Sissy Iona HNODC, Greece

OBSERVATIONS

& PRÉVISIONS CÔTIÈRES

www.seadatanet.org

3rd Training Workshop, 16-19 June, Oostende-IOC Offices

General description of data management procedures – Description of the different steps

"From data collection to the SeaDataNet mgmt system"

Sissy Iona

HNODC, Greece

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23rd SeaDataNet training workshop, 16-19 June, 2008, Oostende-IOC offices

Topics

PART A : Presentation of general data management rules

I. SeaDataNet Data Policy and Data Licence

II. Quality Controls

III. Rules for metadata sumbission to prevent duplication

PART B : Identification of main stages and available tools

IV. Reformatting from observation format to common data format

V. Quality Controls

VI. Metadata Concepts and Management (online, offline)

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Topics







V. Quality Controls


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I. SDN Data Policy History

Drafted by Project Office, 02/2007

Reviewed by the Steering Committee

Validated by the Coordination Group

sdn_po07_Data_policy.doc, 04/2007

http://www.seadatanet.org/media/seadatanet/files/publications/seadatanet_data_policy

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I. SeaDataNet Data Policy

It is derived from the INSPIRE directive for spatial information taking into account the national rules and the SeaDataNet users needs.

Objectives

• to serve the scientific community, public organizations, environmental agencies

• to facilitate the data flow through the Transnational Activities by stating clearly the conditions for data submission, access and use

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I. Links and FrameworkSeaDataNet Data Policy is fully compatible with the EU Directives, International Policies, Laws and Data Principles:

Directive 2003/4/EC of the European Parliament and of the Council of 28 January 2003 on public access to environmental information and repealing Council Directive 90/313/EEC (http://ec.europa.eu/environment/aarhus/index.htm).

INSPIRE Directive for spatial information in the Community (http://inspire.jrc.it/home.html)IOC Data Policy (http://ioc3.unesco.org/iode/contents.php?id=200)ICES Data Policy 2006 (https://www.ices.dk/Datacentre/Data_Policy_2006.pdf)WMO Resolution 40 (Cg-XII; see http://www.nws.noaa.gov/im/wmor40.htm)Implementation plan for the Global Observing System for Climate in support of the

UNFCCC, 2004; GCOS – 92, WMO/TD No.1219.Global Earth Observation System of Systems GEOSS 10-Year Implementation Plan

Reference Document (Final Draft) 2005. GEO 204. February 2005.CLIVAR Initial Implementation Plan, 1998; WCRP No. 103, WMO/TS No. 869, ICPO No.

14. June 1998.

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I. Policy for Data Access and UseMetadata

free and open access, no registration requiredeach data centre is obliged to provide the meta-data in standardized format to populate the

catalogue services

Data and productsvisualisation freely availablethe general case is free and open access (e.g. academic purposes)however (due to national policies) mandatory user registration is required (using Single

Sign One (SSO) Service)a “SeaDataNet role” (partner, academic, commercial etc.) is attributed to individual user

using the Authentication, Authorization and Administration (AAA) ServiceEach NODC attributes the roles to the users of its of countryOut of the partnership, the roles are assigned by SeaDataNet user-desk

When register, the user must accept the SDN licence agreementeach data centre node delivers data according to the user’s role and its local regulationeach data centre should provide freely the data sets necessary to develop the common

products

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I. SeaDataNet Users Management

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I. User Agreement on SeaDataNet Licence

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V. Quality Controls


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II. SeaDataNet Services

SeaDataNet Quality Control is one of the “off-line” services that provides methodologies, standards and tools to ensure the reliability, compatibility, coherence of the data:

a common Quality Control Protocola tool for visualization and automatic checks (ODV)

On-line services

off-line services

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II. QC procedures

Overview (IOC, ICES, EU recommendations, MEDAR Protocol)

• automatic and visual controls on the data and their metadata.

• Data measured from the same instrument and coming from the same “cruise” are organized at the same file, reformatted to the same exchange format and then are subject to a series of quality tests:

1. check of the format

2. check of the location and time

3. check of measurements

• The results of the automatic control are attached as QC flags to each data value.

• Validation or correction is made manually to the QC flags and NOT to the data.

• The results of the QC reported to the data originator to give feedback and ask questions.

