Michelle Ho michellemho

Around

From: http://wiki.openstreetmap.org/wiki/Overpass_API#Simple_usage_examples
around allows you to get all nodes near one or more given nodes. For example, to get all nodes that are at most 10 meters around the nodes called Bristol:

<query type="node">
  <has-kv k="name" v="Bristol"/>
</query>
<around radius="10"/>

Title: What defines a neighborhood?

General Topic: Research

General Theme: TBD ("Local, state, and federal agency adoption and use" or "Data science"?)

What defines a neighborhood? We generally think of neighborhoods as geographic areas of similar characteristics. But what set of characteristics and what level of similiarity? What determines where the boundary lines actually gets drawn? Perceptions of where neighborhoods begin and end vary greatly from person to person. Neighborhoods defined from a data point-of-view also differ greatly. This talk presents several statistical techniques on defining neighborhoods from spatial clustering algorithms to origin-destination based approaches, and examines how neighborhood change-over-time can be represented. How a neighborhood gets defined affects residents, real estate, and researchers alike.

Literature Review

"Sales Territory Design: Thirty Years of Modeling and Implementation" Zoltners and Sinha (2005)

Sales Territory Alignment:

"The assignment of accounts and associated selling activities to salespeople and teams"
Also known as sales territory design, assignment, deployment, realignment and districting

Salesforce Structures

Generalist structure: salesperson assigned to specific geographic area

Workflow:

Find population density to each store location to determine "urban-ness" (the 2015 5-year ACS estimate is used)
Also find median income at each store location at birth date and death date. So if a store opened in 2010, the 2010 5-year estimate is used.
If the population density is greater than 5000 people / sq. km., create isochrones of 10 minute walking radius. Else, 10 minutes of driving time.
For each polygon, find total population at time of death date.
Calculate % change in median income from birth to death date.
Expand the table to create an "time interval" table for the time widget
Add both the store location table and expanded time interval table to a map
"Filter by Layer" analysis on the time interval layer, choosing the store location layer as the filter
"Filter by Layer" analysis on the store location layer, choosing the filtered time interval layer as the filter


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	/*
	DEP_EXT_get_competitors
	Return a table of competitors in the same industry of a selected retailer in the underlying source query
	Example: A user has a dataset of retail brands and the industry. In the underlying source query (via a widget),
	a single retailer is selected (ie. Dunkin Donuts). Then, this function will return a table of the competing retailers
	in the coffee industry (ie. Starbucks, Peets, etc.).
	If more than one retailer is selected, then all competitors will be returned.
	So if Dunkin Donuts AND Stop&Shop are selected in the widget, then Starbucks, Peets, Wegmans, Whole Foods, etc. will be
	returned in the table. If two retailers in the same industry are selected, the competitors are returned in the table
	without the two retailers.

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