Coordinator: Welcome and thank you for standing
by.
At this time all participants are in a listen-only
mode until the question-answer of today's
conference.
At that time, you may press Star 1 on your
phone to ask a question.
This conference is also being recorded.
If you have any objections, please disconnect
your line at this time.
I would now like to turn the conference over
to (Kim Davis) - thank you.
You may begin
(Kim Davis): Good morning everyone, thank
you for joining us today for another Census
Academy Webinar OnTheMap, the Road to Employment
Dynamics.
We are recording today's webinar and it will
be available on Census Academy within the
next couple of weeks.
And we also will be hosting a Q&A session
at the end of today's session.
We have a large number of participants with
us today, so we ask that the participants
ask only one question and one follow up questions
during the Q&A session.
If you have questions, you are also welcome
to enter them into the Chat feature, and we
will address the questions as we participate
in the webinar today.
If you don't get all of the questions in chat
answered, we will follow up at the end via
email to all participants.
We also will be asking for your feedback at
the end of today's presentation in a brief
evaluation survey that will pop up on your
screen when you close out of the events.
And assisting today will be - I'm sorry presenting
today will be (Eric Coyle) who serves as a
Data Dissemination Specialist for the US Census
Bureau.
He is responsible for building and maintaining
relationships with stakeholders through the
dissemination of census data and information.
Mr. (Coyle's) primary responsibilities are
to plan and coordinate and implement data
dissemination and outreach.
We have joining Mr. (Coyle), our Subject Matter
Expert, Ms. (Earlene Dowell).
She is a Program Analyst for the Data Users
Trade and Outreach Branch at the US Census
Bureau.
(Dowell) has been promoting and training people
on the Longitudinal Employer-Hold Dynamics
Products - Programs for over 10 years.
Prior to joining the LEHD program, (Dowell)
played a key role during the 2010 census in
the Public Information Office and taught Communication
courses at the College of Southern Maryland.
(Dowell) received her Master's Degree in Communications
and a Bachelor's Degree in Public Relations
from Hawaii Pacific University.
Welcome to both of our presenters today and
for sharing your expertise.
The floor is yours.
(Eric Coyle): Thank you Kim, good morning
everyone - thank you for joining us this morning
for this very exciting webinar on a particular
favorite tool of mine called On the Map.
And let me go ahead and share the agenda.
So we will be covering the background of this
tool which is the LEHD -- Longitudinal Employer-Household
Dynamics Program and the -- which is the umbrella
for the LED Partnership Program where these
tools come from, specifically today OnTheMap.
I also want to make sure we have a clear understanding
of what the NAICS system is -- NAICS Code
System -- North American Industry Classification
System which is the system we use to identify
businesses in the United States.
So we will also look at census geography as
it is the framework of the data.
And there are some really amazing things that
you can do it On the Map because it does get
down to some pretty low levels of geography
you may not be familiar with.
We'll show you - then I will pass the baton
over to my colleague -- (Earlene) -- who is
our Subject Matter Expert for the LHD programs,
and she will show you some examples and then
do a live demo as well.
I'll show you some additional resources.
And then of course we'll have time for some
Q&A at the end.
So as Kim pointed out, this webinar is being
recorded and will be shared eventually on
Census Academy where you can access the recording
and materials.
So with that, let's go ahead and get started
and get started with our virtual road trip
today.
And so when you talk about LEHD and LED, there
tends to be some confusion with, you know,
which is which and what does what in regard
to LEHD versus LED.
So the LEHD -- Longitude Employer-Household
Dynamics is essentially -- as we just mentioned
-- the umbrella for the LED partnership, and
I'll talk about that more.
But essentially the program -- the LHD Program
-- is part of the Center for Economic Studies
at the Census Bureau and this program produces
new, cost-effective, public-use information
combining federal, state, and Census Bureau
data on employers and employees under this
LED partnership.
So it's really that sort of what formulates
that partnership, what creates it.
So what is the partnership?
What is the LED partnership?
Well, you can see that basically it began
in the late '90s with only a few states.
And we had actually doing all 50 states at
one point and we had all 50 states at one
point.
I think then we had - I think Wyoming wasn't
participating.
But now we have three states that are just,
you know, choosing not to share.
It's not a mandatory partnership.
If they choose not to share their data, they
don't have to.
But (take) all authorities, you know, they
increasingly need detailed local information
about their economies to make informed decisions.
So the LED partnership actually works to fill
critical data gaps and provide indicators
needed by state and local authorities.
Under the LED partnerships, states do agree
to share unemployment insurance earnings and
the quarterly census of employment and wages
data.
So they choose to share that information with
us.
And so those three states that are participating
right now are currently Alaska, Arkansas,
Mississippi.
And Puerto Rican Virgin Islands we are not
producing data for.
But you can still get previous year data for
those three states in quarterly workforce
indicators explorer tool.
So, in some states, you know, they've opted
out in the past and they've opted back in,
so you never know.
