CEOS Working Group on Information Systems & Services Technology Exploration Subgroup Webinars
Please join us for the 4th CEOS WGISS Tech Expo Webinar:
The Open Geospatial Consortium (OGC) Coverage Standards Suite: Introduction & Overview
Date: Friday, January 19, 2018 (Thursday, January 18 in Asia and Australia)
Time: 13:00 UTC (8:00 AM US EST)
Note: If you cannot attend the live webinar, the recorded webinar and presentation files will be made available here.
Typically, “Big Data” in the Earth science domain arise from spatio-temporal sensor, image, simulation, and statistics data. The OGC coverage concept represents a unifying model for such data, based on which the OGC Web Coverage Service (WCS), as OGC’s “Big Data” standard, provides versatile functionality. Large and growing tool support as well as the massive data offerings existing – such as the Petabyte services of the EarthServer initiative – highlight relevance of these standards. This has prompted further standardization bodies such as ISO and INSPIRE to adopt these standards, too.
In this webinar, Dr Peter Baumann (Managing Director of Rasdaman) will present the coverage data and service definitions and their use for building portals, with special emphasis on spatio-temporal datacubes. Ample room will be available for Q&A.
To attend via computer:
- Please go to: http://earthdata.adobeconnect.
- Participant passcode: 886948#
- U.S. toll-free number: 1-844-467-4685
- Participant Passcode: 886948#
To join via telephone (international participants):
Toll-free access is available for 40+ countries. Passcode: 886948#
Webinar 3 – The Burgeoning Role of Python for Earth Observation Data Analysis
Date: Tuesday, August 22, 2017 (Wednesday August 23rd in Asia and Australia)
Agenda: Burgeoning Role of Python for Earth Observation Data Analysis
- Syed Rizvi (Open Data Cube) discusses the use of recently developed Open Data Cube Jupyter notebooks for a water classification application that allowed developers to parse their code into blocks which can be run independently of each other, with variables stored in the background, saving vast amounts of time.
- Rich Signell (USGS) discusses how Jupyter Notebooks have been used by the US IOOS (Integrated Ocean Observing System) to do manual skill assessment of over 20 forecast models for over 1000 sensors by building standards-based Python code that uses catalog search, standard web data service access, custom skill metric calculation and interactive display of results.
- Alber Sanchez (INPE) discusses how Python is used in a web service that reduces the gap between data and analysis for EO scientists. He will present how to retrieve time series of vegetation indexes of the Amazon forest, and how to filter these data.
- Open Data Cube Jupyter Notebooks
- Automating Model Skill Assessment with Python
- Python Used in a Web Service
Webinar 2 – Data Cubes for Large Scale Data Analytics
Date: Monday, June 19, 2017.
Description: Recent work by WGISS members has been fleshing out the concept of Data Cubes to enable analysis of large Earth Observation data sets. Please join us as Rob Woodcock of CSIRO (Australia) and Brian Killough of the CEOS System Engineering Office provide an introduction to Data Cubes. Rob will set the stage for Data Cubes with user needs, key features and basic high-level architecture, followed by Brian to talk about some more of the inner workings of Data Cubes.
Webinar 1 – Relevancy Ranking of Data Search Results
Date: Tuesday, March 14, 2017
Time: 11:30 UTC (7:30am US EDT) — Find your local time by clicking this link.
As CEOS Earth Observations grow in both quantity and variety, users face increasing challenges in finding the most appropriate data for their use. Ranking data search results by their expected relevance for the user is potentially one of the most powerful ways to help users quickly zero in on the best data for their purpose. This webinar will look at some of the techniques being used within Earth Observation data search tools, followed by a discussion of possible future directions in relevancy ranking.