Community Data – Vulnerability indices and technical considerations

AERO has announced an upcoming Special Interest Group session “Working with Community Data Sets”.  
This free event will be of interest to those who want to learn more about the approaches and development of vulnerability indices and the practical, technical and utilization issues associated with this work.  The afternoon will feature:

  • three socio demographic models that are used by education researchers in Ontario;
  • discussion of issues related to the 2011 census;
  • presentation of R and QGIS tips and tricks when working with socio demographic data. 

If you are interested in attending or would like more information, send us a quick note and the registration information will be forwarded to you.

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R Summer Institute – Registration Open

Click here for a pdf of the flyer.

R Summer Institute Flyer3

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SAVE THE DATE! – SummR Series – June 23 and 24

The Toronto and Barrie Region MISA PNCs are sponsoring a two day R workshop on June 23 and 24.  A location in Toronto is in the process of being reserved for this event.

This two day workshop is an extension of the “Introduction to R – Towards Reproducible Research” workshops held earlier this school year. Along with an introductory session for those who are new to R (or requiring a refresher), we will also be exploring analysis of common data sets (EQAO, EDI, community level data) and data visualization techniques in R.  With two days to explore R, more time will be available to learn R in the context of your own data set.

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QGIS – Quick Start Tips

Here are a few quick references for getting started with QGIS.  All steps included are based on a 2.2.0 Valmiera installation of QGIS


  • Install the “Table Manager” plugin to modify the attributes table (i.e. field names etc.)
  • Use the Field Calculator to create new fields and transform values from string to text.  this is useful when you only have to change 1 or 2 fields
  • Use a .csvt file to define the data types for each field in a large CSV file.  The .csvt file should only contain 1 row with “String” and “Integer” values used to represent each column in your .csv file.  The .csvt file should be in the same directory as your csv and will be used by QGIS when you join the data to a shape layer.

Managing Projections

Sometimes when you load a shape file the layers won’t line up.  When this occurs either the projection hasn’t been set or it is using a different coordinate system.  Making sure that the projections used for each layer and the project is important and often resolves this:

Checking the projection used for the project: In the lower right corner of the QGIS desktop there is a box labelled “Render”.  Immediately to the right of that there is a small spherical icon – click on this icon

  • In the “Coordinate reference systems of the world”:
    • Scroll down to “projections”
    • Select “NAD 83/UTM zone 17N”

Checking the projection used in each layer:

  • Right click on the layer
  • Click on “Set layer CRS”
  • Select the Projection of interest (in the case of southern Ontario, NAD 83 zone 17 is what I tend to use)
    • Repeat these three steps for each layer that is included in the project

Building a query (selecting by attributes)

Queries in QGIS use the same syntax as SQL:

    • Click on “Layer” in the top menu bar
      • Select “Query” (or CTRL F)
      • Create your query either by typing it directly into the “Provider specific filter expression” or by double clicking on the elements.  Queries usually take the form of “Field”  “Operator” “Value”.  For example  ID > 0

Joining Data (csv) to a shape file

    • Open your shape file (Layer>Add Vector)
    • Open your data file (Layer>Add Vector)
    • Open attribute of your shape file (right click on shape file> Open Attributes)
      • Confirm name of the primary key
      • Close attribute table
    • Open the properties of your shape file (right click on shape file> Properties)
      • Click on “Joins” tab
      • Click + button to add a join
      • Select the .csv file that is to be joined with the shape file
      • Confirm the Join field and Target fields are correct
      • Click on OK or Apply
      • Right click on the shape file and “Save As”

Spatial Joins

    • Open the polygon and point files
    • Click on “Vector” > “Data Management Tools” > “Join Attributes By Location”
      • The “Target Vector” is the shape file that you want the new data attached to (in this case a polygon file)
      • The “Join Layer” is the shape file with the attributes you want copied (in this case the points file)
      • Type in a filename and location for the new files that will be created
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R – Special Education Data Cleaning

Three new scripts have been added to the R resource section:

  • SpecEd_36_ISD_Coding.R
  • SpecEd_G9_ISD_Coding.R
  • SpecEd_OSSLT_FTE_ISD_Coding.R

These files have been developed to support the analysis of achievement or context by Special Education categories.

Each of the scripts takes your ISD file and:

  • recodes the Special Education IEP Types into a single column with each IEP Type labeled.
  • recodes the Special Education IEP Type into a single column by the Ministry categories of exceptionalities ( page A18).
  • creates a new file with the two new recoded variables appended to all the ISD variables.
  • creates a new smaller file with fields of interest (this file is useful in constructing cohort data sets).
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Join us at OERS 2014…

If you are attending the 2014 Ontario Education Research Symposium be sure to stop by the Data User Group table that will be set up for the poster session. It will be a great opportunity to network and get feedback on the topics and issues you would like to see supported and promoted through the Data User Group.

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Second Workshop Scheduled for “Introduction to R – Towards Reproducible Research”

A second “Introduction to R – Towards Reproducible Research” workshop has been scheduled for January 9th, 2014.  The format and material covered will be the same as the December 9th workshop and is intended to provide an additional opportunity to learn about R.  This workshop is presented in collaboration with the Barrie Region and Toronto Region MISA (Managing Information for Student Achievement) PNCs (Professional Network Centres).

As with the previous workshop, it is intended to be a starting point for: those with no experience with R; those who would like an R refresher; those who would like to begin developing reproducible reports.

The morning will consist of demonstrations of the basics of R such as :

• Loading data, recoding variables, merging data files
• Simple analyses, such as frequencies and cross tabulation
• Data visualization

The afternoon will focus on preparing reports in R, including:

• Customizing appearance
• Combining script, analyses and visualizations
• Automating annual reports

If you are interested in attending, please contact Chris Conley:
Conley_Chris at Durham dot edu dot on dot ca

Note: MISA is a provincial initiative in Ontario designed to increase both provincial and local capacity to use data and information for evidence-informed decision-making to improve student achievement.

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