We do update that.
You can go on to the LEHD website and look
at state partners and they'll tell you and
keep you up to date as far as who's participating
and who is not and what the date is from that
recent update.
And I just realized you guys weren't able
to see this slide, and this is the slide I
was just talking about.
Now, let me we go further on.
So the LED -- LED data -- provides unprecedented
detail about America's jobs, workers, and
local economies as well as the Longitudinal
Record of US employment.
So by integrating this existing data from
the states supplied administrative records
and workers and employers to create this Longitudinal
Data System on US employment.
State of the art methods to protect the confidentiality
of the original respondents allow the LED
to release data from local and regional areas
beyond traditional boundaries for public use
on the internet.
And that is what allows us to get down to
these low-level geographies by that state-of-the-art
methods to protect confidentiality.
Because if any of you are familiar with Census
Bureau data, that's the most paramount aspect
of our data is privacy protection.
Federal law protects individuals and businesses
from any of their data being compromised.
So, therefore, those same state of the art
methods are very crucial and important to
the LED data that is published.
But really essentially the LED is an integral
part of the Department of Commerce's open
government plan to really, you know, unlock
a lot of this incredible public access, public
domain data and to really increase participation
in the use of that data.
That's what we want to see.
We want to see more people get access to this
data, to use our data, to leverage the data,
however, they see fit.
So now when you're building on these state
inputs you can see that, you know, by combining
this data what we're able to do by combining
it with survey data state records, etcetera.
And it allows us to look at and create statistics
on firms, establishments, jobs, and workers.
And which also really is crucially important
is the firm and person characteristics like
age, sex, race, ethnicity.
All that information is there in these different
tools that we have available and On the Map.
You can look at different aspects of workers.
You can look at workers and sort of select
them by either age or sex or race or ethnicity.
And really the most important aspect of this
probably is the fact that there is no new
responding burden.
There is a new survey that's going out and
trying to get responses from people.
This is actual data that currently exists
and we're just combining it together to create
these public data access tools.
So when you look at, you know, how does that
all come together, you can see here, you know,
in regard to the firm data, that's your Quarterly
Census of Employment Wages, your Economic
Survey Data, the Business Register.
Then you look at that Jobs Data.
That's your unemployment, insurance, wage
records, the OPM data, as well as dental records
for that Household Data Demographics Census
Survey Data, right.
So all that gets matched into a well-oiled
machine that is the LEHD Program through or
LED partnership, and we're able to create
these public-use data products.
And these products are pretty amazing.
As you can see, we have quite a few.
Well, let me see here.
There we go.
We have quite a few of these products.
The flagship product was actually the Quarterly
Census of Employment and Wages.
Now - oh I'm sorry, the flagship product was
the Quarterly Workforce Indicators which provides
information about trends, in employment, in
hiring, job creation, and destruction, and
earnings and really unprecedented detail on
geography (unintelligible) as far back as
1990, right.
The second data product is the LEHD Origin-Destination
Employment Statistics or LODES.
Yes, that's probably officially the Guinness
Book of World Records longest acronym because
the L in LODES stands for Longitudinal Employee
Household - Employer-Household Dynamics.
So that provides annual employment statistics
linking home and work locations down to the
census block level.
So that's the incredible tool that we're going
to be looking at today primarily.
Of course, we do have the job-to-job flows,
tracing worker movements through industries'
geographic labor markets, (so) post-secondary
employment outcomes which is a new experimental
set of statistics looking at earnings and
employment outcomes of graduates.
So, you know, that's a really, really., you
know, post-Secondary institution.
It's a really fascinating, really great tool
as well.
I highly recommend, you know, after this webinar
and then we're focused on OnTheMap today to
really check out, take the time, and look
these other tools that are available from
the LED, LEHD Program because they are really
fascinating and there's some really cool stuff
you can do in terms of the visualizations
within these tools.
All right, we also have the Veterans Employment
Outcomes.
That's the brand-new experimental statistics
on looking at earnings and employment of Army
Veterans after discharge.
So that's another really, really great new
tool coming from this program.
And as you can see, we are really giving you
lots of great data and showing you how this
partnership -- this LED partnership -- how
we can leverage it to really give you all
this incredible longitudinal information and
sort of the workforce characteristics.
And it's all coming from existing data, so
keeping it at a relatively low cost to do
all this work.
Now giving you this insight is really important
but getting access to a 24/7 is really what's
incredible and wonderful about these data
products because it is free to the public.
24/7 you can access it.
This is all public domain data.
And with that, I now want to go into the North
American Industry Classification System because
that is the system that we use to identify
and classify our businesses in the US.
And what is the sort of tabulation in the
universe in which we tabulate data on businesses
and industries from the LHD Program.
So it's really important to have just a good
understanding of the NAICS Industry which
started in 1997 and is part of (NASA).
It is hierarchical and meaning that we have
a two-digit NAICS code and then there is a
- all the way to a six-digit NAICs code.
