellings Mixed with other information Mixed with other information Gadus sp.; Gadus sp. A; Gadus sp. a… Gadus sp.; Gadus sp. A; Gadus sp. a… Gadus morhua?; Gadus cfr morhua; Gadus aff. morhua… Gadus morhua?; Gadus cfr morhua; Gadus aff. morhua… Gadus morhua juv.; Gadus morhua juvenile; Gadus morhua juveniles… Gadus morhua juv.; Gadus morhua juvenile; Gadus morhua juveniles… Mixed with ecological/sampling information Mixed with ecological/sampling information Also variation in classification and author string Also variation in classification and author string

20. Examples of variation Callorhinchus callorynchus Callorhinchus callorynchus Cirrhinus or Cirrhina Cirrhinus or Cirrhina Cirrhinus cirrhosa or C. cirrhosus Cirrhinus cirrhosa or C. cirrhosus Cirrhina cirrhosa or C. cirrhosus Cirrhina cirrhosa or C. cirrhosus Microsoft helping a bit: Microsoft helping a bit: Calinectes ornatus Ordway, 1863 Calinectes ornatus Ordway, 1864 … Calinectes ornatus Ordway, 1891 Calinectes ornatus Ordway, 1863 Calinectes ornatus Ordway, 1864 … Calinectes ornatus Ordway, 1891

21. Number of ‘species’ in OBIS 147K unique ‘scientific names’ 147K unique ‘scientific names’ 132K ‘clean names’ 132K ‘clean names’ Approx 10% reduced (from 147K) Approx 10% reduced (from 147K) 80K match with WoRMS 80K match with WoRMS 11K known synonyms or misspellings 11K known synonyms or misspellings Non-matches assumed valid Non-matches assumed valid 121K ‘valid names’ 121K ‘valid names’ Approx 20% reduced Approx 20% reduced

22. Reduction of es(50) per 5d square

23. Same for fish

24. General patterns indistinguishable All Fish DirtyClean

25. Completeness

26. How to get OBIS data? Web site Web site DiGIR provider DiGIR provider OGC-compliant web services OGC-compliant web services Exist on experimental basis Exist on experimental basis Google base Google base Ask us! Ask us! Custom data extraction Custom data extraction

30. Data from field projects Not always easy to ‘trace’ Not always easy to ‘trace’ Not well documented what is CoML data, aand which field project it belongs to Not well documented what is CoML data, aand which field project it belongs to Needs mechanism to better document Needs mechanism to better document Part of the metadata? Part of the metadata? Exercise was done at iOBIS Exercise was done at iOBIS Spreadsheet will be made available Spreadsheet will be made available Please check Please check In general, good agreement with our understanding and information from annual reports In general, good agreement with our understanding and information from annual reports

31. Field projects Acronym # datasets as per group # records as per group # datasets in OBIS # records in OBIS CeDaAMar10901819017 CAML64625000581091837 ArcOD18701971870061 CoMargE23000+1667067 POST1?1114161 CReefs82039298 ICoMM2255111 Mar-ECO1?12744 NaGISA113138123552 GoMA4203130433740 CenSeam7714233119488 TOPP0000 ChEss125931 CMarZ11141 HMAP10319,1111260182 FMAP21443462

32. How to get data in OBIS? Dialogue ongoing with all major providers Dialogue ongoing with all major providers All field projects All field projects Regional OBIS Nodes (RONs) Regional OBIS Nodes (RONs) FishBase, OBIS SEAMAP… FishBase, OBIS SEAMAP… iOBIS needs time to ingest data iOBIS needs time to ingest data Quality control… Quality control… Data cycle Data cycle Lag in data availability ~3 months Lag in data availability ~3 months Depending on quality of the data Depending on quality of the data