Introduction

aspects common to biodiversity data:

1. what (taxonomy)
2. when (temporal)
3. where (spatial)
4. who (collectors)
5. (and sometimes why, e.g. symbiosis)

sub-systems of the atlas, where data surface

i.e. appear, or are made accessible :

1. biocache - http://biocache.ala.org.au - the main specimens+sightings database
2. spatial portal - http://spatial.ala.org.au - the geographical information system (gis), which shares a common backend with the biocache and allows users to cross-reference the species observation data with contextual (dots, lines, boxes, polygons...) and environmental (measurements+facts, classifications, opinions...) data; see http://spatial.ala.org.au/alaspatial/layers/ for a list of layers
3. biodiversity information explorer (bie) - http://bie.ala.org.au - stores the profile data for taxa (descriptions, taxonomy, synonymy, common names, multimedia, ...)
4. collectory - http://collections.ala.org.au - stores information on most data providers
5. volunteer portal - http://volunteer.ala.org.au - a collaborative tool for users to help collections, particularly with transcription of labels, etc.
6. morphbank - http://morphbank.ala.org.au - the australian node of the morphbank distributed network of images & multimedia
7. ... not an exhaustive list

different kinds of data

the sub-systems may be aware of many logical classes of data:

1. species' observation data (what+when+where+who)
2. species' profile data (what+who, what+where, what+why)
3. resource descriptions (who, what)
4. spatial (environmental) data (where)

	observations	profile data	resources	spatial
biocache	1			2
spatial portal	3			4
morphbank	5	6
bie		7		8
collectory			9

classes of data relate to each other

some of these (types, kinds) of data can be related through common dimensions (or aspects, facets, natural keys, ...):

Relate...	observations	profile data	spatial layers
to observations	through preparations, derivation, digitisation, biological relationships, collectors, collection events, statistical analysis	identification, associations (explicit or inferred)	location desc./coordinates, environmental classification
to profile	through taxonomy, inference	taxonomy, biological interactions	taxonomy
to resources	through data provision	taxonomic coverage	spatial layer metadata
to spatial	through location descriptions or coordinates, species distributions, predictive analysis	with species' distributions	by environmental layer grouping, e.g. median rainfall & max rainfall => 'rainfall'

although there is a number of potential relationships at all intersections, there are common aspects that allow for the relationship to exist; when they are normalised we find ourselves with a list of possible dimensions, common to the kinds of data relevant to biodiversity:

naturally, that wouldn't be complex enough! so follow this link for more specifics as well...

https://sites.google.com/site/atlaslivingoz/ala-data/classes