As you can see, that two-digit is really going
to represent that main sector like retail
trade, construction, mining, etcetera.
The subsectors will get you more into detail
in regard to that particular industry, right?
Now for OnTheMap, there's only the two-digit
NAICS codes currently available.
So you can only look at industries at the
two-digit NAICS codes.
However, the QWI -- the Quarterly Workforce
Indicators tool -- does allow you to go from
two to three to four-digit NAICs.
But limitations and more-detailed industry
mean less granularity, so you can only get
down to the county level in that particular
tool.
So keep that in mind.
The codes are updated every five years in
years that end in two and seven.
And so the latest last update to the NAICS
code was 2017.
And that also coincides with our Economic
Census.
You can actually go on to our website onto
Census.gov.
NAICS has its own separate website.
But I often recommend if you're looking for
census data in regard to NAICS, a good place
to start is on our website.
So you can actually go to Census.gov/NAICs.
And you can go in and look at the manual,
the 2017.
You can look at previous year manuals as well
and sort of look at the difference in those
changes for industries.
Now if industry changes in the code system,
really the reasons primary is because industries
-- either a new industry is emerging -- or
other industries disappearing altogether,
right?
So millennials, that may be or (unintelligible)
may be on the webinar may not be familiar
with record stores, all right, or stores that
just sold TVs or stereo equipment or something
like that.
And so those stories kind of went the way
of the (dodo) and now they have been - that
code goes away as well when there's not as
many of those industries to merit having its
own code.
So they get consolidated into what would be
an electronic store, right.
So that would cover any of those industries
that are still left out there.
And of course, new codes created for those
new industries like, you know, renewable energy
industries bio, you know, geothermal, or solar,
etcetera.
Now into geography, this is also really important
because geography is the framework of the
data.
And most people are familiar with legal areas
and legal concepts of geography, regions,
divisions.
But we need to look at something like a census-designated
place.
So, you know, regions are going to be like
Northeast, Midwest, etcetera.
You know, division is a collection of states
within those regions.
But a census-designated place, not everybody
is really familiar with the term places.
So what is a place?
And so the Census Bureau uses the term place
in many of its data tools.
And if you're not familiar with what a place
is or the term that we use, it's essentially
the term we use to describe all cities and
towns.
So that's important to understand when you
see that listed under counties, you'll see,
you know, place and track and zip code or
zip code tabulation area.
I'll talk about that more in a second.
But it's important to understand that distinction
-- that term that we use in many of our data
tools -- to identify all cities and towns.
So a census-designated place is an important
geography because it's essentially an area
that is unincorporated and has been basically
quite requested by the county to tabulate
data for this particular area.
So the county provides the boundaries for
that unincorporated area.
And then we go ahead and gladly tabulate data
for it.
So it's a cooperation between state governments
in the Census Bureau to tabulate data for
those unincorporated areas that we put in
some designated places.
Now not all unincorporated areas are automatically
CDPs.
Again, it's in cooperation with state and
local governments, so it's not requested.
There may not be - it may not be identified
as a CDP.
And then another really important, I won't
get into the census counting divisions.
These are the unincorporated areas that are
not CDPs.
They basically fall within the county boundaries,
or the (PUMA) as much.
But what's really great about this OnTheMap
tools, you can look at the Zip Code Tabulation
areas which are important.
We use that for population.
The -and most of the population is aware of
zip codes and the fact that they're owned
by the post office and the post office can
do pretty much whatever they want with them.
And that's great for the post office.
They use them to deliver the mail.
That's extremely important.
But for fiscal agency, we actually need some
level of permanence.
So we created Zip Code Tabulation areas which
allows us to then look at basically remove
any of those zip codes that are attached to
a PO Box or a large postal customer.
So the OnTheMap to really look at the zip
code tabulars to areas with data on population.
And then you have another really important
geography which is probably one of the most
important that I usually share with my data
users out there, and that is a Census Tract.
Now a Census Tract is a subdivision of a county
based on population thresholds.
And for a Census Tract, that threshold is
1,200 to - I'm sorry (33) to 8,000.
So that threshold is extremely important because
it's what allows us to look at these tracks
and maintain a sort of standard for how we
want these tracts in terms of the population.
I think it's a (unintelligible).
It's actually 1,200 to 8,000.
And we optimize them for 4,000.
So when you're looking at the screen, you're
actually looking at a collection of census
tracts.
And you may notice that some of the tracts
have similar numbers and some are completely
different.
Some are like 2, 3, 1, 2, 10 or 2, 3, 1, 2,
20.
And at one point, that was actually just one
whole tract.
But as the population increased over time,
that tract had to be split to make sure that
it did not go beyond the threshold of 8,000.
Now this happens once every 10 years at the
time of each decennial.
And it's very important to note that they
are relatively permanent and firmly based
on physical boundaries and meant to nest within
counties.
So again, they are subdivisions of counties
and that is their nesting area.
