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---
title: "Democratizing Access to Education Data"
subtitle: "The Urban Institute's Education Data Portal"
author: "Erika Tyagi"
format:
revealjs:
menu: false
embed-resources: true
theme: urbn.scss
logo: images/urban-institute-logo-2.png
footer: <https://educationdata.urban.org>
include-after-body: format-title-page.html
title-slide-attributes:
data-background-image: images/urban-institute-logo-1.png,images/educationdata-hex.png
data-background-size: 25%,15%
data-background-position: 3% 85%,97% 84%
---
## The Education Data Portal bridges the gap between **<span style="color:#1696d2;">data availability</span>** and **<span style="color:#1696d2;">data accessibility</span>**.
::: {.incremental}
1. What do I mean by the availability-accessibility gap?
2. How does the portal bridge this gap so effectively?
3. Why does bridging this gap matter?
:::
## The Education Data Portal
::: columns
::: {.column width="36%"}
:::
::: {.column width="64%"}
::: {style="font-size: 78%"}
* **What?** A freely available **<span style="color:#1696d2;">one-stop-shop</span>** <br> for 100+ datasets released by government agencies and other institutions on schools, districts, and colleges in the U.S.
::: {.fragment fragment-index=1}
* **How?** **<span style="color:#1696d2;">Harmonized</span>** to account for changes <br> to data and file structures over time
:::
::: {.fragment fragment-index=2}
* **Why?** To make it easier for both **<span style="color:#1696d2;">technical</span>** and <br> **<span style="color:#1696d2;">non-technical users</span>** to look at trends over time and combine data from different sources
:::
:::
:::
:::
---
## What do I mean by the availability-accessibility gap?
::: {style="font-size: 90%"}
**Example**: How has tuition at my alma mater risen over my lifetime?
:::
::: columns
::: {.column width="50%"}
::: {.fragment fragment-index=1}
{height=300 fig-align="center"}
:::
:::
::: {.column width="50%"}
::: {.fragment fragment-index=2}
{height=300 fig-align="left"}
:::
:::
:::
## **<span style="color:#1696d2;">Without</span>** the Education Data Portal...
::: {style="font-size: 90%"}
**Example**: How has tuition at my alma mater risen over my lifetime?
:::
. . .
{.absolute top=125 left=420 height="220"}
## **<span style="color:#1696d2;">Without</span>** the Education Data Portal...
::: {style="font-size: 90%"}
**Example**: How has tuition at my alma mater risen over my lifetime?
:::
::: {style="font-size: 60%"}
* Find the agency collecting the data
:::
{.absolute top=125 left=420 height="220"}
## **<span style="color:#1696d2;">Without</span>** the Education Data Portal...
::: {style="font-size: 90%"}
**Example**: How has tuition at my alma mater risen over my lifetime?
:::
::: {style="font-size: 60%"}
* Find the agency collecting the data
* Read the data documentation
:::
{.absolute top=125 left=420 height="220"}
## **<span style="color:#1696d2;">Without</span>** the Education Data Portal...
::: {style="font-size: 90%"}
**Example**: How has tuition at my alma mater risen over my lifetime?
:::
::: {style="font-size: 60%"}
* Find the agency collecting the data
* Read the data documentation
* Download data files for each year
:::
{.absolute top=125 left=420 height="220"}
## **<span style="color:#1696d2;">Without</span>** the Education Data Portal...
::: {style="font-size: 90%"}
**Example**: How has tuition at my alma mater risen over my lifetime?
:::
::: {style="font-size: 60%"}
* Find the agency collecting the data
* Read the data documentation
* Download data files for each year
* Load each file into R or Python
:::
{.absolute top=125 left=420 height="220"}
## **<span style="color:#1696d2;">Without</span>** the Education Data Portal...
::: {style="font-size: 90%"}
**Example**: How has tuition at my alma mater risen over my lifetime?
:::
::: {style="font-size: 60%"}
* Find the agency collecting the data
* Read the data documentation
* Download data files for each year
* Load each file into R or Python
* Notice anomalies in the data
:::
{.absolute top=125 left=420 height="220"}
## **<span style="color:#1696d2;">Without</span>** the Education Data Portal...
::: {style="font-size: 90%"}
**Example**: How has tuition at my alma mater risen over my lifetime?
:::
::: {style="font-size: 60%"}
* Find the agency collecting the data
* Read the data documentation
* Download data files for each year
* Load each file into R or Python
* Notice anomalies in the data
* Re-read the data documentation
:::
