Refine the Results↓

Current Search Limits:
Data

Data Visualization as Rorschach Test


Posted: Feb 21 2016 by Kim Kastens
Topics: Data

In a recent post, I discussed the work of Graham Turner, who has tested model outcomes from the Limits to Growth effort against empirical data. Turner's comparison shows that the business-as-usual (aka "standard run") model from Limits to Growth seems to be tracking pretty well against the data on measures related to economy, environment, and population. Although model and data have been agreeing pretty well so far, the hard part of the forecast hasn't yet been tested. Between approximately 2010 and 2040, the model predicts that Industrial_output_per_capita, Services_per_capita, and Food_per_capita will stop rising and start falling, followed by similar reversals in Population and Pollution. Meanwhile, Death_rate has been falling and is forecast to turn around and start rising.

One of these inflection points seems to be beginning to show up in the data: Turner's graph shows that global Death_rate has flattened out and begun to rise ever so slightly. Why might this be? More

Comments (2)

What precursor understandings underlie the ability to make meaning from data?


Posted: Jun 6 2013 by Kim Kastens
Topics: Temporal Thinking, Research Idea, Interpretation/Inference, Metacognition, Data

I've been thinking a lot recently about how scientists and students make meaning from data, spurred in part by the Earth Cube education end-users workshop. Among other things, I've been trying to understand what kinds of deeply foundational understandings might be constructed by young children through unstructured observation using the human senses, and then later re-purposed as they begin to work with data.

Here is one candidate: Future data users need to understand that:

  • events in the world leave traces, and
  • by looking the traces, we can make inferences about the events.
  • More

    Comments (1)

Is the Fourth Paradigm Really New?


Posted: Oct 20 2012 by Kim Kastens
Topics: Community, Spatial Thinking, Interpretation/Inference, Data, History of Geosciences

Cover of Fourth Paradigm I have a long-standing interest in the use of data in education, so I've been reading with interest several articles and a book concerned with the so-called "Fourth Paradigm" of science, in which insights are wrested from vast troves of existing data. The Fourth Paradigm is envisioned as a new method of pushing forward the frontiers of knowledge, enabled by new technologies for gathering, manipulating, analyzing and displaying data. The term seems to have originated with Jim Gray, a Technical Fellow and visionary at Microsoft's eScience group, who was lost at sea in 2007. The first three paradigms, in this view, would be empirical observation and experimentation, analytical or theoretical approaches, and computational science or simulation. Earth and Environmental Sciences are well represented in the book, with essays on data-rich ecological science, ocean science, and space science.

I am finding these readings very stimulating and worthwhile. But I question whether this way of making meaning from the complexity of nature is really so new. More

Comments (2)

A more nuanced view of Concept-driven versus Data-driven visualizations


Posted: Mar 12 2012 by Kim Kastens
Topics: Interpretation/Inference, Data, Perception/Observation, Spatial Thinking

In several previous posts, I explored how Clark & Weibe's (2000 ) idea of data-driven versus concept-driven visualizations plays out in geosciences and how this distinction could be important as we help students learn to learn from visualizations. This semester, in my course on "Teaching & Learning Concepts in Earth Sciences," students found and documented visualizations that afford insights via spatial thinking about a topic they are working on for a semester long project. Applying the idea of data-driven versus concept-driven visualizations to this image collection surfaced several additional nuances to the categorization schema. More

Turning Nature Into Categories


Posted: Feb 13 2012 by Kim Kastens
Topics: Data, Metacognition, Interpretation/Inference, Perception/Observation

Two years ago in this space, I wrote about "Turning Nature into Numbers," humanity's accomplishment of developing instruments and methodologies that can turn the fleeting qualitative impressions that we have of our surroundings into quantitative values--numbers--which can be readily stored, shared, transmitted and compared.

Numbers are great, but it seems to me that for developing an opinion or making a decision, humans often want categories rather than numbers. More

RSS