1. Data Type Registry Data set descriptions for automation
Stephen M Richard, IEDA, EarthCube
RDA Plenary 8, Denver, CO

2. Use cases Document the meaning of entities and attributes in data.
Re-use of data type and attribute definitions
Machine-assisted data integration: matching attribute content.
Validation of data instances against a type definition.
Tools that spin up a UI for a particular data type.
Link software to data sources that it can use
Support file introspection to assist with deep data registration

3. Use Case Scenario: Data integration
For demonstration, we are interested in hydraulic conductivity
Different field names, table layouts
Workflow:
Import to document store using source data structure
Inspect the field names and values to propose mapping to known data types
Curate to valid and refine mappings

4. Role of DTR in processing Pipeline

5. DTR model update: Some Input Sources
RDA data Type registry prototype (WG output, March 2015)
ISO19110
ISO11179 Clause 11
CSDGM Entity/Attribute
OGC SWE Common Data Model
NetCDF common data model
Apache AVRO
XML schema

6. The model.. Thing Property DataObject Attribute
Conceptualization of the world
Thing
has
Property
0..many
meaning
representation
has
DataObject
Attribute
Some properties on a thing might be essential, others might be optional. A property may have links back to the Things (ObjectClass in the UML) that can carry that property.
A property may have a conceptual domain defined that scopes the intention of the values for that property.
0..many
Representation of the world

7. Representation.. Attribute DataType DataObject Array Dictionary List
has
Attribute
0..many
has
DataType
DataObject
Array
Dictionary
List
Primitive

8. Simple ‘Flat File’ DataObject = meanPorosity observation
Well Name
location
depthTop_ft
depthBottom_ft
meanPorosity
lithology
formation
source
DCL & FA #1
SE1/4NW1/4NW1/4, sec. 13, T. 12 S., R. 17 E.
2,420
2,443
0.105
vuggy dolostone
Jefferson City Dolomite.
Gogel, 1981; reported by usgs2321 Table 2
Geis #1
SW1/4SW1/4SW1/4, sec. 32, T. 13 S., R. 2 W.
1,980
2,200
0.13
oolitic limestone
Lansing and Kansas City Groups.
3,482
3,493
0.074
dolostone
Roubidoux Formation.
SE1/4NW1/4NW1/4, sec. 13, R. 17 E.
2,934
2,985
0.92
calcareous sandstone and granite
Lamotte Sandstone and Precambrian rock.
2,616
2,804
0.181
cherty limestone and dolostone
Warsaw, Keokuk, and Burlington Limestones.
2,944
3,046
0.125
porous dolostone
Hunton Group.
DataObject = meanPorosity observation
Attributes: Well Name
Location
depthTop_ft
depthBottom_ft
meanPorosity
lithology
formation
source
Values all have datatype = primitive
DataObject
Attribute
DataType
Primitive

9. More complex DataObject
<Description> <scope> <scopeCode>service</scopeCode> <name>Internal service</name> </scope> <dateInfo> <date> T00:00:00</date> <dateType>creation</dateType> </dateInfo> </Description>
attribute
attribute
Data object
attribute
Data object
attribute
attribute
Data object
attribute

10. For Proposed Model Details see
current.htm