INSTITUTE OF OCEANOGRAPHY AND FISHERIES SPLIT,
CROATIA, since 1930
INSTITUTE OF OCEANOGRAPHY AND FISHERIES
Setaliste Ivana Mestrovica 63, 21000 Split;
Damjana Jude 12, 20000 Dubrovnik
MEDAS SYSTEM FOR ARCHIVING,
VISUALISATION AND VALIDATION OF
OCEANOGRAPHIC DATA
Dadic, V. and D. Ivankovic
Ocean Biodiversity Informatics
International Conference on Marine Biodiversity Data Management
Hamburg, Germany: 29 November to 1 December 2004
1
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INSTITUTE OF OCEANOGRAPHY AND FISHERIES SPLIT,
CROATIA, since 1930
Database users
Croatian National
Monitoring Programme
Web browser
Application
server
MEDAS
Database with
web interface
Use
Systematic Research of the Adriatic
Sea as a Base for Sustainable
Development of the Republic of
Croatia
In
Frame of
Croatian Institutions
Marine Environmental Database of the Adriatic Sea
(MEDAS)
Ocean Biodiversity Informatics
International Conference on Marine Biodiversity Data Management
Hamburg, Germany: 29 November to 1 December 2004
3
INSTITUTE OF OCEANOGRAPHY AND FISHERIES SPLIT,
CROATIA, since 1930
Database structure
MARINE PHYSICS
• SEA LEVEL
•SEA CURRENTS
•CTD
•METEOROLOGY
META DATA
•ROSCOP
•INSTRUMENS
•RESPONSIBLE
PERSONS
•CLASSICAL OCEANOGRAPHY
•(T,S,Ph,o2, sea surface meteorology)
MEDAS
FISHERIES
•COASTAL FISHERIES
•PELAGIC FISHERIES
•DEMERSAL FISHERIES
•EGGS,LARVES, JUVENILS
•CATCH STATISTICS
•AQUACULTURE
INTERFACE
•GIS LAYERS
•EXCHANGE
FORMATS
MARINE
CHEMISTRY
•NUTRIENTS
•HEAVY METALS
•P A T
•P A H
DATABASE
BASIC LAYERS
•COASTAL LINE
•BATHYMETRY
•WRECKS …
MARINE BIOLOGY
•ZOOPLANCTON
•ZOOBENTHOS
•PHYTOPLANCTON
•MICROBIOLOGY
Ocean Biodiversity Informatics
International Conference on Marine Biodiversity Data Management
Hamburg, Germany: 29 November to 1 December 2004
4
INSTITUTE OF OCEANOGRAPHY AND FISHERIES SPLIT,
CROATIA, since 1930
Database capability
Online
stations
(real time)
Mapping
tool
Cruise summary
reports
MEDAS
(near real time – GPRS)
database
Data in
digital form
Manually
inserted data
Data for
running models
Data visualisation
Search criteria,
grouping data,
statistics
Data export:
• MEDAR / MEDATLAS
• Excel
• Ocean Data View
• Surfer
• Arc GIS 8.1
Ocean Biodiversity Informatics
International Conference on Marine Biodiversity Data Management
Hamburg, Germany: 29 November to 1 December 2004
5
INSTITUTE OF OCEANOGRAPHY AND FISHERIES SPLIT,
CROATIA, since 1930
MEDAS database - history
Distribution of
measuring stations
archived in MEDAS
database
 ORACLE 5 + Forms 3 – mapping tool: non
 ORACLE 7 + Forms 5 - mapping tool : C++
 Oracle 9i + Oracle Application server
- Mapping tool : Java applet
Ocean Biodiversity Informatics
International Conference on Marine Biodiversity Data Management
Hamburg, Germany: 29 November to 1 December 2004
6
INSTITUTE OF OCEANOGRAPHY AND FISHERIES SPLIT,
CROATIA, since 1930
Why this technologies?
