The document discusses the development of a cross-domain vocabulary for observation data in science, addressing challenges in data integration and analysis. It emphasizes the importance of standardized protocols, procedures, and terminologies for enhancing environmental monitoring and data cataloguing. Various types of samples and observations are defined, along with references to existing standards and frameworks like W3C vocabularies.

1. Web standards support science data
Simon J D Cox
Land and Water
29 May 2018

2. Overview
• X-domain vocabulary for observation data
• Data catalogues
C3DIS 2018-05-29 | Cox | Standards for science data2 |

3. Motivation for a common model
• Integrated analysis and
modelling
• Data integration a significant
challenge
• X-disciplinary terminology
C3DIS 2018-05-29 | Cox | Standards for science data
Remote sensing
Sensor
Value
Parameter
Scene
Earth science
Algorithm, code,
simulator
Model, field
Variable
Volume, grid
Metrology
Instrument
Value
Measurand
Sample
Chemistry
Instrument,
analytical process
Analysis
Analyte
Sample
Environmental
monitoring
Gauge, sensor
Value, time-series
Parameter
Station
Observations &
Measurements
procedure
result
observed property
feature of interest
3 |

4. An Observation is an action
whose result is an estimate of the value of some property of the feature-of-interest
that applied at the stated phenomenon-time,
obtained using a specified procedure, completed at the recorded result-time
C3DIS 2018-05-29 | Cox | Standards for science data Cox, OGC Abstract Specification – Topic 20: Observations and Measurements 2.0
http://www.opengeospatial.org/standards/om
4 |

5. Implementation work
C3DIS 2018-05-29 | Cox | Standards for science data5 |

6. C3DIS 2018-05-29 | Cox | Standards for science data 6 |

7. Integration with existing SeaDataNet Standards
Existing Activity
SWE Adoption
Seismic
7C3DIS 2018-05-29 | Cox | Standards for science data

8. 8
EU Air Quality Directive
C3DIS 2018-05-29 | Cox | Standards for science data

9. 9
12Z
7-May 9-May8-May6-May5-May
00Z00Z12Z00Z12Z12Z00Z12Z 00Z
result
forecast : OM_Observation
parameter.name = “analysisTime”
parameter.value = 2010-05-06T00:00Z
phenomenonTime.begin = 2010-05-06T00:00Z
phenomenonTime.end = 2010-05-09T12:00Z
resultTime = 2010-05-06T04:30Z
validTime [optional – not specified]
resultQuality [optional – not specified]
ISO19156 Observations and measurements:
also suitable for numerical simulations – including forecasts
C3DIS 2018-05-29 | Cox | Standards for science data

10. C3DIS 2018-05-29 | Cox | Standards for science data 10 |
National Environmental
Information Infrastructure

11. C3DIS 2018-05-29 | Cox | Standards for science data11 |
Now a W3C vocabulary (2017)
https://www.w3.org/TR/vocab-ssn/

12. “Observation” = Act of observation
protocols and
procedures
C3DIS 2018-05-29 | Cox | Standards for science data12 |
instruments and sensors
observable-
properties
Conceptual model of the
application-domain including the
object types (features)
Standard terms, encapsulate the complexity

13. C3DIS 2018-05-29 | Cox | Standards for science data13 |
Domain model
Characteristic
properties
height
dbh
taxon
location
Feature type
VascularPlantOccurr
ence
Property values
= 91 m
= 1.5 m
= Eucalyptus
regnans
= -42.72, 146.81
A feature type
is defined by a set of
characteristic properties
A feature
instance
is defined by the
values of its properties

14. “Observation” = Act of observation
C3DIS 2018-05-29 | Cox | Standards for science data14 |
https://www.w3.org/TR/vocab-ssn/
Phenomenon-time = time result applies to feature
Result-time = time result became available
Sensor observations: result-time ≥ phenomenon-time
Forecasts: result-time < phenomenon-time
Archeology, Geology, Cosmology: result-time >> phenomenon-time

15. Many types of result
1.76m Scaled number
(-37.908, 145.029) epsg:4326 Vector, Tuple
Array, Image, Field
“Silurian” ISC 2017 Word or concept, classifier
“poor” {reference} Assessment
“false” Boolean
Value of result is tied to a reference system
C3DIS 2018-05-29 | Cox | Standards for science data15 |

16. Extension for Observation Collections
Members share one or more of
• Observed-property
• Feature-of-interest
• Procedure (protocol)
• Sensor (instrument)
• Phenomenon time, or
• Result time
C3DIS 2018-05-29 | Cox | Standards for science data16 |
https://w3c.github.io/sdw/proposals/ssn-extensions/

17. Sample = result of Act-of-sampling
A ‘sample’ is a thing or subset which is intended to
be representative of a larger thing or set …
… created or selected for the purpose of making
observations to determine the value of one or more
properties, traits or qualities of the larger thing
C3DIS 2018-05-29 | Cox | Standards for science data17
The essential property of a sample is the 'is-sample-
of' relationship with the larger thing.
https://goo.gl/KBvkgW

18. Types of sample
A material sample or specimen is typically
selected to allow ex-situ observations
A statistical sample or subset is a specified
number of individuals from a population
A spatio-temporal sample may have the
same dimension but a smaller extent than
the thing which it represents,
or a lower topologic dimension than the
thing which it represents
C3DIS 2018-05-29 | Cox | Standards for science data18

19. Also actuation
C3DIS 2018-05-29 | Cox | Standards for science data19 |

20. Data catalogs
C3DIS 2018-05-29 | Cox | Standards for science data20 |
https://www.w3.org/TR/vocab-dcat/

21. DCAT 2014
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• Abstraction of registry models –
ISO 2146, 11179, 19135
• Widely used in Europe
• Harvested by Google

22. Data eXchange Working Group
C3DIS 2018-05-29 | Cox | Standards for science data22 |
DCAT-rev

23. DCAT profile for observations?
C3DIS 2018-05-29 | Cox | Standards for science data23 |

24. Summary
• Formal x-domain vocabulary for observation data
• Widely adopted in several domains
• Ontology standardized through W3C 
• Standard Dataset Catalog vocabulary
• Extension to support cataloguing other resources
• Services, … samples, protocols, software
• Also see W3C QB - https://www.w3.org/TR/vocab-data-cube/
• Easily combined for specialist applications
• Science data
C3DIS 2018-05-29 | Cox | Standards for science data24 |

25. Land and Water
Simon Cox
Research Scientist
t +61 3 9545 2365
e simon.cox@csiro.au
w www.csiro.au
Thank you
Land and Water