{.absolute top=125 left=420 height="220"}
## **<span style="color:#1696d2;">Without</span>** the Education Data Portal...
::: {style="font-size: 90%"}
**Example**: How has tuition at my alma mater risen over my lifetime?
:::
::: {style="font-size: 60%"}
* Find the agency collecting the data
* Read the data documentation
* Download data files for each year
* Load each file into R or Python
* Notice anomalies in the data
* Re-read the data documentation
* Update the code per the documentation
:::
{.absolute top=125 left=420 height="220"}
## **<span style="color:#1696d2;">Without</span>** the Education Data Portal...
::: {style="font-size: 90%"}
**Example**: How has tuition at my alma mater risen over my lifetime?
:::
::: {style="font-size: 60%"}
* Find the agency collecting the data
* Read the data documentation
* Download data files for each year
* Load each file into R or Python
* Notice anomalies in the data
* Re-read the data documentation
* Update the code per the documentation
* Remember to repeat the process again next year
:::
{.absolute top=125 left=420 height="220"}
## **<span style="color:#1696d2;">Without</span>** the Education Data Portal...
::: {style="font-size: 90%"}
**Example**: How has tuition at my alma mater risen over my lifetime?
:::
::: {style="font-size: 60%"}
* Find the agency collecting the data
* Read the data documentation
* Download data files for each year
* Load each file into R or Python
* Notice anomalies in the data
* Re-read the data documentation
* Update the code per the documentation
* Remember to repeat the process again next year
* (And hope nothing changes)
:::
{.absolute top=125 left=420 height="220"}
## **<span style="color:#1696d2;">Without</span>** the Education Data Portal...
::: {style="font-size: 90%"}
**Example**: How has tuition at my alma mater risen over my lifetime?
:::
::: {style="font-size: 60%; color: #9d9d9d"}
* Find the agency collecting the data
* Read the data documentation
* Download data files for each year
* Load each file into R or Python
* Notice anomalies in the data
* Re-read the data documentation
* Update the code per the documentation
* Remember to repeat the process again next year
* (And hope nothing changes)
:::
{.absolute top=125 left=420 height="220"}
**<span style="color:#1696d2;">This is tedious, error-prone, and not fun.</span>**
## Using the portal **<span style="color:#1696d2;">R package</span>**...
::: {style="font-size: 90%"}
**Example**: How has tuition at my alma mater risen over my lifetime?
:::
. . .
::: columns
::: {.column width="55%"}
```{.r code-line-numbers="4-13"}
library(educationdata)
# Get data
data <- get_education_data(
level = "college-university",
source = "ipeds",
topic = "academic-year-tuition",
filters = list(
year = c(1990:2020),
unitid = "173258",
tuition_type = "4"
)
)
# Plot data
data %>%
ggplot(aes(x = year, y = tuition_fees_ft)) +
geom_line()
```
:::
::: {.column width="45%"}
{.absolute top=200 left=580 width="500"}
:::
:::
::: {style="font-size: 65%; color: #696969"}
The R package is available on CRAN.
:::
---
## Using the portal **<span style="color:#1696d2;">Python package</span>**...
::: {style="font-size: 90%"}
**Example**: How has tuition at my alma mater risen over my lifetime?
:::
::: columns
::: {.column width="55%"}
```{.python code-line-numbers="4-13"}
import educationdata
# Get data
data = get_education_data(
level = "college-university",
source = "ipeds",
topic = "academic-year-tuition",
filters = {
"year": range(1990, 2020),
"unitid": "173258",
"tuition_type": "4"
}
)
# Plot data
data.plot.line(
x = "year", y = "tuition_fees_ft"
)
```
:::
::: {.column width="45%"}
{.absolute top=200 left=580 width="500"}
:::
:::
::: {style="font-size: 65%; color: #696969"}
The Python package is not yet publicly available.
:::
---
## Using the portal **<span style="color:#1696d2;">Stata package</span>**...
::: {style="font-size: 90%"}
**Example**: How has tuition at my alma mater risen over my lifetime?
:::
::: columns
::: {.column width="55%"}
```{.code code-line-numbers="2-7"}
* Get data
educationdata using ///
"college ipeds academic-year-tuition", sub( ///
year=1990/2020 ///
unitid=173258 ///
tuition_type=4 ///
)
* Plot data
twoway (line tuition_fees_ft year)
```
:::
::: {.column width="45%"}
{.absolute top=200 left=600 width="480"}
:::
:::
::: {style="font-size: 65%; color: #696969"}
The Stata package is available on SSC.