They can coincide or correlate with cities
and towns out there, but they're not bound
by those particular boundaries.
So below the census tract level you'll have
block groups.
That is also based on population size.
And for block groups, you're looking at 600
to 3,000 top size for those particular areas.
Those are the subdivisions of tracts.
And then the lowest level of geography is
the block.
And within this particular tool and OnTheMap,
you can get down to the census block.
So what does that look like when you put it
all together?
I love showing this because it really gives
a clear picture of how these geographies are
created and what that full public picture
looks like.
So if a census block is not based on population
size or housing units.
There is a formula that goes into creating
a census block.
And in urban areas, it will pretty much mirror
city blocks or, you know, in urban areas.
As you get out to suburban and rural areas,
it's kind of going to go a little bit all
over the place and expand and get really far
out there.
And again, that's because it's not based on
population size or housing units, but it is
firmly based on physical boundaries.
So just keep that in mind.
Now within OnTheMap tools, if you were actually
creating because you can actually use a polygon
feature in OnTheMap to create your own geographic
area.
You can upload shapefiles and all that kind
of stuff.
There's lots of cool features.
But if you were to try to go ahead and split
that block with your line -- depending on
where that line falls in the centroid of that
block -- it's either going to remove the block
from your map from your data in your analysis
or it's going to pull it in, okay.
So keep that in mind.
You cannot split a block in OnTheMap, right?
So that's important to understand.
The block though -- again not based on population
size or how the units will attach to block
groups -- based on that top size (I mentioned
the force), 603,000 is going to combine with
other block groups to format Census Tract.
So in Tract 107, which you're looking at here
on your screen, you actually have a collection
of four block groups and you have multiple
blocks within those block groups.
All right, now that tract then combines with
all your other tracts that you see to form
your county.
Now the really important aspect about tracts
is no matter how many times that tract is
split.
Let's say the Tract 107 here - it's at the
time of the Decennial Census so they've got
to go ahead and look at all the tracts and
figure out which ones have increased over
the past 10 years and which ones need to be
split.
So if you split this tract, no matter how
many times you got to split it based on the
population, that tract -- the frame of that
tract -- will never change.
It will always stay in its original frame.
And that allows you to go ahead and aggregate
that data if it's been split and compare it
with the previous tract data.
So that's a really great feature of our Census
Tracts.
And just to kind of give you an overall hierarchy
view, I know it's kind of a scary-looking
slide there to see all these different geographies.
But it gives you kind of an overall picture
of, you know, the really important geos that
we have in this fiscal area that we have like
tracts and block groups - excuse me, and the
blocks.
And just a reminder that places represent
cities and towns including TDPs and just designated
places.
Okay, so with that I'm going to go ahead and
pass the baton on to my colleague -- (Earlene)
-- and she's going to give you some examples,
some real examples using OnTheMap, and then
actually take you online as well and show
you how to recreate those examples.
So (Earlene), the floor is yours - thank you.
(Kim Davis): Thanks (Eric).
(Earlene Dowell): Okay great - hopefully everyone
can see my screen.
So thank you so much to the Census Academy
and to (Eric Coyle) for allowing me to share
with you some of the real examples using OnTheMap
during COVID-19.
What we're going to be doing, I will share
two examples with you and then I will demo
some of OnTheMap features and then I'll go
over the second example.
And then we'll work through the second example
together.
(Zillow) wrote an article about rapid movement
towards remote work arrangements in the wake
of the pandemic.
This raises an interesting question on the
future of urban workers.
Will workers place less value on living near
a downtown job center?
Though it's too soon to answer this question,
(Zillow) found that 8.2 million US workers
that live in cities travel to the suburbs
to work.
In the article, 25 out of the country's 35
metro areas -- such as San Francisco, Boston,
Riverside, Tampa, and Orlando -- tend to work
in the suburbs or rural areas.
The article also looked at age as characteristics
which was the same across the board and not
subject to younger population as one would
expect.
So using Tampa as the selected area and the
Inflow/Outflow Analysis, we can see how many
workers live in Tampa and how many of those
workers leave Tampa to work in the suburbs.
So here, we can see that out of 140,663 workers
that live in Tampa, 85,168 leave Tampa to
work outside of the city.
This is 60 percent of workers traveling out
of the city to work.
Also using the Inflow/ Outflow Analysis -- if
you look at the table on the right-hand side
-- and we are definitely going to work through
this as the demo.
You can see that age 29 and younger workers
through the data tool, we know that workers
equal 58,180, age 30 to 54 total doubled with
121,759 and age 55 and up totaled 49,433.
So let me go live to demonstrate how easy
it is to recreate this example and show you
another analysis of how far people are traveling
to the outside of the city and the directions
they are traveling to.
So if I go to OnTheMap.ces.census.gov, we'll
do this together, but just to show you how
the example regarding Tampa works.
So here is OnTheMap and we go ahead and click
on the Search Box and I'm going to type in
Tampa.
