1. CWIC Metrics Eugene G. Yu (gyu@gmu.edu)gyu@gmu.edu Lingjun Kang (lkang3@masonlive.gmu.edu)lkang3@masonlive.gmu.edu Archie Warnock (warnock@awcubed.com)warnock@awcubed.com

2. Outline CWIC Metrics – Current architecture – Current status CWIC Metrics Development Plans – New capabilities – Possible extension to meet the new capabilities

3. CWIC Metrics URLs – CSW - http://cwic.wgiss.ceos.org/cwicmetrics/http://cwic.wgiss.ceos.org/cwicmetrics/ – OpenSearch - http://cwic.wgiss.ceos.org/cwicosmetrics/http://cwic.wgiss.ceos.org/cwicosmetrics/ What are recorded? – Dataset – Connector What are reported? – By dataset – By pre-defined connector (new connector needs to be added by changing the code and re-calculation) – Reports are dynamic and interactive

4. CWIC Metrics - Architecture Logging appended into a single file Recorded only dataset and connector File-based summary – Directly added to the json file – Revisit the record of the same period would be resulted in double counting Modifications would lead to recalculation from the very beginning Connectors are pre-set to be summarized – Hard-code the list of connectors to be summarized

5. CWIC Metrics - status Dataset and their beginning dates – List of current datasets (to be summarized and listed) What can be seen? – A screen capture showing the reports By dataset By connector

6. CWIC Metrics – new capabilities (1/2) New capabilities – Finer details for metrics collection Basic unit up to dataset Added details of information – Data originator – Data distributor – Projects – Bases for metric summary dataset (basic unit – lowest level of metric data collection) Data centers (Distributor? Originator?) Projects

7. CWIC Metrics – new capabilities (2/2) New capabilities (continued) – Reflecting hierarchical ownership Data – Aggregation (hierarchical structures) Aggregate by connector Aggregate by data centers Aggregate by project – Any other aggregation option?

8. CWIC Metrics – Architecture (updating) To support the new capabilities Necessary changes – Restructure the metrics logging Adding required info – Finer details – Terminology alignment Roll-over by dates (reducing the file size) – Collected base metrics management DBMS or file-based database (e.g. MongoDB) – Aggregation implementation SQL-based aggregation (e.g. Views) Output JSON for presentation (e.g. modular JSON converter from Views or Web Services to populate the JavaScript module) Combined CSW/OpenSearch metrics