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MEDATLAS Quality Flags values

(based to the GTSPP Flag Scale definition)

0: No QC0: No QC

1: Correct value1: Correct value

2: Out of statistics but not obviously wrong2: Out of statistics but not obviously wrong

3: Doubtful value3: Doubtful value

4: Bad value 4: Bad value

5: Modified value (only for the location, date, bottom depth)5: Modified value (only for the location, date, bottom depth)

9: missing value9: missing value

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SEADATANET Quality Flags values (L021)

(Based on IGOSS/UOT/GTSPP & Argo QC flags)

Quality flags

0 No quality control

1 The value appears to be correct

2 The value appears to be probably good

3 The value appears probably bad

4 The value appears erroneous

Information flags

5 The value has been changed

6 Below detection limit

7 In excess of quoted value

8 Interpolated value

9 Missing value

A Incomplete information

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II. Main QC procedures description

Format Check

• Detects anomalies like wrong platform codes or names, parameters name or units, missing mandatory information like reference to a cruise or observation system, source laboratory, sensor type

• No further control should be made before the correction and validation of the archive format

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II. Main QC procedures descriptionCheck of date and location

For vertical profiles • duplicate entries

• date: reasonable date, station date within the begin and end date of the cruise.

• ship velocity between two consecutive stations.

(e.g., speed >15 knots means wrong station date or wrong station location).

• location/shoreline: on land position

• bottom sounding: out of the regional scale, compared with the reference surroundings

For time series of fixed mooring • sensor depth checks: less than the bottom depth

• series duration checks: consistence with the start and end date of the dataset

• duplicate moorings checks

• land position checks

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Conventional techniques

• Algorithms- comparison of the location, time of the measurements (5 miles,

15 mins in GTSPP)

- comparison of the measurements

- comparison of extra metadata (platform codes- floats id, … )

• Visualization of ships tracks, transects, …

Advanced techniques

• Unique data identifier -CRC Tag (GTSPP report 2002)

II. Main QC procedures descriptionDuplicates checks

Keep the most complete data set

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II. Main QC procedures descriptionMeasurements main checks

• presence of at least two parameters: vertical/time reference + measurement

• pressure/time must be monotonous increasing

• the profile/time series must not be constant: sensor jammed

• broad range checks: check for extreme regional values compared with the min. and max. values for the region. The broad range check is performed before the narrow range check.

• data points below the bottom depth

• spikes detection: usually requires visual inspection. For time series a filter is applied first to remove the effect of tides and internal waves.

• narrow range check: comparison with pre-existing climatological statistics. Time series are compared with internal statistics.

• density inversion test : (potential density anomaly, FOFONOF and MILLARD, 1983, MILLERO and POISSON, 1981)

• Redfield ratio for nutrients: ratio of the oxygen, nitrate and alkalinity (carbonates) concentration

over the phosphate (172, 16 and 122 in Atlantic and Indian ocean, Takahashi & al )

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II. Broad Range Check•Regional parameterization in MEDAR/MEDATLAS II•(plus depth parameterization)

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II. Main QC procedures description Narrow range check

qc flag=2, probably good data, after auto controlqc flag=2, probably good data, after auto control

qc=1, manually

The automatic comparison with reference climatologies is made by linearly interpolating the references at the level of the observation.

Outliers are detected if the data points differ from the references more than:

• 5 x standard deviation over the shelf (depth <200m)

• 4 x standard deviation at the slop and straits region

(200 m< depth < 400m)

• 3 x standard deviation at the deep sea (depth >400m)

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Spikes check

• The test is sensitive to the vertical/time resolution.

• It requires at least 3 consecutive good/acceptable values.

• It requires 2 consecutive at the surface and the bottom.

• The IOC Algorithm to detect the spikes taking into account the difference in values (for regularly spaced data like CTD):

|V2-(V3+V1)/2 | - |V1-V3|/2 ) > THRESHOLD VALUE

• For irregularly spaced values (like bottle data) a better algorithm to detect the spikes, taking into account the difference in gradients instead the difference in values, is:

| |(V2-V1)/(P2-P1)-(V3-V1)/(P3-P1)| - |(V3-V1)/(P3-P1)| |> THRESHOLD VALUE

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II. QC procedures descriptiondensity inversion test, the importance of visual check

example of density inversion due to temperature increase with depth

Suggested threshold value=0.03 for high resolution data, 0.05 for near surface and low resolution data

Wrong Temp value detected automatically

z1z1

z2

z2

Wrong Temp value detected automatically,but it is correct value,the previous is manually corrected

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Large temperature inversion and gradient tests

(World Ocean Data Centre, NODC Ocean Climate Laboratory)

Relying solely to temperature data to quantify the maximum allowable temperature increase with depth (inversion) and decrease (excessive gradient) with depth (0.3 C per m, 0.7 C per m)

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II. Main QC procedures descriptionARGO Real-Time QC on vertical profiles

Based on the Global Temperature and Salinity Profile Project –GTSPP of IOC/IODE, the automatic

QC tests are:

Platform identification: checks whether the floats ID corresponds to the correct WMO number.

Impossible date test: checks whether the observation date and time from the float is sensible.