Once I type in Tampa, I'll click on search
and every geography that has the word Tampa
pops up.
So since we're looking at the metro area,
I'm going to go ahead and click on the area
that says metropolitan micropolitan areas,
and I'm going to click on Tampa, St. Petersburg,
Clearwater, Florida.
And then once that happens, a pop- up comes
up.
And then we can see the selected area that
we've chosen.
We can see how many select - how many square
miles are in that selection.
We can see how many census blocks are in that
selection.
And the great thing about all of our data
tools is that it's very intuitive.
So it's obvious what you're going to click
next.
So I'm going to go ahead and click on Perform
Analysis on Selection Area.
So once I'm there, it gives me another pop-up
box and it gives me the analysis setting.
So in the first column, it says Home or Work.
This is where you can choose whether you want
to look at where workers live or where workers
work.
That's the big thing about OnTheMap.
It connects where the worker lives and where
the worker works.
The next column is the analysis type.
So we have five different analyses that we
have listed here but we can do other things
and more, more custom to whatever that you
might be looking at.
So here, we - the first one is the area profile,
and that's just it.
We look at an overview of the area that we're
looking at.
And it can tell you what the age, what the
earnings are, what the sex, what the race,
what the ethnicity, what your educational
attainment is, and then it looks at the NAICS
as well.
The area comparison compares - you can compare
earnings.
You can compare age.
You can compare zip codes.
You can compare counties and all sorts of
different other earnings.
Distance Direction tells you where they're
coming from and how many miles they're coming
from.
And then Destination tells you what place
they're coming from or what city they're coming
from, what county they're coming from.
And you get to choose what you would like
to look at.
And then the Inflow/Out is what we looked
at earlier.
And that just tells us how many people travel
into the selected area to work, how many people
live and work within the selected area, and
how many people travel out of the selected
area to work.
And then the next column is Year.
So here you can choose all the different years.
So if there is a state that doesn't have a
certain year, you will get a message that
says Data Not Yet for This State.
But a lot of times we're just processing the
data and it's just being added.
And then Job Type is how many, I mean, the
jobs that you have out there.
So all jobs is every single job that you might
have out there.
Primary jobs is the one that brings home the
most money.
And these two -- the All Jobs and Primary
Jobs -- include the Federal jobs, but that's
for 2015 through 2010.
We are still putting in the 2016, 2017 data
for the Federal government, I mean, Federal
workers and that should be updated by this
year.
And them all Private Jobs is just that.
It's just the private sector.
And then the Private Primary is the private
sector that brings home the most income.
So as I said, everything is very intuitive,
but we're going to go ahead and click on Inflow/Outflow
in the second column down at the bottom.
And then I'll click this lightning bolt bold
gold with an exclamation point.
And then hopefully you can all see that now
that we see that there are 266,552 people
that travel into Tampa to work, 846,714 live
and work within Tampa, and then there's 250,231
that live in Tampa but travel out of Tampa
to work.
So on the right side, you can see the table,
and the one that we're interested in is the
Living in the Selected Area but Employment
Outside.
So if I click on that, the map updates and
the (VIN) updates and we're just looking at
the 250 - 250,231.
But we have another feature where you go on
the left side where it says, All Workers.
I can click on All Workers and then we can
look at the worker age which is what the article
talked about.
So here we can look at worker age and then
we can see 29 - 29 or younger.
And then this update the VIN, I mean, the
table and the VIN updates and you can see
the arrow.
Now we're looking at 63,697.
Those that were living in that area are traveling
out of the area, 29 and younger.
You can click on that again and we can look
at 30 to 54.
And then once again, everything updates and
we can see that those that are 30 to 54 for
living in the area traveling out of the area
is about 131,832.
And then finally the worker age for the 55
or older, we have about 54,702 in Tampa traveling
out of Tampa to work.
So the other thing is like where are they
going to work out of Tampa?
So if I come here to the lower left-hand corner
and I click on Change Settings, we can see
the inflow/outflow.
And then so I'm going to go just above that
where it says Distance Direction, and I'll
click on that.
And then we'll click Go Again.
And now what we're looking at is how many
miles people are traveling?
So you can see where my cursor is -- that
10 to 24 miles -- those workers, that's about
29% of the worker population that live in
Tampa are traveling out to work.
And then we can see 25 to 60 and then we can
see greater than 50 miles.
And then you can see the radius at the top
here.
And then if I click on, for example, 25 to
50 miles, and we want to see what that is.
And then it updates, and we can see the regions
that people are traveling to work 20 to 50
miles.
And we can see the north and northeast, the
east, the southeast, and so on.
But if you total all of that together, and
I'm going back to the main page for the distance
direction.
But if you total, you know, all of those that
are traveling 10 to 24, 25 to 50, and greater
than 50, that's about 60% of the population
-- the worker population -- traveling out
of the metropolitan area to work, so just
fascinating stuff.
So let me go back to the PowerPoint, and then
we'll talk about the second one.
