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CT DEEP Long Island Sound Water Quality Data archive Todd Fake University of Connecticut NERACOOS/NECOSP Data Management Workshop, Sept. 26, 2012.

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Presentation on theme: "CT DEEP Long Island Sound Water Quality Data archive Todd Fake University of Connecticut NERACOOS/NECOSP Data Management Workshop, Sept. 26, 2012."— Presentation transcript:

1 CT DEEP Long Island Sound Water Quality Data archive Todd Fake University of Connecticut NERACOOS/NECOSP Data Management Workshop, Sept. 26, 2012

2 LISICOS & CT DEEP Long Island Sound Water Quality Data Development of a sustained capability to observe the Long Island Sound ecosystem and an adequate capability to understand and predict its response to natural and anthropogenic changes. Provide easier access to this long term water quality data Added value to LISICOS research and provide other parties direct access to these data

3 About CT DEEP Long Island Sound Water Quality Data The Connecticut Department of Energy and Environmental Protection (DEEP), on behalf of the Long Island Sound Study estuary program, conducts a Long Island Sound Water Quality Monitoring Program since 1991 October to May, water quality is monitored by collecting samples once a month from 17 sites Bi-weekly hypoxia surveys start in mid-June and end in September with up to 48 stations being sampled during each survey.

4 How we manage our data CT DEEP maintains in-house relational database Periodically this database is ingested into the LISICOS data system using a series of set queries

5 Data Management Successes Allowed researchers to easily access, compare and analyze data Comprehensive analysis of DO duration Analysis of long term trends of nitrate and phosphorous LIS bottom temperature

6 Data Management Challenges Once initial framework was built challenges have been minimal Delay in data transfer – Security and time limitation

7 Take home points Allowing data collectors to leverage existing platforms to visualize and serve information Broadens user base, saves data management time, provided platform to exploit these data


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