ORACLE 9i:
 Stability, security
 Lack of stuff (few men's show)
ORACLE Application Server:
 No need for client side software (only browser)
 Accessibility (different institutions, ship – GPRS)
 Easy web publishing (default)
Java applet – mapping tool and data visualisation:
 Portability (cross platform)
 Use of Client side resources (no need for powerful server )
Disadvantages:
 Software license cost
 Instability and bugs of some Java versions
 Sometimes need for manually JVM install
Ocean Biodiversity Informatics
International Conference on Marine Biodiversity Data Management
Hamburg, Germany: 29 November to 1 December 2004
7
INSTITUTE OF OCEANOGRAPHY AND FISHERIES SPLIT,
CROATIA, since 1930
MEDAS database web interface
Ocean Biodiversity Informatics
International Conference on Marine Biodiversity Data Management
Hamburg, Germany: 29 November to 1 December 2004
8
INSTITUTE OF OCEANOGRAPHY AND FISHERIES SPLIT,
CROATIA, since 1930
Importance of good search criteria
Ocean Biodiversity Informatics
International Conference on Marine Biodiversity Data Management
Hamburg, Germany: 29 November to 1 December 2004
9
INSTITUTE OF OCEANOGRAPHY AND FISHERIES SPLIT,
CROATIA, since 1930
Input forms
Data input trough web
forms (Croatian language
only)
Authorisation
requested
Basic input validation
Secure protocol (https)
Ocean Biodiversity Informatics
International Conference on Marine Biodiversity Data Management
Hamburg, Germany: 29 November to 1 December 2004
10
INSTITUTE OF OCEANOGRAPHY AND FISHERIES SPLIT,
CROATIA, since 1930
Cruise report example
 Cruise information
with mapping tool
 Frames organised
 Form – applet
interaction
Ocean Biodiversity Informatics
International Conference on Marine Biodiversity Data Management
Hamburg, Germany: 29 November to 1 December 2004
11
INSTITUTE OF OCEANOGRAPHY AND FISHERIES SPLIT,
CROATIA, since 1930
Importance of Where, What and Who
Where & When
Who
What
Ocean
Biodiversity Informatics
Expended GF3 based
organisation
International Conference on Marine Biodiversity Data Management
Hamburg, Germany: 29 November to 1 December 2004
12
INSTITUTE OF OCEANOGRAPHY AND FISHERIES SPLIT,
CROATIA, since 1930
Real-time circulation model
Ocean Biodiversity Informatics
International Conference on Marine Biodiversity Data Management
Hamburg, Germany: 29 November to 1 December 2004
Real – time data (automatic stations)
INSTITUTE OF OCEANOGRAPHY AND FISHERIES SPLIT,
CROATIA, since 1930
Station PUNTA JURANA
in front of the main
building of the Institute
12 meteorological oceanographic
parameters (nine air and
three sea parameters)
Station VELI RAT
measurements every 10
minutes 24 hours a day
Meteorological sensors on the top of lighthouse
11 meteorological - oceanographic parameters (nine
air and two sea parameters)
Measurements every 10 minutes 24 hours a day,
data refresh interval – 1 hour
Ocean Biodiversity Informatics
International Conference on Marine Biodiversity Data Management
Hamburg, Germany: 29 November to 1 December 2004
13
14
INSTITUTE OF OCEANOGRAPHY AND FISHERIES SPLIT,
CROATIA, since 1930
About data
Data sources in MEDAS database
period almost a century (1907– 2004)
countries: Croatia, Austria, ex Yugoslavia, Italy, USA, Russia,
France, Germany and Slovenia
Oceanographic data (characteristics):
measured by research and other vessels
randomly distributed stations (not regular in time and space)
measured at various sea levels
different methods and instruments (different quality of data)
Bathimetry and
coastline of the Adriatic
Sea
Ocean Biodiversity Informatics
International Conference on Marine Biodiversity Data Management
Hamburg, Germany: 29 November to 1 December 2004
15
Quality Control and Data Processing
INSTITUTE OF OCEANOGRAPHY AND FISHERIES SPLIT,
CROATIA, since 1930
Data quality control in MEDAS database includes:
Duplicate data elimination
Range checking of data
Statistical checking of data
Stability checking of data.