So in another recent article, the Load to
Data was used to track where workers from
a plant in Minnehaha County, South Dakota
resided.
The data showed that many that worked in Minnehaha
also lived in Minnehaha.
But the next largest number of workers resided
in Lincoln County.
The data also found a number of Native Americans
who worked at the plant and resided on a nearby
reservation where there is a lack of medical
resources to a vulnerable population.
So using the article on South Dakota, let's
recreate this example using OnTheMap.
And if you can work with me, let's do it together.
So I'm just going to stick to the slide show
and then I'll jump into a live demo.
So if you go to this (URLOnTheMap.cef.census.gov),
and that should take you to our home page.
And then you can type in Minnehaha in the
search box.
And once you type in Minnehaha, go ahead and
click Search or Enter.
And then choose the bold Minnehaha under counties
for South Dakota.
And then once you're there, you get your pop-up
and then you would click on the Perform Area
Analysis in blue.
And then let me catch up with you all.
So let me go live too, and I will reload mine.
So I'll go ahead and type in Minnehaha.
Click on Search under County's Minnehaha County,
South Dakota.
We can see that there are 5,510 census blocks
in that area - clicking on Perform Analysis.
And then I'm going to show you the Area Profile.
So, and I'm going to Click Go so you can see
an example.
So I'm going click Go and I have it on 2017.
And so an analysis error comes up.
And earlier how (Eric) talked about the different
states that are in, this gives you information.
So Alaska, we don't have 2017 data, but in
Arizona, we don't have 2002.
And then if we go down to the bottom, we can
see South Dakota.
We don't have 2017.
So I'm just going to close out of that box.
And then I'm going to click on 2016 because
that's what the article used.
It used the 2016 data.
And then I'll click on Go.
Sorry for the delay.
Another thing I forgot to mention is that
if you're using OnTheMap or any of the LEHD
data tools, we recommend that you use Chrome
or Firefox mostly because it plays nicely
with those two web browsers because there
are so many graphics that has to be uploaded
from the maps.
So it's coming in.
You can see and on the right-hand side we
can see that there is a total of private primary
jobs of 105,195.
We can look at the worker age.
We can look at the earnings.
We can see the NAICS industry sectors.
So under manufacturing, that would be 10,760,000
workers in Minnehaha, and then which is a
lot of workers.
And then if you keep scrolling down, we can
see worker race.
So it talked about Native Americans and we
can see out of that worker population that
there are 1,687 American Indians or Alaska
Native alone that work in Minnehaha.
And before I get far into this and forget
to tell you, yes, you can print out detailed
reports.
You can (print) them up to pdf Excel or html.
You can export the geography so it will print
the chart and the map for you.
So then, let's also click on Change Settings
down in the lower left-hand corner.
And then let's go ahead and click on Destination
under the analysis type.
And then under a Destination Type, let's look
at County.
So I'll click Go again.
And thanks for your patience.
Everybody must be working with me.
So in the article, it talked about Lincoln
County.
So on the right-hand side in the table, you
can see that Lincoln County came in second.
So this is just proving the article and how
they use the data.
And we can see that those that live in Lincoln
County, that's about 16,122, but they work
in Minnehaha.
So is the, you know, the workers that work
in Minnehaha that are going home to Lincoln
County.
All right, the other thing that I like about
this analysis type is the (Spoke) Overlay.
And so it's not automatic.
It's not default.
So you have to actually click on the Spoke
Overlay which is under the map controls on
the left-hand side.
And if I click on that, that kind of gives
you a visual of where they're coming from
or where to work in Minnehaha.
So here is the top 10.
And then the great thing is that you can click
on this key that says Identify.
This is my favorite feature.
So if I click on Identify under Map Controls
and then I'll pull out of that little window
and then I'll click on the tip of the Spoke,
it'll give me more information regarding that
area.
So we can see that I clicked on Lincoln County.
How many workers are in Lincoln County?
And then we can look at what their age is.
We can look at what their earnings are.
And we can see the industry segments that
they are in.
So All Other is probably the manufacturing
plant.
So I'll close out of that.
And then just one more visual just for kicks.
I know that there's about 60 I think maybe
counties in South Dakota.
But I'll just go ahead and click on 25.
So that just kind of gives you a visual of
those that might have been infected at this
plant and where they're all traveling to,
to go home though, so one moment.
So see, we can see what the effect could be
regarding people that might have the virus
that worked at this plant in Minnehaha, and
where they're all going home to, you know,
from work.
All right, back to the PowerPoint.
So this is just a lot of links that are very
helpful.
I just briefly touched on just the tip of
what OnTheMap can do.
It can do so many other things.
It can do customs, analyses.
It can just - it's just a wonderful data tool.
It can look at commuting patterns as you saw,
but here are the links.
There's a lot of links that can help you walk
your way through all the different analyses
that we have that you can learn on your own
if you need to.
But, there's - you can always ask me too.
All right, and with that, I will hand it back
to (Eric).