:::
---
## Using the portal **<span style="color:#1696d2;">Data Explorer</span>**
::: {style="font-size: 90%"}
**Example**: How has tuition at my alma mater risen over my lifetime?
:::
::: columns
::: {.column width="55%"}
{.absolute top=130 left=0 width="560"}
:::
::: {.column width="45%"}
{.absolute top=200 left=600 width="480"}
:::
:::
## How does the portal bridge this gap so effectively?
. . .
1. By focusing on the **<span style="color:#1696d2;">underlying API</span>**
2. By focusing on **<span style="color:#1696d2;">data documentation</span>**
## The underlying API
Provides **<span style="color:#1696d2;">the foundation</span>** of the portal
::: columns
::: {.column width="40%"}
{.absolute top=160 left=20 width="350"}
:::
::: {.column width="60%"}
::: {.incremental}
* 100+ data endpoints <br> (***with*** the data)
* 12+ metadata endpoints <br> (***about*** the data)
* All other tools, packages, and documentation are built from these endpoints
:::
:::
:::
## Data documentation
Considered a **<span style="color:#1696d2;">first-order feature</span>** of the portal
::: columns
::: {.column width="40%"}
{.absolute top=160 left=20 width="400"}
:::
::: {.column width="60%"}
::: {.incremental}
* Written for ***both*** <br> humans and machines
* Provides the user with <br> details ***on demand***
:::
:::
:::
## Data documentation {.nostretch}
Written for ***both*** humans and machines
{width="55%"}
## Data documentation
Written for ***both*** humans and machines
::: columns
::: {.column width="35%"}
{width="100%"}
:::
::: {.column width="65%"}
```{.code}
{
"results": [
{
"variable": "urban_centric_locale",
"label": "Degree of urbanization (urban-centric locale)",
"format": "urban_centric_locale",
"data_type": "integer",
"values": "{
1: '1 - Large city',
2: '2 - Midsize city',
3: '3 - Urban fringe of large city',
4: '4 - Urban fringe of midsize city',
[...]
}
}
]
}
```
:::
:::
::: {style="font-size: 55%; color: #696969"}
https://educationdata.urban.org/api/v1/api-variables/?<span style="color:#003B4F;">variable=urban_centric_locale</span>
:::
## Data documentation {.nostretch}
Provides the user with details ***on demand***
::: columns
::: {.column width="50%"}
{width="85%"}
:::
::: {.column width="50%"}
::: {.fragment fragment-index=1}
{width="85%"}
:::
:::
:::
## How does the portal bridge this gap so effectively?
::: {style="font-size: 90%;"}
By focusing on the **underlying API** and **data documentation**... through collaboration with **<span style="color:#1696d2;">education</span>** and **<span style="color:#1696d2;">technology**</span> experts
:::
::: columns
::: {.column width="33%"}
{width="220" fig-align="right"}
:::
::: {.column width="33%"}
{.absolute top=285 left=400 width="200"}
:::
::: {.column width="33%"}
{width="210" fig-align="left"}
:::
:::
::: {style="font-size: 55%; color: #696969"}
* Education contributors: Erica Blom, Jay Carter, Leonardo Restrepo
* Technology contributors: Ben Chartoff, David D'Orio, Graham MacDonald, Kyle Ueyama, and Vivian Zheng
:::
## Why does bridging this gap matter?
. . .
Different people ask different questions.
## Why does bridging this gap matter?
Different people ask different questions.
{width="620"}
{.absolute top=140 left=710 width="250"}
{.absolute top=380 left=710 width="250"}
## Why does bridging this gap matter?
Different people ask different questions.
{width="500"}
{.absolute top=160 left=690 width="270"}
{.absolute top=350 left=700 width="250"}
## Why does bridging this gap matter?
Different people ask different questions.
{width="520"}
{.absolute top=160 left=700 width="250"}
{.absolute top=410 left=690 width="270"}
## Each month, thousands of users ask questions through the portal {.nostretch}
{width="95%" fig-align="left"}
## Why does bridging this gap matter?
::: columns
::: {.column width="55%"}
::: {style="font-size: 120%"}
By unlocking data for more people, we can allow more questions to find **<span style="color:#1696d2;">evidence-based answers</span>** that **<span style="color:#1696d2;">drive impact</span>**.
:::
:::
::: {.column width="45%"}
:::
:::
## Get in touch
::: columns
::: {.column width="50%"}
::: {style="font-size: 85%;"}
* **Access the portal**
<https://educationdata.urban.org>
* **Email the portal**
* **Email me**
:::
:::
::: {.column width="50%"}
{.absolute top=40 left=560 width="430"}
:::
:::
---