Impossible location test : checks whether the observation latitude and longitude from the float is sensible.

Position on land test : observation latitude and longitude from the float be located in an ocean.

Impossible speed test : checks the position and time of the floats.

Global range test : applies a gross filter on observed values for temperature and salinity.

Regional range test: checks for extreme regional values

Pressure increasing test : checks for monotonically increasing pressure

Spike test : checks for large differences between adjacent values.

Gradient test : is failed when the difference between vertically adjacent measurements is too steep.

Digit rollover test : checks whether the temperature and salinity values exceed the floats storage capacity.

Stuck value test : checks for all measurements of temperature or salinity in a profile being identical.

Density inversion : Densities are compared at consecutive levels in a profile, in both directions, i.e. from top to bottom profile

and from bottom to top.

Grey list (7 items): stop the real-time dissemination of measurements from a sensor that is not working correctly.

Gross salinity or temperature sensor drift : to detect a sudden and important sensor drift.

Frozen profile test : detect a float that reproduces the same profile (with very small deviations) over and over again.

Deepest pressure test : the profile has pressures not higher than DEEPEST_PRESSURE plus 10%.

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II. Main QC procedures descriptionCORIOLIS Real-Time QC on time series

Automatic quality controls

test 1: Platform Identification test 2: Impossible Date Test test 3: Impossible Location Test test 4: Position on Land Test test 5: Impossible Speed Test test 6: Global Range Test test 7: Regional Global Parameter Test for Red Sea and Mediterranean Sea test 8: Spike Test

test 10: comparison with climatology

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CORIOLIS Delayed Mode QC on profiles and time series

• Automated and Visual QC (already described)

• Objective analysis and residual analysis (to correct sensor drift and offsets)

World Ocean Data Centre

• Objective Analysis

• Post objective analysis subjective checks (to detect unrealistic – “bulls eyes” features in data sparse areas)

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II. References Argo quality control manual, V2.2, 2006 (http://www.coriolis.eu.org/cdc/argo/argo-quality-control-manual.pdf)

Coriolis Data Centre, In-situ data quality control, V1.3, 2005 (http://www.coriolis.eu.org/cdc/documents/cordo-rap-04-047-quality-control.pdf)

GOSUD Real-time QC, go-um-03-01, V1.0, 2003 (https://www.ifremer.fr/bscw/bscw.cgi/0/53815)

Data Type guidelines - ICES Working Group of Marine Data Management (12 data types) (http://www.ices.dk/Ocean/guidelines.htm)

GTSPP Real-Time Quality Control Manual, 1990 (IOC MANUALS AND GUIDES #22)

(http://www.meds-sdmm.dfo-mpo.gc.ca/ALPHAPRO/gtspp/qcmans/MG22/guide22_e.htm)

UNESCO/IOC/IODE and MAST, Manual of Quality Control Procedures for Validation of Oceanographic Data, 1993 (Manual and Guides #26) (http://www.jodc.go.jp/info/ioc_doc/Manual/mg26.pdf)

“Medar-Medatlas protocol, Part I: Exchange format and quality checks for observed profiles”, V3, 2001 (http://www.ifremer.fr/medar/qc_doc/med_manv3.doc)

“QUALITY CONTROL OF SEA LEVEL OBSERVATIONS”, ESEAS-RI, V1.0, 2006 (http://www.eseas.org/eseas-ri/deliverables/d1.2/)

QUALITY CONTROL PROCESSING OF HISTORICAL OCEANOGRAPHIC TEMPERATURE, SALINITY, AND OXYGEN DATA. Timothy Boyer and Sydney Levitus, 1994. National Oceanographic Data Centre, Ocean Climate Laboratory

World Ocean Database 2005 Documentation. Ed. Sydney Levitus. NODC Internal Report 18,U.S. Government Printing Office, Washington, D.C., 163 pp

Quality checks at Ifremer/Sismer (http://www.ifremer.fr/sismer/program/qc_phy/quality_UK.htm)

IGOSS Quality Flags (http://www.nodc.noaa.gov/argo/qc_flags.htm)

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Topics







V. Quality Controls


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RT and DM profiles from operational oceanography

Data sets from the GTS (real time transmission) with rounded values and poorly documented profiles

International Programmes and data exchange/dissemination

Data insufficiently documented and attributed to two different sources

PTS files and same station with other parameters

Data declassified by the Navies with poor meta-data

…

III. Causes of the duplicates

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effect the products preparation

(bias the computations)

mistakenly reported and disseminated data

III. Why to prevent duplications ?

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III. How to handle the duplicates ?