(Eric Coyle): Thank you (Earlene), that was
outstanding.
We appreciate those examples on how this information
- how these tools are really being utilized
even in the midst of a pandemic.
So I know we got some questions.
Usually the number one question everyone has
on their minds.
I mean, we get to one right now before we
finish up and get to the real Q&A is in regard
to the 2018 data, and if and when we know
when that's going to be added into the dataset?
(Earlene Dowell): We hope to have that at
the end of the year.
And then when we do put in the 2018, we will
probably try to also add the 2019.
So everything will be updated together.
Currently, we are just working on putting
in the Federal workers first.
(Eric Coyle): Great, thank you for that - so
before we get into our Q&A, we just want to
sort of plug some of our other additional
outlets here for information for you all.
So if you are so inclined, you can check out
our America Count stories.
There's a lot of great ways you can see - other
great ways you can see how Census data is
being used sort of in real-world situations
and stories that are being created, new content
added on a weekly basis pretty much.
And then if you want, you can actually subscribe
to our newsroom to get updates through various
topics or for various topics of interest.
So if you want to know when that update for
(LEHD) is coming, you might subscribe to Employment
Data for Under the Newsroom.
We also have Directors' blog and (staff resources).
A lot of these different -- like American
Count Disaster stories we'll have sort of
really great visuals embedded into the stories
themselves, so I highly recommend that.
Oops, sorry I'm not sure how that happened
- get back.
And we also have a lot of great platforms
on social media, so you can check us out there.
You can interact with us.
We do a lot of visualizations on any particular
topic of the day whether it's something for
even International Donut Day.
We'll have like a visual on how many donut
stores and donuts are consumed or National
Pet Day or etcetera.
So you'll find lots of different visuals that
will produce just for our social media platforms
and content that we love to share through
that, those mediums.
And of course, you should already be well
aware of Census Academy.
We look forward to having you join us for
more feature webinars.
You can also subscribe to Census Academy.
It's just something we really highly recommend
and encourage you to do.
So you're always just aware of not just our
webinars that are upcoming but even our data
(gyms) and sort of little how-to videos that
we produce on how to access data from data
tools like OnTheMap or any of the other LHD
tools that we have available.
And so we also have courses that you can look
at and you can access at your own leisure
and run through.
And more content is being added.
There's a lot of great stuff forthcoming with
Census Academy, but also share your feedback.
If you have an idea for a course or a webinar
or a data (gym) for that matter, please go
ahead and share that feedback with us.
We value all feedback, good or bad.
So with that, we'll go ahead and then we've
only got about eight minutes left.
We'll go ahead and operate if you want to
go ahead and cue up any questions that we
may have.
Coordinator: Thank you - we will now begin
the question and answer session.
If you'd like to ask a question, please press
Star 1, unmute your phone and record your
name clearly.
Your name is required to introduce your question.
If you need to withdraw your question, press
Star 2.
Again, to ask a question please press Star
1.
It will take a few moments for the questions
to come through.
Please standby.
(Kim Davis): Hi everyone - this is your host
today, (Kim Davis).
And I just wanted to let you know that a few
questions have come up about currency of data
in relationship to COVID.
So I will put in Chat and link to our COVID
hub, a resource about data that we have available
and collected in collaboration with other
Federal agencies so you can see what activities
are going on.
We have conducted a couple of surveys, and
so I'll put the links from the information
for both of those COVID Hub resources.
Okay Operator, you're welcome to open it up
on the phone line - thank you.
Coordinator: I am showing no questions at
this time.
So just as a reminder, Star 1 if you'd like
to ask a question.
(Eric Coyle): Well while we wait for that,
I do see some questions in the Chat I think
I can try to address.
And then (Earlene), if you can - if you want
to tackle any of those as well, yes, you can
ask a question in Chat - absolutely.
So I think there was one I saw in regard to
what is the best way to get geospatial on
NAICS within a county - the geospatial information
or county.
I'm not sure you can - I'm not sure you can
do that within OnTheMap unless, (Earlene),
is that available?
I know you can download (sheet) files.
(Earlene Dowell): I'm sorry, what was the
question?
I guess - I apologize, I was reading the Chat.
(Eric Coyle): Oh yes, no, so the best way
of getting geospatial information on NAICS
with a county.
Well, you can download - I know you can download
the information by selecting a county to get
data on and do an analysis through OnTheMap.
I can then download the map and everything
like that.
Does it provide the geospatial information?
(Earlene Dowell): I want to say yes.
But if you would please send me an email and
I can doublecheck with our programmers regarding
that.
But I believe yes - yes is the correct answer.
(Eric Coyle): Okay, and then someone else
has the question in regards to the input/output
changes from year-to-year.
Well, there's a really cool feature on OnTheMap
that allows you to actually animate.
You can - and I'll go ahead -- and since I've
got the baton here -- I'll go ahead and share
my screens and go to OnTheMap here.
Let me go ahead and share real quick.
