Earth Science Data Analytics/2014-05-22 Telecon
SDA Telecom notes – 5/22/14
Known Attendees:
To be Provided
Agenda:
1 – Steve Kempler - Recap of last telecon
2 – Tiffany Matthews – Describe/Demonstrate UV CAT and ClimatePipes visualization analytics tools
Ref: https://www.youtube.com/watch?v=BFN0RzN1hSE&feature=em-share_video_user
3 – Tiffany - To lead discussion started last week: 'enabling users to leverage data to observe more phenomena than what can be identified when studying an average'.
Tiffany will continue discussion with her presentation entitled: " Atmospheric Science Data Center Sample Data Analytics Use Cases."
4 – Steve - Present new Cluster Information Sharing Websites
Earth Science Data Analytics Discussion Forum - http://wiki.esipfed.org/index.php/Earth_Science_Data_Analytics/Discussion_Forum
Use Case Collection webpage - http://wiki.esipfed.org/index.php/Use_Case_Collection
Data Analytics Tools/Techniques Collection webpage - http://wiki.esipfed.org/index.php/Analytics_Tools
Presentations:
Notes:
Today, Tiffany provided a demonstration of UV CAT, a visualization analytics tool. Tiffany followed with a continuation of last month's discussion on different types of data analytics. Steve followed, showing the ESDA Use Case Gathering website, and Data Analytics Tools/Techniques Inventory website.
Questions from Tiffany's UV CAT demonstration
- Is UV CAT a useful analytics tool for our use cases?
- What data prpa
Tiffany next led a discussion to answer the following questions:
1. What are your most time consuming data tasks that can leverage analytics?
2. Identify and discuss different types of analytics
3. What kind of data analytics is needed for specific use cases?
4. Identify tools and technologies that address different types of analytics
(Of course,) We did not get through all questions, but after a very good discussion, we decided to post the questions on the 'ESDA discussion Forum' (http://wiki.esipfed.org/index.php/Earth_Science_Data_Analytics/Discussion_Forum) and continue discussion on the forum (I encourage all to participate with questions, answers, and experience)
Discussion highlights (thus far), focusing on the different types of data analytics:
- Getting data, in particular, meaningful data is very time consuming
- Metadata is very useful in accessing and understanding data to determine its meaningfulness
- Using semantics to acquire information in metadata needs to be further pursued
- Making data usable in system (i.e., analytics tool, decision support, etc.) is time consuming; Automating process is sometimes difficult
- Types of analytics needed: Provider - Analytics to make data more usable
- Types of analytics needed: Provider/User - For data integration; Combine data from 2 or more data sources; what isn the best way to do this (<-- end goal dependent)
- This is the figure (I believe) Rudy was alluding to, when referring to Big Data Value Chain:
- Using analytics to combine data tools, and be able to reverse out of analytics to get back to the original data
- Tools: Needed for identifying new information from a combination of existing data
- Tools: For linking data to causes (thus working backwards: result --> cause --> data)
- Tools: Data fusion - for example, for environmental data analysis
- But…who should apply data analytics?
Producers (e.g., science teams), the data experts; Providers (e.g., data centers), who know how to build infrastructure/framework to support advancing data analysis; Users (e.g., researchers, decision support), who know exactly what their goals are
- An answer: All… but the key, is to make sure knowledge, experience, and needs, are shared amongst all the groupings.
Discussion continued on Discussion Forum: http://wiki.esipfed.org/index.php/Earth_Science_Data_Analytics/Discussion_Forum
Next Telecon:
- June 26, 3:00 EST
- Agenda (as of now)
- Listen and Learn - We will have 2 guest speakers to discuss their Analytics activities
- ESDA Activities - Use Case Collection webpage - http://wiki.esipfed.org/index.php/Use_Case_Collection
- Preparation for Frisco