There are copies of one data set in several in several regional databases (ICES), project (MEDAR) and global databases (WOD05)

The duplicate data should not be reach the aggregation level

The simplest way: the duplicates descriptions (metadata) must not enter the system

Submit only your national metadata

(Project coordinator country= collator/data center country)

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Topics







V. Quality Controls


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IV. Quality Control Procedures within SeaDataNet

Reformatting

Quality Controls

Metadata Management +Information Compilation

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IV. Data reformattingIn general the original formats of the data files cannot be

used in data management

Incomplete/not standardized meta-data

Incompatibility with QC and other processing input format

Need of a unique format for safeguarding and exchanging the data sets of the same type

Data management format, archiving format and transport (exchange) format may be not necessarily the same

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IV. Sustainability of an archiving formatThe archiving format should:be independent from the computer (and libraries)

– RDBS are not appropriate

insure that any isolated data includes enough meta-data to be processed (eg. Location and date)

be compatible and include at least the mandatory fields (meta-data) requested for the greed exchange format(s)

Include additional textual or standardized “history” or “comment” fields to prevent any loss of information

Provide similar structure and meta-data for different data type such as vertical profiles and time series

These rules are normally followed also for exchange formats.

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IV. SeaDataNet adopted transport formats

Obligatory formats

•NetCDF (Binary) for gridded data and 3D observation data such as ADCP

•ODV4 spreadsheet for other data types (vertical profiles and time series

Optional

•ASCII Medatlas

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IV. SeaDataNet Tool for data reformatting

a new reformatting tool to convert any ascii file to Medatlas and ODV formats

In addition: interacts with Mikado to produce ISO 19115 XML metadata descriptions

How it works? Next presentation by M.Fichaut

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V. Quality Controls


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V. SeaDataNet Quality Control Standards

SeaDataNet quality control flags (L201)

SeaDataNet Protocol V1

Ocean Data View V4

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SEADATANET Quality Flags values

(Based on IGOSS/UOT/GTSPP & Argo QC flags)

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V. Tool for quality control

Ocean Data View for automatic checks and visualization

Integration for DIVA

(presentation by R. Schlitzer)

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V. Quality Controls


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VI. Why Metadata?

We need the metadata to discover the data

SeaDataNet built a metadata system to discover the data

It is ISO19115 compliant for interoperability with other systems

Partners’ maintain the system by submitting metadata

No metadata = no discovery of partners’ data

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VI. Metadata Discovery System

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High Level Directories – EDMED, CSR, EDIOSfor describing collected observation datasets

(by ships, by laboratories, by continuous observing system)

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Common Reference Tables – EDMERP, EDMOhold research projects and organizations metadata common to higher directories

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The Common Data Index (CDI)provides access to the data, information and products by data type and/or any other field

distributed by the TA platforms

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VI. System Maintenance and Upgrade1. Version 0 – 2006-2007

• Continuation and maintenance of existing Sea-Search system :

the data access needs several different requests to each data centres

and the data sets are delivered in different formats

2. Version 1 – 2008-2010

• Setup of the integrated online data services to users :

networking of 10 “interoperable” data centres of the Technical Task Team

unique request to the interconnected data centres

and the data sets are delivered with a unique format

Presently under test and progressive integration of 10 data centres during 2008

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VI. How to submit Metadata?1. Compile the information

For all types of data information is required about :

Where the data were collected: location (preferably as latitude and longitude) and depth/height

When the data were collected (date and time in UTC or clearly specified local time zone)

How the data were collected (e.g. sampling methods, instrument types, analytical techniques)

How the data are referenced (e.g. station numbers, cast numbers)

Who collected the data, including name and institution of the data originator(s) and the principal investigator

What has been done to the data (e.g. details of processing and calibrations applied, algorithms used to compute derived parameters)

Comments for other users of the data (e.g. problems encountered and comments on data quality)

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VI. How to submit Metadata?2. Check for missing mandatory information and ask the originator

(bold in documents describing the XML schemas, available at BSCW)

3. Map your metadata with the fields described in the XML documents

4. Prepare the XML files:

Mannually

using the on-tools (CMS forms)

MIKADO

Automatically (if metadata are in a RDBS, configuration files are needed)

using MIKADO

local tools

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VI. How to submit Metadata?

5. Always validate the XML files using the available XSD schemas before sending them to the directory manager (if you used the off-line tools)

Practical work follows

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VI. Population tools and updating mechanismsSynopsis

Through on-line (like CMS forms) and off-line tools that produce XML ISO 19115

compliant exchanges and developed by the Technical Task Team in the joint

research activities JRA1,JRA2

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SDN Discovery System Contents

EDMED: 3.500

CSR: 39.648

EDMERP: 1.600

EDMO: 1.134

CDI: 341.499

Documents

Sissy Iona HNODC, Greece