Data profiles (sets)
 51769 temperature
 32562 salinity profiles
 5840 oxygen
 2925 pH
 13835 nutrients
 3345 chlorophill_a
Procedure: two
steps
QC1 first step
QC2 second step
 1753 plankton (zoo and phyto)
 1218 fish trawler data
 785 echosounding samples
Ocean Biodiversity Informatics
International Conference on Marine Biodiversity Data Management
Hamburg, Germany: 29 November to 1 December 2004
16
INSTITUTE OF OCEANOGRAPHY AND FISHERIES SPLIT,
CROATIA, since 1930
Cases when data excluded from processing
CAST
CRUISE
0 - No QC
1 - Correct value
2 - Suspect value
3 - Out of climatological range
4 - Interpolated value
5 - wrong value
9 - missing value
UNKNOWN
DATE
DATABASE
WRONG
POSITION
OF STATION
EXCLUDE WHOLE
DATA CAST
NO DEPTH
EXCLUDE A DATA
FROM CAST
Ocean Biodiversity Informatics
International Conference on Marine Biodiversity Data Management
Hamburg, Germany: 29 November to 1 December 2004
17
Classical Oceanographic Data Inventory
INSTITUTE OF OCEANOGRAPHY AND FISHERIES SPLIT,
CROATIA, since 1930
The most complete data sets: 1907-2004
Ocean Biodiversity Informatics
International Conference on Marine Biodiversity Data Management
Hamburg, Germany: 29 November to 1 December 2004
18
INSTITUTE OF OCEANOGRAPHY AND FISHERIES SPLIT,
CROATIA, since 1930
BOT
Number of
measuring
data at
different levels
CTD
MBT
XBT
Ocean Biodiversity Informatics
International Conference on Marine Biodiversity Data Management
Hamburg, Germany: 29 November to 1 December 2004
451 stations with
wrong position
Split
327 resolved
124 unresolved
Brač
Makarska
Hvar
Ploče
INSTITUTE OF OCEANOGRAPHY AND FISHERIES SPLIT,
CROATIA, since 1930
An example of spatial distribution of received oceanographic
stations stations in wide area City of Split
Korčula
Ocean Biodiversity Informatics
International Conference on Marine Biodiversity Data Management
Hamburg, Germany: 29 November to 1 December 2004
19
INSTITUTE OF OCEANOGRAPHY AND FISHERIES SPLIT,
CROATIA, since 1930
Example: Result of converting from pressure to
depth and vice-versa
Ocean Biodiversity Informatics
International Conference on Marine Biodiversity Data Management
Hamburg, Germany: 29 November to 1 December 2004
20
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18000
14000
0
12000
10
10000
50
8000
100
6000
500
4000
1000
INSTITUTE
Broj podataka OF OCEANOGRAPHY AND FISHERIES SPLIT,
CROATIA, since 1930
Broj podataka
16000
Number of data of
temperature at 5
different levels by
season
2000
Broj podataka
0
ZI
PR
LJ
JE
Godišnj e doba
Season
a)
0
17500
15000
12500
10000
7500
5000
2500
0
10
50
100
500
a) Original data
b) Data in interval of 3 sigma of
average
c) Data inside 1 sigma of
average
1000
ZI
PR
LJ
Godišnje doba
Season
15000
12500
10000
7500
5000
2500
0
JE
b)
0
10
50
100
500
1000
ZI
PR
LJ
Godišnje doba
Season
Ocean Biodiversity Informatics
JE
International
Conference on Marine Biodiversity Data Management
Hamburg, Germany: 29 November to 1 December 2004
c)
INSTITUTE OF OCEANOGRAPHY AND FISHERIES SPLIT,
CROATIA, since 1930
Seasonal presentation of total amount of
temperature data
Fall
Winter
Summer
Spring
Ocean Biodiversity Informatics
International Conference on Marine Biodiversity Data Management
Hamburg, Germany: 29 November to 1 December 2004
22
INSTITUTE OF OCEANOGRAPHY AND FISHERIES SPLIT,
CROATIA, since 1930
Sea surface temperature sorted by time from 1900
up to 2000
Ocean Biodiversity Informatics
International Conference on Marine Biodiversity Data Management
Hamburg, Germany: 29 November to 1 December 2004
23
INSTITUTE OF OCEANOGRAPHY AND FISHERIES SPLIT,
CROATIA, since 1930
Definition of areas in the Adriatic Sea for calculation
climtologcal ranges of classical oceanographic parameters
(I)
(III)
(II)
(IV)
Ocean Biodiversity Informatics
International Conference on Marine Biodiversity Data Management
Hamburg, Germany: 29 November to 1 December 2004
28 one degree squares and 4 sub-regions in the Adriatic Sea
24
INSTITUTE OF OCEANOGRAPHY AND FISHERIES SPLIT,
CROATIA, since 1930
Data processing is done in the next steps in aim to
get output data in suitable form for analysis
Calculation of basic statistics
(number of samples, mean value,
standard deviation, min and max
values)
Procedure:
Interpolation of measuring data on
41 standard oceanographic levels
using Newton method of finite
differences modified by reference
RR curves
Semiautomatic
Visualisation
Calculation of basic statistics
on standard levels
Interpolation by kriging method
and graphical presentation by