So in OnTheMap, this is just the work analysis,
the default here, and you can always come
down here and click on Change Settings.
And then that will go ahead and open up that
Analysis Tool to allow you to either select,
you know, those different variables that you
want.
To look at the data over time, you just need
to go ahead and check these various years
now and then what.
As long as that data is there, that goes back
to (unintelligible) and could get an error
depending on the location where you're looking
at.
You can select which jobs you want to look
at and then go ahead and make sure you check
inflow/outflow.
That definitely helps.
Click Go.
And when you (unintelligible) check those
boxes for multiple years, there's a really
cool feature that allows you to (unintelligible).
You can look at a year-for-year just by using
the dropdown menu here under the Display Settings
on the left to change that.
Or you can also go ahead and animate the overlays.
So this is really cool.
You can actually just click the (gun animation)
and it will go ahead and give you that year-for-year
for all those years that you selected and
seeing that change.
Additionally, for all these different types
of analysis, what I found really useful -- let
me go ahead and stop the animation here -- is
to go ahead.
And in that sort of, you know, export geography
is a feature we were talking about, shapefile
(unintelligible) in the selection area, etcetera.
You can get a detailed report.
And a detailed report for the inflow/outflow
is going to give you inflow/outflow is going
to give you more data than you see here on
the right.
So on the right of your screen, you get a
- kind of get the sort of really focused on
that one particular inflow/outflow analysis.
But if you click on that Detailed Report,
then you're going to get that breakdown of
other characteristics that we see with other
sorts of selections that we can make like
age groups, income, you know, more results.
You'll get that for each one of those types
of analysis that we're looking at whether
it's the jobs people working within a given
area, living in a given area, working outside
or living outside and working in a given area,
and of course, living and working inside and
living in a given area.
So there's lots of really great features here.
We've only touched on a few but you can definitely
learn more going through some of the different
links that I shared in the presentation.
You can look at different ways that you can
actually draw.
If you want to go ahead and clear your selection,
you can do that.
Make sure you come here and get no selective
layer.
And then you can actually, I believe - let
me go ahead and clear selection.
Results - I will remove my results tab if
that helps.
And now I can go ahead and draw.
I can click on that draw polygon and I can
zoom all the way down, really about halfway
in.
So if I zoom down even further, I can just
kind of click a different area.
Double-tap when you're done, confirm and confirm
selection.
Once you do that, you can perform an analysis
on that area just like that - super easy.
And of course, if you want to upload your
shapefiles, import geography here, that's
a really great feature to have.
I recommend before you do anything in terms
of analysis and doing geography's, if you
want to upload shapefiles, you do that from
that start page here before you make any searches.
Scroll down if you're going to find that ability
to do that right there.
You can also hide tabs, show tabs.
You can move all these around.
Let's see if I can get rid of that.
Here we go.
If I (unintelligible) if I get that chart,
I can slide that around too.
So there's lots of great manipulation here
that you can see.
I'll go ahead and go back...
(Kim Davis): Hey Eric, we have a question.
Is it possible to map current unemployment
data?
(Eric Coyle): Current unemployment data - well,
the feature -- the main -- so not within this
tool.
I think you could do that through data.census.gov...
(Kim Davis): Okay.
(Eric Coyle): ...because everything about
OnTheMap is looking at where employees work
and where they live.
So it's specifically looking for people that
are employed.
Unemployment data mapping that would be maybe
- I think maybe in Census Business Builder
has that variable in there.
(Kim Davis): Okay, and if a user goes with
a customized map, how small can the geo go
without using data that may be non-disclosure?
(Eric Coyle): It gets down to the -- for this
OnTheMap -- because of the protections that
are already in place in the formulas that
are in place, there is data suppression that's
occurring.
You're just not aware of it.
But that's what allows - that sort of - that's
where data protection in the formulas that
go into this particular tool that allows the
data user to get down to the block level within
this - within OnTheMap.
(Kim Davis): Oh, we are at the top of the
hour so I just have one more question before
we'll wrap things up here today.
If you think it's likely that we'll have the
2018 and 2019 data by the end of 2020, would
it be reasonable to think that we might have
2020 before the end of 2021?
And I think (Earlene), that might be more
directed ...
(Earlene Dowell): Right.
(Kim Davis): ...to you.
(Earlene Dowell): Yes, I can't answer that
question.
I'm sorry.
We don't know.
(Kim Davis): Okay well thank you both for
presenting and going through OnTheMap and
Jobs Data for us today.
We appreciate your presentation and your expertise.
If we were unable to answer any of your questions,
we will follow up with those questions via
email.
We'd like to thank everyone for joining us
today.
And join us for our next webinar tomorrow.
Tips and tricks to accessing data on ancestry
and foreign-born population.
Thank you everyone and have a nice day.
Coordinator: That concludes today's conference.
Thank you for participating.
You may disconnect at this time.
Speakers, please allow a moment of silence
and stand by for your post-conference.
END
