1. Existing Designs and Prototypes at RPI
Show and Tell
Existing Designs and Prototypes at RPI

2. Earth Science Ontology Repository (ESOR)

3. What is ESOR?[1]
The Earth Science Ontology Repository(ESOR) provides an entity matching service as a backend knowledge base for multiple applications. It serves a similar function as BioPortal[2], but with more of a focus on the Earth Science domain.

5. How to use ESOR
links:
keyword search:
matched entity with score by keyword
dataonetwc.tw.rpi.edu/linkipedia/search?query=
ontology by entity
dataonetwc.tw.rpi.edu/linkipedia/read?url=

6. Example#1 input: “snow, snow depth” (MsTMIP #28)
output of keyword search:

7. Example #2
output of matched entity with score by keyword:

8. Example #3
output of ontology by entity:

9. Comparison with Bioportal
using “snow depth” or “snow, snow depth” as input, Bioportal will return matched entities with either of the keywords “snow” or “depth”. Therefore, the better match “ is missed.
A similar problem occurs with other MsTMIP variables (#10 Heterotrophic Respiration, #11 Leaf Area Index, #22 Near surface specific humidity, #23 Sensible heat, #24 Latent Heat )
Bioportal had much more complicated functions than ESOR. However, if we just use it as a backend knowledge base, our ESOR has better performance in terms of recall and precision.

10. List of ontologies version 1 (the current version)
ChEBI (Chemical Entities of Biological Interest)
OBI (Ontology for Biomedical Investigations)
OBO-E (Extension Observation Ontology)
PROV-O (The Provenance Ontology)
SWEET Chemical Properties
SWEET Human Research
SWEET Units
SemantEco Water Ontology
Semanteco Pollution Ontology
Time Ontology
UO (Units of Measurement Ontology)
dcterms (Dublin Core)
foaf (Friend of a Friend)
geonames
wgs (Basic Geo Vocabulary)
...
version 2 (coming soon)
KB_Bio_101 (AURA)
Santa Barbara Coastal Observation Ontology (OBOE-SBC)
...
* for the complete list, see document section 3:

11. Underlying techniques

12. How can we benefit from ESOR in D1?
help the user to choose the right entity with which to annotate their dataset
serve as a backend knowledge base for automatic semantic annotation
match entities based on content instead of single keywords

13. SemantEco Annotator

14. SemantEco: Semantic Environmental Monitoring
Goal
Approach
Question we try to answer
Enable/Empower communities (citizens & scientists) to explore pollution sites, facilities, regulations, and health impacts along with provenance
Connections to USGS, Lake George, IBM, expanding to discussions of predictions and intervention suggestions
Where are pollution events happening?
What are the health impacts?
How does pollution correlate with population changes (wildlife, invasives, etc.)?
Explanation of pollution limits
Graphing thresholds and trends
Possible health effect of contaminant (EPA)
Filtering by facet to select type of data
Link for reporting problems
Extended with input from USGS, with population counts for birds & fish

15. Tools for Semantic Annotation of Measurements
Annotator
Demo:
annotation of CSV’s
OBOÉ design pattern
D1 Phase I product, and other ongoing work at RPI...
GITHUB, Web interface available

16. Focus of D1 Semantics in Phase II
Semantics of Measurements:
...binding raw data values to concepts drawn from ontologies
...often through metadata
...using W3C standards for annotation--
PROV, OA
...to facilitate resource discovery and interpretation through enhanced precision and recall of searches

17. What’s new: ontology search
Features:
Weighted ranking
Entity Linking
Similarity check
User Preference
Semantic Annotator owl search takes advantages of the earth science ontology knowledge base and linkipedia tool from Tetherless World Constellation at RPI.

18. What is new: User Management
User interface can be implemented for a variety of storage / representation methods
User Store interface handles read-write for Users (to-from database, file, etc)
Permission interface is a simple representation of source and level that can be translated to URI
Permission
User
UserStore
Misc interface updates:
Integrated ontology search
Other bug fixes

19. How can we benefit from SemantEco Annotator in D1?
Annotator can be integrated into the DataONE annotator, especially for use with CSV-formatted datasets
Reuse the design pattern
Facilitate resource discovery and interpretation through enhanced precision and recall of searches

20. Related projects
Jefferson Project

21. The Jefferson Project
Fundamental Goal: Understand, Predict and Enable a Healthy Lake George Ecosystem Using Cutting–Edge Science to Enable Smarter Solutions
Multi-beam SONAR, Bathymetric LiDAR, Terrestrial LiDAR, Sensor Network composed of 30+ instruments streaming data 365/24/7
High resolution, high accuracy, high data density seamless data set
~ 70 Tb/year total raw data expected, 7-8Tb/year of “product data”
Semantic approach's contributes in two knowledge representation and reasoning areas
human interventions on the deployment and maintenance of local sensor networks including the scientific knowledge to decide how and where sensors are deployed
Data Integration through the use of the Human-Aware Sensor Network Ontology (HASNetO), which is based on OBOE, W3C PROV, and VSTO
knowledge about simulation results including parameters, interpretation of results, and comparison of results against external data

22. Reference
[1] ESOR link:
[2] BioPortal:
[3] The Earth Science Ontology Repository: [4] Wikipedia/dbpedia mapping for MsTMIP variables: ding=h.fj17u9rk42u [5] MsTMIP use case: 1NNqE5DEi585MnOq8fhpo/edit#heading=h.u4s2g4klu51s [6] MsTMIP 45 variables mapping: [7] Annotator:
Thanks!