9 Matching Annotations
  1. Feb 2021
    1. January 11, 2021

      Click here for a new blog post from Greg Snow on a useful visual data exploration tool.

  2. Oct 2020
    1. (d) All calculations shown in this appendix shall be implemented on a site-level basis. Site level concentration data shall be processed as follows: (1) The default dataset for PM2.5 mass concentrations for a site shall consist of the measured concentrations recorded from the designated primary monitor(s). All daily values produced by the primary monitor are considered part of the site record; this includes all creditable samples and all extra samples. (2) Data for the primary monitors shall be augmented as much as possible with data from collocated monitors. If a valid daily value is not produced by the primary monitor for a particular day (scheduled or otherwise), but a value is available from a collocated monitor, then that collocated value shall be considered part of the combined site data record. If more than one collocated daily value is available, the average of those valid collocated values shall be used as the daily value. The data record resulting from this procedure is referred to as the “combined site data record.”
      1. Calculate mean of all collocated NON-primary monitors' values per day
      2. Coalesce primary monitor value with this calculated mean
    1. 1.1. Monitors For the purposes of AQS, a monitor does not refer to a specific piece of equipment. Instead, it reflects that a given pollutant (or other parameter) is being measured at a given site. Identified by: The site (state + county + site number) where the monitor is located AND The pollutant code AND POC – Parameter Occurrence Code. Used to uniquely identify a monitor if there is more than one device measuring the same pollutant at the same site. For example monitor IDs are usually written in the following way: SS-CCC-NNNN-PPPPP-Q where SS is the State FIPS code, CCC is the County FIPS code, and NNNN is the Site Number within the county (leading zeroes are always included for these fields), PPPPP is the AQS 5-digit parameter code, and Q is the POC. For example: 01-089-0014-44201-2 is Alabama, Madison County, Site Number 14, ozone monitor, POC 2.

      How monitors (specific measures of specific criteria) are identified in AQS data.

  3. Sep 2020
    1. The RDF model encodes data in the form ofsubject,predicate,objecttriples. The subjectand object of a triple are both URIs that each identify a resource, or a URI and a stringliteral respectively. The predicate specifies how the subject and object are related, and isalso represented by a URI.

      Basic description of Resource Description Framework

    1. separate the workflow description from its execution.

      Separating a workflow description from its execution is an important aspect of reproducibility.

    1. We have a universal goalfor our computational classes to get students to do something interesting with data (e.g.,visualization) within the first ten minutes of the first class.

      Entry goal for data science instruction.

    Annotators

    1. In order to be useful during teaching, a formative assessment has to be quick to administer (so that it doesn’t break the flow of the lesson) and have an unambiguous correct answer (so that it can be used with groups). The most widely used kind of formative assessment is probably the multiple choice question (MCQ). A lot of teachers have a low opinion of them, but when they are designed well, they can reveal much more than just whether someone knows specific facts. For example, suppose you are teaching children how to do multi-digit addition [Ojos2015] and you give them this MCQ: What is 37 + 15? a) 52 b) 42 c) 412 d) 43 The correct answer is 52, but the other answers provide valuable insights: If the child chooses 42, she has no understanding of what “carrying” means. (She might well write 12 as the answers to 7+5, then overwrite the 1 with the 4 she gets from 3+1.) If she chooses 412, she is treating each column of numbers as a separate problem. This is still wrong, but it’s wrong for a different reason. If she chooses 43 then she knows she has to carry the 1 but is carrying it back into the column it came from. Again, this is a different mistake, and requires a different clarifying explanation from the teacher.

      Motivating example of using multiple choice to assess mental models, more than simply evaluating presence or absence of knowledge.

  4. May 2016
    1. “Almost any experience is improved by paying full attention to it,” Ms. McGonigal said. “Attention is one way your brain decides, ‘Is this interesting? Is this worthwhile? Is this fun?’ ”It’s the reason television shows we tweet through feel tiresome and books we pick up and put down and pick up again never seem to end. The more we allow ourselves to be distracted from a particular activity, the more we feel the need to be distracted. Paying attention pays dividends
  5. Oct 2015
    1. The thought that millions of years have been required for the creation goes far in helping us appreciate the uniqueness and preciousness of our earth. As we look at nature, we are looking into deep creation through an eye fashioned out of elements gleaned from the remains of burned-out stars. Not a nature fashioned by the quick wave of a hand, but one that has required about 13.7 billion years to cultivate (pg. 163).

      Beautiful thoughts from Steven Peck on how appreciating evolution enriches spirituality.