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Home > Courses/Training > Marine DM II
MDL COURSE 102: Introduction to Marine Data Management II
Version: 2-11-2015
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THIS COURSE covers many topics covered by the complex diagram below. It is a great starting point for graduate students, young professionals and experts in fields related to oceanography. Prior to the course, each student must read through a list of background articles in the IODE OceanTeacher Academy Digital Library. At the end of the course, each student must present a personal project presentation. Most of the data products involved are climatological, but a good introduction to operational/synoptic products is included. It involves a number of carefully-selected global datasets that represent major formats, or that require common methods of preparation before display in GIS maps. Students will work with a selected single area for classroom exericises (Liberia), but are requested to make a parallel suite of analyses for their own areas of interest (not always their home region!). A short PowerPoint of those analyses should be sent in at the end of the course.
Volunteer instructors: All Docents, Murray Brown
Skills and practices that will be taught:
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How to install and set up the chosen GIS software, Saga
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How to find, download and display the very most basic global maps
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How to select, specify (by coordinates) and save an area of interest (AOI) map for any country
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How to create ancillary GIS objects needed for further work, such as grid templates, frames and AOI polygons
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Find and add global relief (i.e. bathymetry, topography) data to maps, from either grid or vector sources, particularly GEBCO 2003
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How to add gridded data to maps
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How to cut global gridded data down to the AOI
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How to identify, find and download numerous map objects of interest from a catalog of global sources
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How to obtain historical in situ marine data (stations, drifters, ships-of-opportunity, etc.) from the largest global archive, the World Ocean Database
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How to create an ocean data collection for the AOI in the software Ocean Data View (ODV)
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How to create a family of standard data collection products in ODV: station plots, scatter plots, section plots, surface plots, sample history plots (as Hovmuller plots), time- and space-distribution of current vectors
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Select data subsets within the AOI collection and export them in various formats (ASCII, ODV)
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Create surface plots for specially-selected parameter-surface combinations, and export them as XYZ tables for use in GIS
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Import ASCII data tables into Saga
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Create shapefiles in Saga for gridding
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How to grid data in Saga
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How to work with color palettes in Saga for optimal presentations
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How to load and use relief data in Saga for analyses and display
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How to make depth- or height-masking grids in Saga for eliminating extraneous portions of grids (e.g. over land, etc)
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What are the most frequently needed products from grids, and how to make them in Saga
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How to estimate contour line positions in grids, with Saga
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Where and how to obtain the broadest spectrum of climatological grid products for use in GIS
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How to use either U- and V-component grids or speed and direction grids in Saga to make wind and current field vectors (i.e. arrows)
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Where and how to obtain operational data from various global systems and to display/synthesize them in Integrated Data Viewer (IDV)'
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SST
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Salinity
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Sea height
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Winds
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Currents
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Pigments
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Primary production
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Etc.
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Connections between Saga and IDV visualizations and Google Earth.
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Connections between satellite image archives and GIS, especially SST and pigments
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How to make good PowerPoint presentations
Required Software (latest versions; Windows and Mac; 32-bit and 64-bit): Saga, GEBCOLite (if GEBCO CD is not available), Ocean Data View, Integrated Data Viewer (IDV), Google Earth
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| 1. Pre-Course Reading |
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2. Integration of Marine Data Resources - Click on the chart to see a better version
Marine data management, quite simply, is a balancing act between the 3 major concepts: Formats, Software and Data. You need to become familiar with major resources in all categories, and how they work together. In years gone past, scientists had to slog through numerous format conversions (including writing necessary code) to make connections. But in recent years a small family of flexible formats, powerful computer programs and flexible online data sources have brought everything together.

