System concept and development by:Tony ReesDivisional Data CentreCSIRO Marine Research, Australia

c-squares - a new method for representing, querying, displaying

and exchanging dataset spatial extents

some example Metadatabases (Data Directories)

Typical features: include searchability by • text• keywords• spatial and time constraints

This presentation - focus on spatial searching

+ many others -- 100 < 1000? ...

current “base level” representation of spatial data coverage in metadata is by bounding box (minimum bounding rectangle, MBR)

• concept introduced in 1994 (FGDC)

• used for spatial searching, 1995 onwards

• still the primary tool for metadata spatial searches

--------- data

----- data bounding rectangle (MBR)

--------- search rectangle

How well do MBR’s represent spatial data?(examples from our own metadata system)

Franklin 02/1999 hydrology data

MBR actual data locations

SRTM 8-449 catch data

Catch records - Hoplostethus atlanticus

alternatives to MBR’s for representation of data spatial extents ...

• bounding polygons

• multiple bounding rectangles

• defined regions - countries, administrative areas, bio- or geo-regions …

• circles (centre point + radius)

• pre-defined path + distance (e.g. along a contour, coastline, satellite path)

• actual point locations held in the metadata record

• grid-based system

global grid systems already available ...

• International Map of the World (IMW) rectangles (6 x 4 degrees)

• Marsden Squares (10 x 10 degrees)

• Maidenhead Squares (2 x 1 degree)

• WMO (World Meteorological Organisation) Squares (10 x 10 degrees)

• others ?

-- WMO squares eventually chosen for ease of subdivision (base 10) and simple relationship between WMO numbers and lat/long values

WMO 10-degree squares notation (part)

(Available via the web in NODC, 1998: World Ocean Database 1998 Documentation)

3414

1400

The “c-squares”concept

c-squares:Concise Spatial Query and

Representation System

“c-squares” principle

data “footprint” using bounding rectangle

data “footprint” using 1 x 1 degree c-squares

actual ship’s track - “Franklin” voyage 10/87

same using 0.5 x 0.5 degree c-squares

• each square is numbered according to a globally applicable system based on recursive divisions of WMO (World Meteorological organisation) 10-degree squares, e.g.:

10 degree square: 3414 (= WMO number) 5 degree square: 3414:2

1 degree square: 3414:227 0.5 degree square: 3414:227:4

0.1 degree square: 3414:227:466(etc.)

• strings of codes represent an individual dataset extent, e.g.3013:497|3111:468|3111:478|3111:479|3111:488|3111:489|3111:499|3112:122|3112:123|3112:131|3112:132|3112:134|3112:141|3112:142|3112:143|3112:217|3112:218|3112:219|3112:226|3112:235|3112:350|3112:351|3112:352|3112:353|3112:360|3112:361|3112:362|3112:363|3112:370|3112:371|3112:380|3112:381|3112:390|3113:100|3113:101|3113:102|3113:103|3113:104|3113:205|3113:206|3113:207|3113:216|3113:217|3113:228|3113:238|3113:239

encodes the extentshown in the example:

“c-squares” numbering system

Codes have straightforward relationship with lats/longs, mapsheets, etc. ...

e.g.:

1400:458 (1-degree square with origin at 45 º N, 008 º E)

additional degrees E [00+8] =8 additional degrees N [40+5] = 45 5-degree quadrant, i.e. 3 4 1 2

tens of degrees E (i.e., 00) tens of degrees N (i.e., 40)global sector (1=NE, 3=SE, 5=SW, 7=NW) 110 km

8 9 10

44

45

46

0.5- and 0.1- degree squares

squares can be “bulked” - example: 3212:*** instead of specifying every 1-degree square within 10 degree square 3212.

This leads to corresponding data reduction, e.g. Australia (at 1-degree resolution) can be described in 343 squares rather than 800:

“quad tree” -type approach used where numerous adjacent squares are occupied

Example database-level implementation of c-squares for metadata records (e.g. at 1 degree resolution)

(etc.)

• c-squares spatial queries simply test whether a text string representing the search box (ideally one or several c-squares) is matched anywhere in the c-squares string …

example: - search square 3113:2 will match any c-squares string which includes 3113:2 within it, e.g.:

<csquares>3112:363|3112:370|3112:371|3112:380|3112:381|3112:390|3113:100|3113:101|3113:102|3113:103|3113:104|3113:205|3113:206|3113:207|3113:216|3113:217|3113:228|3113:238|3113:239</csquares>

hierarchical naming system for c-squares means that finer resolution squares are automatically picked up in any “coarser resolution” search

Spatial queries using c-squares

example search result ...