mapping tool
No
OK
YES
Finish
Ocean Biodiversity Informatics
International Conference on Marine Biodiversity Data Management
Hamburg, Germany: 29 November to 1 December 2004
25
26
INSTITUTE OF OCEANOGRAPHY AND FISHERIES SPLIT,
CROATIA, since 1930
Standard depth
Adriatic Sea: 41 standard levels
Max distance between
two outer levels
Max distance between
two inner levels
Ocean Biodiversity Informatics
International Conference on Marine Biodiversity Data Management
Hamburg, Germany: 29 November to 1 December 2004
Number of standard level
27
INSTITUTE OF OCEANOGRAPHY AND FISHERIES SPLIT,
CROATIA, since 1930
Newton interpolation of finite differences (nth order)
Newton interpolation of finite differences (2th order)
through 3 points
Newton interpolation of finite differences
(2th order) through 3 points modified by R-R
reference curve
Comparison of the three different
methods of interpolation data on
standard levels
Ocean Biodiversity Informatics
International Conference on Marine Biodiversity Data Management
Hamburg, Germany: 29 November to 1 December 2004
Temperature (oC)
28
INSTITUTE OF OCEANOGRAPHY AND FISHERIES SPLIT,
CROATIA, since 1930
Testing of parameters
Testing of parameters in
reference curves:
m=1-22 n=1,10
Optimal values:
m=1.6, n=0.6
Ocean Biodiversity Informatics
International Conference on Marine Biodiversity Data Management
Hamburg, Germany: 29 November to 1 December 2004
29
INSTITUTE OF OCEANOGRAPHY AND FISHERIES SPLIT,
CROATIA, since 1930
Method of analysis of spatially distributed data
Kriging method has been used as optimal method of interpolation
of randomly distributed data in space because it provides the best
linear unbiased estimate (BLUE) of the variable at a given point.
It is an exact interpolator in the sense that interpolated values, or
best local average, will coincidence with the values at the data
points.
The kriging method is valid if there is continuity among dana,
which is testing by variogram.
Ocean Biodiversity Informatics
International Conference on Marine Biodiversity Data Management
Hamburg, Germany: 29 November to 1 December 2004
INSTITUTE OF OCEANOGRAPHY AND FISHERIES SPLIT,
CROATIA, since 1930
Investigation of spatial continuity of temperature by
variance
Continuity
Discontinuity
Semivariance
Winter
Spring
Summer
Autumn
Number of pairs
Winter
Spring
Summer
Autumn
Ocean Biodiversity Informatics
International Conference on Marine Biodiversity Data Management
Hamburg, Germany: 29 November to 1 December 2004
Distance between pair of stations (*60 Nm)
30
31
Quality controlled data
INSTITUTE OF OCEANOGRAPHY AND FISHERIES SPLIT,
CROATIA, since 1930
All stations
(1900-2004)
Spatial distribution of oxygen stations
Oxigen stations
37439 drops
7845 drops
Spatial distribution of oceanographic
measuring stations
Ocean Biodiversity Informatics
International Conference on Marine Biodiversity Data Management
Hamburg, Germany: 29 November to 1 December 2004
INSTITUTE OF OCEANOGRAPHY AND FISHERIES SPLIT,
CROATIA, since 1930
Filed of spatially distribute sea surface temperature
derived from original data and data partly passed
QC procedure for the period 1907-2003
Ocean Biodiversity Informatics
International Conference on Marine Biodiversity Data Management
Hamburg, Germany: 29 November to 1 December 2004
32
33
INSTITUTE OF OCEANOGRAPHY AND FISHERIES SPLIT,
CROATIA, since 1930
Averaged values and standard deviation of salinity in
1 deg. squares (0-5 meters) for the period 1907-2004
Square includes:
- coastal area
- open sea
(need to use smaller
size square)
Possible choosing
different size of
squares
Ocean Biodiversity Informatics
International Conference on Marine Biodiversity Data Management
Hamburg, Germany: 29 November to 1 December 2004
INSTITUTE OF OCEANOGRAPHY AND FISHERIES SPLIT,
CROATIA, since 1930
Result of data analysis of T,S, O2, pH and nutrient
parameters
34
It was concluded:
 41 standard levels in the Adriatic Sea was defined as enough for
qualitative climatological analysis of T,S,O2, pH and nutrients in the
Adriatic Sea
 climatological range of oceanographic parameters in the Adriatic
sea for above mentioned parameters was defined
 spatial continuity of oceanographic parameter are from 5 to 7.5
km depends of season and depth of standard oceanographic level
 detail structure of spatial distribution for climatological
properties of oceanographic parameters has been calculated
 different layers of the water mass in the Adriatic Sea has been
analysed.
