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- Clowder
- Dataset is annotated with sensor information
- Reuse existing relationship between dataset and sensor
- Or... add metadata to dataset
- Variable Annotation Extractor (VAE)
Jira server JIRA columns key,summary,type,created,updated,due,assignee,reporter,priority,status,resolution serverId b14d4ad9-eb00-3a94-88ac-a843fb6fa1ca key BD-2315 - Annotate files with entries from standard vocabularies
- Col. 3 contains term http://odm2/precipitation
- Multiple mappings can be provided, each with their own likelihood
- For example, if only 9 out of 10 columns match a prior mapping, likelihood is 90%
- Or percentage of files seen with this type of mapping
- Variables Mapping Service (VMS)
Jira server JIRA columns key,summary,type,created,updated,due,assignee,reporter,priority,status,resolution serverId b14d4ad9-eb00-3a94-88ac-a843fb6fa1ca key BD-2310 - POST/GET/PUT/DELETE mappings
- The collection in MongoDB contains documents that represent mappings
- Each mapping is a collection of mappings between strings (column headers) and standard vocabularies (uri terms)
- How many times have seen a particular mapping (how many unique files)
- When a mapping is not complete, i.e. we can only identify a subset of the columns, we should keep track of how many we columns we successfully identified
- let's say a csv file has 10 columns, but we can only tag 4, we would have 40% accuracy
- Maybe keep a collection of what files match what mapping
- SEARCH for mappings that match a set of CSV headers and return them in order of accuracy
- Client submits one list of CSV column names, service returns a list of potential mappings including accuracies.
- Dockerize the service:
Jira server JIRA columns key,summary,type,created,updated,due,assignee,reporter,priority,status,resolution serverId b14d4ad9-eb00-3a94-88ac-a843fb6fa1ca key BD-2318
- Semantic Annotation Service (SAS)
- http://ecgs.ncsa.illinois.edu/SAS.html
- We should build a simpler version of this as a Flask application storing info in MongoDB
- Datapoints Extractor (DPE)
- Creates datapoints in the Geostreaming API based on rows in the CSV input file
- Requires mapping from Variable Annotation Extractor
- Site information as metadata on dataset
- Geostreaming Data Framework
- Store and visualize datapoints
- https://geodashboard.ncsa.illinois.edu/
- Geostreaming API (GSAPI)
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