In this world nothing can be said to be certain, except death and taxonomies. Joe (of course, a take on Ben Franklin’s famous quote)

The Dashboard, a quick recap (Water Level, Hydro-climate Dashboards)

The way I saw it (Jan 2012) Quick web visualization of Laurentian Great Lakes Water Levels and Forecasts (and other related data) Help bring perspective to current level data Help assess the accuracy/skill of lab forecasts

The way I have seen it Evolved pretty rapidly into a data dump and display (thru end of 2012) Meaning, I had to take another look at my approach to this.

Approaches? Version 1 (GLWLD, GLHCD Beta) – Code is a complex and twisted list of manually inputted data and interactions with it – or, in other words, awful Version 2 (GLHCD) – January-March 2013 – Data is inventoried, and the inventory is read – Data is organized in the inventory by lake and 2 levels of categories – Each data set is handled in an algorithm, treated pretty much the same way. – Display and interaction handling is uniform, not a maze.

Approaches? Version 1 (GLWLD, GLHCD Beta) – For every data set, a set of commands and potentially user interface elements had to be written Version 2 (GLHCD) – January-March 2013 – For every data set, a line in the inventory is added – The commands I would have written are now expressed as an automatic decision tree (essentially)

Now what? Collision course: Simple Web Display Model Skill/Accuracy Assessment Data Dump and Display Need/Desire to improve models How am I going to handle all this? What’s available to do this? What’s not? Take an inventory Organize inventory of data

Lake/Region Superior MI-Huron St. Clair Erie Ontario All Other Status Operational Research Variable Water Levels Forecasts Reconstructions (Paleo, other) Climate Meteorology Ice Clouds Fluid/Hydrologic Input/Output More... (Algae, D.Oxy, chlorophyll, microsystin...) Source NOAA NOAA/NOS NCDC USACE Coastwatch Quinn et al. Hayhoe et al. Lofgren et al. MacKay and Seglenieks Wiles et al. Baedke and Thompson Johnston et al. Etc. Temporal Scale Minutely Hourly Daily Weekly Monthly Annual Multi-year Multi-decadal Multi-centurial Multi-millenial Union of All Laurentian Great Lakes (2D) Time Series Data Sets (produced and not produced)

Taxonomies Are Useful Helps consolidate related data Helps organize it in a logical way Acts as a map – What’s here? – What’s not? Where are our gaps? – Where can we go? What could we do? Can provide a basis for metadata (in particular, XML based metadata)

In short… We’re not lost at sea.

What does this have to do with the dashboard again? This taxonomy is a useful byproduct of recent developments of the dashboard. The theoretical basis is pretty well set in stone – Taxonomy → Hierarchy → Tree – Trees are well known Abstract Data Types in computer science – Tree manifests itself in dashboard code as an object of objects (of objects) – Taxonomy discovered in reverse order: Objects → Tree → Hierarchy → Taxonomy

Lake/Region Superior MI-Huron St. Clair Erie Ontario All Other Status Operational Research Variable Water Levels Forecasts Reconstructions (Paleo, other) Climate Meteorology Ice Clouds Fluid/Hydrologic Input/Output More... (Algae, D.Oxy, chlorophyll, microsystin...) Source NOAA NOAA/NOS NCDC USACE Coastwatch Quinn et al. Hayhoe et al. Lofgren et al. MacKay and Seglenieks Wiles et al. Baedke and Thompson Johnston et al. Etc. Temporal Scale Minutely Hourly Daily Weekly Monthly Annual Multi-year Multi-decadal Multi-centurial Multi-millenial Union of All Laurentian Great Lakes (2D) Time Series Data Sets (produced and not produced) ChartsTabsGeneral IdentifiersCategories

Now let’s get to paper #2 We’ve already done Environmental Modeling and Software Considered: – Water Resources Research – Journal of Hydrology – Environmental Science and Technology – Journal of Great Lakes Research (default)

Water Resources Research Water Resources Research is an interdisciplinary journal that publishes original research in the natural and social sciences of water. This includes the role of water in the physical, chemical, biological, and ecological sciences; public health; and related social and policy sciences. It encompasses methodological development of observational, experimental, theoretical, analytical, numerical, and data driven approaches that advance the science of water and its management. Submissions are evaluated for their novelty, accuracy, significance, and broader implications of the findings.

Water Resources Research My conclusion: not the best fit, but certainly nothing to immediately drop from consideration.

Journal of Hydrology The Journal of Hydrology publishes original research papers and comprehensive reviews in all the subfields of the hydrological sciences including water based management and policy issues that impact on economics and society. These comprise, but are not limited to the physical, chemical, biogeochemical, stochastic and systems aspects of surface and groundwater hydrology, hydrometeorology and hydrogeology.

Journal of Hydrology Relevant topics incorporating the insights and methodologies of disciplines such as climatology, water resource systems, hydraulics, agrohydrology, geomorphology, soil science, instrumentation and remote sensing, civil and environmental engineering are included. Social science perspectives on hydrological problems such as resource and ecological economics, environmental sociology, psychology and behavioural science, management and policy analysis are also invited. Multi-and interdisciplinary analyses of hydrological problems are within scope.

Journal of Hydrology My conclusion: It’d be a stretch… so it’s a no.

Environmental Science and Tech News and features section The news and features section of ES&T presents objective reports and analyses of the major advances, trends, and challenges in environmental science, technology, and policy for a diverse professional audience. It aims to promote interdisciplinary understanding in the environmental field. Although we welcome technical content in these articles, it is not a proper forum to present new data. Instead, the discussion should be based on data found in the peer- reviewed literature.

Environmental Science and Tech Research section ES&T seeks to publish papers that are particularly significant and original. The types of papers published in the research section of ES&T are research article, policy analysis, critical review, correspondence (comment/rebuttal), and correction/addition (errata). Manuscripts are initially reviewed by the editor and, if appropriate, by other scientists who assess the significance, originality, and validity of the work, as well as its appropriateness for publication. The Editor- in-Chief and Associate Editors, listed in the masthead, are responsible for all material published in ES&T.

Environmental Science and Tech My conclusion: we could do this much more easily than WRR

Journal of Great Lakes Research This is the default. It’s multi-disciplinary, it’s for all Great Lakes, and it’s kinda hard not to give it a few thoughts.

Journal Picking 1.Journal of Great Lakes Research (default) 2.Environmental Science and Technology 3.Water Resources Research 4.Journal of Hydrology Powerpoint deck done! Discussion of this and the initial outline next

Starter Questions: Why shouldn’t we do this paper this way? Would this paper interfere with an ongoing conversation on data management, or would it add to it? How? Why? Why shouldn’t this paper be in a Great Lakes Related / Hydrology Journal? (Organizational structures have been around for a looooong time, and would be nothing new or novel in an information / library science journal)