Ocean Biodiversity Informatics
International Conference on Marine Biodiversity Data Management
Hamburg, Germany: 29 November to 1 December 2004
INSTITUTE OF OCEANOGRAPHY AND FISHERIES SPLIT,
CROATIA, since 1930
Water mass distribution in the period of low liw inflow (derived
from oceanographic data)
Ocean Biodiversity Informatics
International Conference on Marine Biodiversity Data Management
Hamburg, Germany: 29 November to 1 December 2004
35
INSTITUTE OF OCEANOGRAPHY AND FISHERIES SPLIT,
CROATIA, since 1930
Water mass distribution in the period of liw inflow
intensification (derived from oceanographic data)
Ocean Biodiversity Informatics
International Conference on Marine Biodiversity Data Management
Hamburg, Germany: 29 November to 1 December 2004
36
INSTITUTE OF OCEANOGRAPHY AND FISHERIES SPLIT,
CROATIA, since 1930
Heavy metals in
dry weight of
oyster tissue
analysis
Cadm ium (Cd) in oyster in the Istarska
County
1250
w Cd (µg kg-1 s.m.)
1000
OT23
750
OT24
OT25
OT27
500
250
0
2000
2001
2002
Year
2003
Source: IOR-Split
ZInk (Zn) ikn oyster in the Primorsko-goranska
County
Cuper (Cu) u oyster in Dubrovačko-Neretvanska County
250000
50000
40000
150000
OT21
100000
OT22
50000
w Cu (µg kg-1 s.m.)
w Zn (µg kg-1 s.m.)
200000
OT2
30000
OT3
OT4
OT6
20000
0
2000
2001
2002
Godina
2003
10000
Ocean Biodiversity Informatics
International Conference on Marine Biodiversity Data Management
Hamburg, Germany: 29 November to 1 December 2004
Source: IOR-Split
0
2000
2001
2002
Year
2003
Source:
IOR-Split
37
INSTITUTE OF OCEANOGRAPHY AND FISHERIES SPLIT,
CROATIA, since 1930
38
MEDAS
Arc-View
USA NODC Tax code
Mean concentration
of chlorofill_a
Ocean Biodiversity Informatics
analysis
International Conference on Marine Biodiversity Data Management
Hamburg, Germany: 29 November to 1 December 2004
INSTITUTE OF OCEANOGRAPHY AND FISHERIES SPLIT,
CROATIA, since 1930
Example: spatial analysis of distribution
commercialy demersal fish population in the
Adriatic Sea
Calculation of spatially distribution of
relative abundance (kg/km2) of:
HVAR
 total stock of demersal fish
population
 stock of main commercial spicies
from two extensive trawl-surveys
carried out in two distinct periods
shifted 50 years in time:
•
•
Expedition Hvar (1948-1949)
EU project MEDITS (1996-1997)
MEDAS
MEDITS
SURFER
FAO tax code
39
Ocean Biodiversity Informatics
International Conference on Marine Biodiversity Data Management
Hamburg, Germany: 29 November to 1 December 2004
INSTITUTE OF OCEANOGRAPHY AND FISHERIES SPLIT,
CROATIA, since 1930
Spatial distribution of total fish stock (kg/km2)
during HVAR and MEDITS expedition
HVAR
MEDIT
S
Ocean Biodiversity Informatics
International Conference on Marine Biodiversity Data Management
Hamburg, Germany: 29 November to 1 December 2004
40
41
INSTITUTE OF OCEANOGRAPHY AND FISHERIES SPLIT,
CROATIA, since 1930
Spatial distribution of main commercial fishes
(kg/km2) during HVAR and MEDITS expedition
 Composition changes of
demersal stocks
assemblage within two
surveyed periods should be
foreseen as a consequence,
either of fishing pressure or
environmental changes in
the sea.
HVAR
 Decrease of quantity of total
as well as the most important
commercial fishes of the
demersal fish stock
 The changes in fish
abundance are more
significant in shallow coastal
area then in deeper sea areas
MEDITS
Ocean Biodiversity Informatics
International Conference on Marine Biodiversity Data Management
Hamburg, Germany: 29 November to 1 December 2004
INSTITUTE OF OCEANOGRAPHY AND FISHERIES SPLIT,
CROATIA, since 1930
Example: planning of assignment of marine areas
in the Split-dalmatia County
Ocean Biodiversity Informatics
International Conference on Marine Biodiversity Data Management
Hamburg, Germany: 29 November to 1 December 2004
42
43
INSTITUTE OF OCEANOGRAPHY AND FISHERIES SPLIT,
CROATIA, since 1930
Future Improvements:
Transcode all database thematic parts
to web environment
Input forms (ergonomic)
Web visualisation tools
Data quality procedures and tools for
biological parameters
Extend taxonomic codes
Add multimedia support
Add GIS support
Ocean Biodiversity Informatics
International Conference on Marine Biodiversity Data Management
Hamburg, Germany: 29 November to 1 December 2004