This chart seems terribly complicated at first, but it will be explained during the course. We'll be using
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Software
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Ocean Data View (left side)
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Saga (in the middle)
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Integrated Data Viewer (right side)
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Google Earth (right side)
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Data Sources
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World Ocean Database/WOD (left side)
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Online data archives/mixed formats (upper middle)
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Operational data (upper right)
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Others, as time permits
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Formats - As indicated
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3. Preparation for the Course Exercises
You will become hopelessly lost within the short span of this course (1 or 2 weeks) and even in your own personal data collections, unless you adopt good data management practices. We strongly recommend the constant use of these elements:
- Folder Structure - Basic list of topics developed over 20 years of DM training. Author has 10 BG and ~4000 files just for Liberia training
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"Long" File Names
- parameter_
- date/time_
- depth/height_
- location_
- originator_
- provider_
- extras_
- No spaces, no hyphens, no caps (except T), include format in extras, if zipped
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4. Area of Interest
This section deals with setting up an AOI, based on:
Defining the AOI with with signed decimal degree values
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Top latitude (not "north")
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Bottom latitude (not "south")
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Left longitude (not "west")
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Right longitude (not "east")
Making important auxiliary layers
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Graticule - lat/lon lattice
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Line and polygon frames - outer edge of AOI
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Grid templates - to control data gridding
Adding important features
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Political features
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Other coasts
Trimming shapes to the AOI to reduce filesize and speed up mapping
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5. Initial Collection from the World Ocean Database
The WOD is the largest available, online, free ocean database. It should be the starting point for any personal or organizational database:
- Data range from >200 years old to stations within the past few years
- Constantly updated, includes a synchronizing option
- In-situ only, no remote sensing
- No instrumental time-series - e.g. tide gauge, current meter
- About 30 parameters
- 12 types, depending on measurement methods - ship stations, drifters, diving pinnipeds, etc.
- Uses cruise/station/depth/date/time paradigm for data organization
- Includes quality flags for all measurements
Downloading the data is easy and fast:
- Download zipped collections in a venerable, 80-character "archive format"
- Also download or link to huge collection of metadata for each ocean station
Data can be quickly loaded into Ocean Data View (ODV) to create a "collection"
- Native WOD structure can be used
- Other structures (stored in ODV) can also be used
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6. Basic Data Analyses
Users of ODV can immediately make very professional graphical analyses, using several very common "layouts"
- Station plots - plot of any variable(s) versus depth for one or a few stations; usually joined lines
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Scatter plots - plot of any two variables versus each other, usually for large numbers of samples
- T-S plot is a famous plot of temperature and salinity; often used to characterize water masses
- Section plots - plot of any variable along a specified line and versus depth, like a fence; usually gridded for clarity
- Surface plots - plot of any variable on a surface defined by another variable; easier to make and use than to describe
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7. Exporting ODV Products
ODV collections are ideal mechanisms to make data products and graphical analysis products for use elsewhere:
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Original data exported according to various selection criteria
- Export as tabular spreadsheet
- Export as smaller ODV collection for fast use
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Interpolated data exported for a defined "surface" from surface mode
- Variable at Depth = X is often the method used, but can be Variable_1 at Variable_2 = X, etc.
- Images of data, as points or gridded analyses (usual graphics formats)
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8. Data Gridding and Contouring
Gridding and contouring data are linked methods used to visualize and understand data points that are scattered in space. Before computers were set up to contour data, scientists had to do it by hand after all cruises. This exercise should give you some respect for how much work contouring was.
- Gridding - Process of creating a regular lattice ("grid") of regularly spaced values. Each value is the result of calculations ("algorithms") based on nearby original data value. Gridding is a science all its own, and needs careful study. Algorithms range from simple averaging of all values in a defined box around a central point, to extremely complex methods involving much more complex mathematics and operational parameters.
- Gridding smooths out rough areas, and fills in gaps
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Grid - May be rectilinear (horizontal and vertical lattice lines), or may conform to any curvilinear shape. Rectilinear grids may be equilateral (i.e. x intervals = y intervals) or not. Necessary information to describe rectilinear grids would include:
- ASCII or binary?
- ASCII data line terminators: UNIX or DOS?
- Data are Big Endian or Little Endian?
- What number types if binary?
- Number of grid cells in E-W direction?
- Number of grid cells in N-S direction?
- Columns spacing (delta-X)?
- Row spacing (delta-Y)?
- Lat/lon of first point in grid array?
- Location of first point in the grid, lower-left or upper-left?
- Read the grid by rows or by columns?