(etc.)

Viewing the full metadata record produces ...

(etc.) with clickable link to show dataset extent using c-squares:

Base maps for displayed data can be changed at will by the user, e.g.:

(numerous other maps available, sample only shown)

c-squares strings can be sent directly to the CMR c-squares mapper (accessible via the web), e.g. from OBIS (Ocean Biogeographic Information System, USA):

Process invoked for web mapping

<form action = "http://www.marine.csiro.au/cgi-bin/cs_map.pl" method="post"><INPUT TYPE="hidden" NAME="csq" VALUE="3215:459:4|3215:459:3|3215:459:4|(etc.)"><INPUT TYPE="hidden" NAME="title" VALUE="Global Distribution of <i>Raja</i>"><INPUT TYPE="submit" NAME="submit" VALUE="make map ..."></form>

<metadata>

<title>Franklin Voyage FR 10/87 CTD Data</title>

<custodianOrg>CSIRO Marine Research</custodianOrg>

(etc. etc.)

<boundingBox>

<northBoundingCoord>-9.0</northBoundingCoord> <southBoundingCoord>-19.0</southBoundingCoord> <westBoundingCoord>117.0</westBoundingCoord> <eastBoundingCoord>145.8</eastBoundingCoord>

</boundingBox>

<csquares>3111:499:2|3112:390:1|3111:489:3|3112:380:3|3112:380:4|3112:381:1|3111:488:2|3112:381:2|3112:371:3|3111:478:4|3112:370:4|3112:370:1|3111:478:1|3111:479:2|3111:479:1|3112:361:4|3111:468:4|3112:363:3|3112:361:3|3111:467:2|3112:360:2|3112:363:1|3112:362:2|3112:360:1|3112:352:4|3112:352:3|3112:350:4|3112:352:1|3112:351:2|3112:352:2|3112:353:2|3112:353:1</csquares>

(etc.)

c-squares strings are suitable for inclusion as a new metadata element alongside “bounding box”, for example ...

… would permit interoperability with both enabled and non-enabled systems

Summary - strengths and weaknesses of c-squares

Strengths ...

• “c-squares” is a concise and flexible method of encoding simple to moderately complex forms

• automated or manual code entry (and maintenance) is straightforward

• spatial searching is simple text string matching operation (no GIS involved)

• “c-squares mapper” utility available via simple web call

• can be used as adjunct to bounding coordinates searches

Weaknesses …

• some other numbering systems in use (Marsden Squares, Maidenhead Locators) - needs willingness to standardise on a single system for interoperability

• c-squares are not a fixed multiple of kilometres, miles, etc.

• strings can become quite long for large, complex regions (e.g. “Pacific Ocean”) - need to be able to incorporate data reduction using “bulk” method

other comments ...

• “c-squares” notation is language-independent - can be equally useful in English, French, Italian, Japanese … also discipline-independent

• downwards-scalability of the c-squares notation means that it can be applied to any size region (e.g. local level)

• equally applicable to both terrestrial and marine data

• uses established standards for nomenclature, basis already available via the web (e.g. NODC site)

• Implemented already in CMR’s “MarLIN” metadata system and “CAAB” taxon dictionary

• concept is available for implementation in any other agencies’ metadata systems without cost or technology overhead

• potential to to be recognised as a formal metadata element by relevant user communities / national bodies

• current CMR c-squares mapper is already accessible for general use

• c-squares website constructed as a focal point for all c-squares related materials - including:

• initial c-squares specification• connection information to the c-squares mapper• sample PL/SQL code (to convert lat/long pairs to c-squares)• on-line lat/long - to - c-square converter• example c-squares-enabled metadata records, and more

c-squares current and future status...

Questions, comments?

Acknowledgements …

• Miroslaw Ryba and other CMR staff for assistance with constructing the c-squares mapper and general feedback

• “Blue Pages” Marine and Coastal Data Directory (MCDD) for the notation for subdividing WMO squares

• Martin Dix (CSIRO Atmospheric Research) and NOAA “Globe” Project for base maps as used in the mapper (used by permission)

website: http://www.marine.csiro.au/csquares/(NB: handout available at this meeting)

My email: Tony.Rees@csiro.au