An expandable web-based platform for visually analyzing basin-scale hydro-climate time series data

Growing demand from the general public for centralized points of data access and analytics tools coincides with similar, well-documented needs of regional and international hydrology research and resource management communities. To address this need within the Laurentian Great Lakes region, we introduce the Great Lakes Dashboard (GLD), a dynamic web data visualization platform that brings multiple time series data sets together for visual analysis and download. The platform's adaptable, robust, and expandable Time Series Core Object Model (GLD-TSCOM) separates the growing complexity and size of Great Lakes data sets from the web application interface. Although the GLD-TSCOM is currently applied exclusively to Great Lakes data sets, the concepts and methods discussed here can be applied in other geographical and topical areas of interest. Solution fulfills documented need in hydrological and resource management communities.Employed visualization paradigm permits easy visual analysis of Great Lakes Data.Data are downloadable for further analysis; Information about data is in application.Novel development model permits significant data and application feature expansion.

[1]  J. Houghton,et al.  Climate Change 2013 - The Physical Science Basis: Working Group I Contribution to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change , 2014 .

[2]  Thorsten Wagener,et al.  Ten guidelines for effective data visualization in scientific publications , 2011, Environ. Model. Softw..

[3]  M. Black,et al.  Hydrologic variability and the application of Index of Biotic Integrity metrics to wetlands: A great lakes evaluation , 2002, Wetlands.

[4]  C. M. Sperberg-McQueen,et al.  Extensible Markup Language (XML) , 1997, World Wide Web J..

[5]  Opher Etzion,et al.  Event Processing in Action , 2010 .

[6]  John D. Lenters,et al.  A regime shift in Lake Superior ice cover, evaporation, and water temperature following the warm El Niñ winter of 1997–1998 , 2014 .

[7]  Ben Smith AdvancED ActionScript 3.0: Design Patterns , 2011 .

[8]  Andrew D. Gronewold,et al.  Visualizing relationships between hydrology, climate, and water level fluctuations on Earth's largest system of lakes , 2014 .

[9]  Andrew D. Gronewold,et al.  A dynamic graphical interface for visualizing projected, measured, and reconstructed surface water elevations on the earth's largest lakes , 2013, Environ. Model. Softw..

[10]  Tim Bray,et al.  Internet Engineering Task Force (ietf) the Javascript Object Notation (json) Data Interchange Format , 2022 .

[11]  Bala Rajaratnam,et al.  The Extraordinary California Drought of 2013-2014: Character, Context, and the Role of Climate Change , 2014 .

[12]  Craig A. Stow,et al.  Water Loss from the Great Lakes , 2014, Science.

[13]  Jeffery S. Horsburgh,et al.  An integrated system for publishing environmental observations data , 2009, Environ. Model. Softw..

[14]  Lars Marius Garshol,et al.  Metadata? Thesauri? Taxonomies? Topic Maps! Making Sense of it all , 2004, J. Inf. Sci..

[15]  Stephen K. Gill,et al.  Variation of Great Lakes water levels derived from Geosat altimetry , 1994 .

[16]  Mike Pearson,et al.  Visualizing Uncertainty About the Future , 2022 .

[17]  Laura Christopherson,et al.  Water Science Software Institute: Agile and Open Source Scientific Software Development , 2014, Computing in Science & Engineering.

[18]  Daniel Andresen,et al.  A distributed data component for the Open Modeling Interface , 2014, Environ. Model. Softw..

[19]  Thomas H. Johengen,et al.  Working in Freshwater: The Great Lakes Observing System Contributions to Regional and National Observations, Data Infrastructure, and Decision Support , 2010 .

[20]  Sanjay Ghemawat,et al.  MapReduce: Simplified Data Processing on Large Clusters , 2004, OSDI.

[21]  François Bousquet,et al.  Modelling with stakeholders , 2010, Environ. Model. Softw..

[22]  Peter D. Blanken,et al.  Predicting the Net Basin Supply to the Great Lakes with a Hydrometeorological Model , 2012 .

[23]  E Ferguson,et al.  From comparative risk assessment to multi-criteria decision analysis and adaptive management: recent developments and applications. , 2006, Environment international.

[24]  Yehia El-khatib,et al.  Web technologies for environmental Big Data , 2015, Environ. Model. Softw..

[25]  Corinne Le Quéré,et al.  Climate Change 2013: The Physical Science Basis , 2013 .

[26]  A. Ricciardi,et al.  Predicting the identity and impact of future biological invaders: a priority for aquatic resource management , 1998 .

[27]  Yao Liang,et al.  Design of an integrated data retrieval, analysis, and visualization system: Application in the hydrology domain , 2006, Environ. Model. Softw..

[28]  Tommi Mikkonen,et al.  Web Applications – Spaghetti Code for the 21st Century , 2008, 2008 Sixth International Conference on Software Engineering Research, Management and Applications.

[29]  James A. Hendler,et al.  US Government Linked Open Data: Semantic.data.gov , 2012, IEEE Intelligent Systems.

[30]  Ralph Johnson,et al.  design patterns elements of reusable object oriented software , 2019 .

[31]  Anthony J. Jakeman Environmental modelling,software and decision support , 2012 .

[32]  Craig A. Stow,et al.  An appraisal of the Great Lakes advanced hydrologic prediction system , 2011 .

[33]  Jeffery S. Horsburgh,et al.  A relational model for environmental and water resources data , 2008 .

[34]  George Martine,et al.  The new global frontier : urbanization, poverty and environment in the 21st century , 2008 .