AGU2017 fall meeting 2017, New Oreleans, 11th Decmember 2017 IN13D-08 Oceanids command and control (C2) data system Marine autonomous systems data for vehicle piloting, scientific data users, operational data assimilation, and big data (with a focus on the metadata system) Justin J H Buck1 Alexander Phillips2, Alvaro Lorenzo2, Malcolm Hearn1, Thomas Gardner1, Kay Thorne1, Alexandra Kokkinaki1 and Oceanids command and control system development team (1) National Oceanography CentrE, BODC, Liverpool, United Kingdom (2) National Oceanography CentrE, MARS, Southampton, United Kingdom

The Oceanids Command and Control (C2) project

The MARS fleet of underwater vehicles Long range fleet includes: Submarine gliders Autonomous underwater vehicles Autonomous surface vehicles Each vehicle akin to a small research vessel in its observation capability. MARS fleet Deployments: NOC-MARS SAMS UEA BAS Total 2016-17 8 5 3 16 2017-18 18 + 5 9 33

Current management of long range fleet operations Command and Control Current management of long range fleet operations Autosub Long Range Slocum C-Enduro Seaglider Waveglider Autonaut Data Management Data Visualisation www.mars.noc.ac.uk Science Data

Command and control (C2) goal AIS, Tides, Weather, Etc. Science Data Products Unified Piloting Interface www.mars.noc.ac.uk Human pilots controlling a fleet of vehicles or autonomous control of the fleet with human oversight. Piloting Aids e.g. Fleet Health Monitoring & Mission Risk Assessment Data Processing Vehicle Missions Consistent data formats e.g. NetCDF Science Data & Engineering Data Fleet Operations Data Management Science Data

Command and control (C2) goal AIS, Tides, Weather, Etc. Science Data Products Unified Piloting Interface www.mars.noc.ac.uk Human pilots controlling a fleet of vehicles or autonomous control of the fleet with human oversight. Piloting Aids e.g. Fleet Health Monitoring & Mission Risk Assessment Data Processing Vehicle Missions Consistent data formats e.g. NetCDF Data need to be archived, processed and accessible within seconds to minutes of collection. Science Data & Engineering Data Fleet Operations Data Management Science Data

System architecture & status Oceanids portal; human interface to services and apps e.g. piloting, data, data products, reliability analyses etc. System architecture & status Glider data toolbox Data fusion & advanced autonomy Agile based development methodology used. API gateway Data archive Data delivery Authorisation & access control Meta-data system Work-flow control Piloting data core In production Testing Current development C2 data broker Not started Data processing Data backend Vehicle sensors

Oceanids metadata system

Metadata system requirements Meta data need to be sufficient to fully automate the processing, discovery and delivery of data in near real time covering: Sensors Platforms Access control Deployment information (project, PI, etc) Metadata will need to be created prior to deployment Metadata system builds on the work of previous projects: Oceans of tomorrow - SWE and linked data for the marine domain ENVRIplus OGC SWE sensor repository

Metadata curated using open & standard ontologies geo: geoSPARQL ontology for geospatial linked data LSO SSN Good relations PROVO om-lite SKOS time geo ssn:What sensors measure, how they measure, and the qualities of such measurements time: temporal concepts, durations and datetime information NVS2 Platform types (L05) Sensors (L22) Roles (C38) Units of Measure (P06) Manufacturers (L35) Observable Properties (P01/P02) Sensor Types (L06) gr: Model, manufacturer, hasMakeAndModel, depth, height, weight SKOS: Supports the use of knowledge organization systems (KOS) such as thesauri, classification schemes, subject heading lists and taxonomies within the framework of the Semantic Web provo: What has occurred and how things were made what the entities are, what produced them and how om-lite: An OWL representation of the Observation Schema O&M /OGC Supports metadata exposure in: SSN RDF OGC SensorML JSON-LD? Here you can add an oral comment about integration and update with the new SOSA ontology.

Marine SWE profile (http://meetingorganizer. copernicus <sml:classfication> <sml:ClassifierList> <!-- Name of the manufacturer of the Sensor X --> <sml:classifier name=“InstrumentType"> <sml:Term definition= "http://vocab.nerc.ac.uk/collection/W06/current/CLSS0002/"> <sml:label>Instrument Type</sml:label> <sml:value> http://vocab.nerc.ac.uk/collection/L05/current/353/ </sml:value> </sml:Term> </sml:identifier> <sml:IdentifierList> </sml:identification>

ERDDAP instance form https://www.linkedsystems.uk/erddap/InstancesHome.html Form to create sensor and platform instances UUID returned to users to uniquely identify sensor Sensors can be linked to platforms to build deployment metadata Results available in SensorML via linked systems domain This form is the basis for creation of metadata via the Oceanids portal

Summary This standardised data delivery API gateway will enable timely near-real-time data to be served to Oceanids users, BODC users, operational users and big data systems. Current envisioned standards: OGC SWE demonstrated during the Oceans of Tomorrow projects W3C linked data, example sensor at http://en.lodlive.it/?http://linkedsystems.uk/system/prototype/TOOL0969/ EGO NetCDF to serve Ocean glider network Also see demonstration of operational BODC & SeaDataNet SPARQL endpoints (AGU data fair, Wednesday 12pm) The use of open standards will enable web interfaces to be rapidly built on the API gateway and delivery to European research infrastructures that include aligned data reference models: EMSO using OGC SWE as a standard ENVRIplus sensor repository API gateway can potentially be opened beyond Oceanids users once C2 fully operational and impacts understood

Questions?

Acknowledgments Oceanids project is funded by a 4 year NERC capital call awarded in 2016. Data standards work was funded by the European projects SenseOCEAN and BRIDGES, and supported by the National Environmental Research Council (NERC). SenseOCEAN is a Collaborative Project funded by the European Union Seventh Framework Programme (FP7/2007–2013) under grant agreement No. 61414. BRIDGES project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 635359. NVS2.0 server is supported by NERC National Capability (NC) funding for NC-services, facilities and data (NC-SFD).