- Have the grid values been multiplied by some factor, and what is that factor?
- For nested multiple grids, what is the reading order of the variables?
- Some formats are self-describing, so they take care of these questions for you, e.g. HDF, NetCDF, GRIB, ESRI ASC
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Contours can be drawn (manually or digitally) through a grid, to depict the loci of points where a parameter has a specific value, e.g. 18-degree temperature contour
- General term for all contours: ISOPLETHS
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Various types of isopleths:
- Isotherms
- Isohales
- Isobars
- Etc.
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9. Grid and Raster Analysis with Saga
The method to grid data in Saga is very general and applies to most GIS systems:
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The data are first loaded into Saga as a data table
- TXT, tab-separated is best
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Convert the table in the GIS to a "point shape"
- Other shapes you should know are "line shapes" and "polygon shapes"
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Use any one of many available algorithms in Saga
- Make tests to see which work best with your data, and also experiment with the gridding parameters for each algorithm
- Once you have the grid, you can make any of several very important "standard" products for use in publications, theses and websites
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10. Global Relief Data Products
Relief (= depths + heights) has always been a critical concern for scientists, explorers and builders, fishermen, etc. An entire vocabulary and technology has grown up around management of relief data:
- Relief can be expressed as grids or as contour lines. Contour maps are immediately understood by most persons, but grids are required to make them.
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Dozens of formats exist to hold relief data, including special formats designed just for relief.
- Digital Elevation Models (DEM)
- ETOPO series of global products - various resolutions
- GEBCO global grids - 0.5 and 1.0 degree resolutions
- Contours can be held in a small family of vector formats
- GIS programs usually can make/save contour lines from grids, according to user specifications
- Contour lines still hand-drawn to satisfy some official purposes (e.g. GEBCO) or for special situations (e.g. expert knowledge of an area)
Relief product examples:
- Contour maps
- Grids using value-color mapping ("palettes")
- Elevation "tracks" created by moving a cursor over a relief grid
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11. Vector Charts
There are basically 2 types of natural data:
- SCALARS - Values of a parameter that can be complete expressed as a numerical value and its units (when existing). For example temperature in degrees Kelvin, or salinity (no units).
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VECTORS - Values of a parameter that 2 numerical values to be expressed, for example winds and currents:
- COMPONENT VECTORS: Most common method requires vector components in the east-west direction (commonly called the U component), and the vector component in the north-south direction (commonly called the V component).
- DIRECTION VECTOR AND SPEED: Less commonly used method (nowadays) requires a scalar quantity expressing simple speed, and a vector of unit length that expresses direction.
There are 3 ways to express vector directions:
- COMPONENT VECTORS - direction already uniquely defined by components; use geographic direction to describe the result
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GEOGRAPHIC DIRECTION - clockwise "rose"
- North = 0º or 360º according to user's conventions
- East = 90º
- South = 180º
- West = 270º
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MATHEMATICAL DIRECTION - counter-clockwise "rose":
- East = 0º or 360º according to user's conventions
- North = 90º
- West = 180º
- South = 270º
Meteorology versus Oceanography
- Met data often display "direction from which" for wind vectors
- Oc data often display "direction toward which" for current vectors
- You need to look after this on a case-by-case basis to make sure you have the right data and the right display method
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12. Managing Operational Data
"Operational Oceanography can be defined as the activity of systematic and long-term routine measurements of the seas and oceans and atmosphere, and their rapid interpretation and dissemination." - EuroGOOS Definition.
- Making measurements/sampling
- Transmitting data to centers
- QC and processing
- Integration between technical systems
- Modeling
- Distribution of products from all elements
Complex data formats that integrate data and metadata, for example:
- GRIB - met or OO grids
- BUFR - met obs
- HDF - satellite grids
- NetCDF - met or OO obs or grids
- Etc.
Standards and software for data management have also been developed, for example:
- OPeNDAP - protocol for client-server actions for earth science data
- LAS - very widely used online program for visualizing/obtaining data, uses OPeNDAP
- THREDDS - umbrella concept that combines client-server functions of several approaches, including metadata catalogs, OPeNDAP, FTP to allow easy community access to data
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