After you’ve got your spreadsheet ready, Click on the ‘File’ tab, then go down to click the ‘Publish to the Web…’ button.

Next you’ll have to click the ‘Start Publishing’ Button. I would also recommend that you click the box that says ‘Automatically re-publish when changes are made’, this will allow you to update your maps on GeoCommons directly from Google Spreadsheets. After you’ve clicked these buttons, you will be allowed to get a link to the published data. Here you should change from the default ‘Web-page’ to ‘CSV’. This will give you a link to your published data below.Copy the Link. It should look something like this:

Now you can head over to GeoCommons.com and after you’ve signed in, click the button the “Add a URL link” in the upload section. Paste the link from Google spreadsheets where it tells you to enter the URL, then specify CSV in the format section.

You will need to geocode your dataset, this should be pretty self explainatory if you’ve ever used GeoCommons, so I wont go into the details, but just know that once you’ve geocoded this URL once, we will continue using the attributes you specified to geocode any additional data you add into your spreadsheet. Your final dataset will look something like this:

Because the raw data is linked to a live website, you’ll see the ‘Fetch Latest” button above the title. Clicking on this button will update the GeoCommons dataset based on any changes that may have happened to your spreadsheet, and by updating the dataset, you’ll also be updating all of the maps using this as a layer. This means that when you’re working with a dataset that is constantly changing and being updated you’ll be able to update your maps by just clicking one button.

I’ve added a short video to show you the entire process from start to finish in less than 2 minutes.

To help us, stimuluswatch.org has set up a site dedicated to helping “the new administration keep its pledge to invest stimulus money smartly, and to hold public officials to account for the taxpayer money they spend.” They provide a database of “proposed ‘shovel-ready’ projects” throughout the country which will be candidates for federal grant money as part of the stimulus package. The site offers the capability for citizens to view the proposals and decide if they think they are critical or not.

In order to help viewers better assess the appropriateness of these projects, we uploaded the data to Finder! and then used Maker! to compare where these projects will be and where jobs are most needed.

In the map below, we show the projects by the number of jobs that will be created. The larger circles are where more jobs will be created. We also show the change in unemployment by county between November of 2007 and November of 2008. The blue counties are where there was a decrease in unemployment, the white where there was a fairly small increase, and the yellow and orange areas show larger increases.

Taking a look at the country as a whole, it does seem that many of the projects are proposed in areas that have suffered job losses. This is particularly true for areas of Southern California, Florida and the Rust Belt. Areas in the center of the country, where there have been the some decreases in unemployment have less proposals for job creating projects.

Lets look more closely into an area to examine how the proposed projects are matching up to job losses. Georgia is one area that seems to have experienced a heavy loss in jobs over the past year.

You can see in the map above that there are many clusters of counties whose unemployment rate has increased by more than five percent in Georgia. None of these counties have a project planned in the direct vicinity. The county of Hancock Georgia has had the highest increase in unemployment and the third highest unemployment rate for this November of all the counties in the US. In November of 2007, its unemployment rate was 9.2 and in November of 2008 the rate reached 20.1, a 10.9 percent increase overall. The nearest proposed projects to Hancock are either an hour and a half away in Macon or an hour and forty minutes away in Conyers.

While the governor of Georgia may have good reasons for creating jobs in the proposed areas, it leaves one to wonder what will become of the towns, such as Hancock, who have suffered the greatest in this economic crisis.

Take a look at this map yourself in Maker!. You can zoom in to areas you are interested and decide for yourself the validity of these projects.

On the other hand, it is interesting that Illinois is fairly well represented here. Of the 891 projects in the country, 119 or 13.8% of them are in Illinois. While Illinois does have some yellow and orange counties, it is by no means the hardest hit state in the country in terms of unemployment. Does the state expect some favoritism from the new president?

At a closer look, the 119 projects in Illinois will create significantly fewer jobs then projects in other states. California, which faced the fourth highest unemployment rate in November, is proposing 93 projects which will produce 238,329 jobs.

The chart below provides 16 states with the highest unemployment rates in November along with the number of projects proposed in each state and the total number of jobs and the number of jobs per 1,000 people those projects will create.

States like Michigan and South Carolina, who need jobs the most are proposing projects that will create comparatively few jobs per capita. You can download a CSV of this dataset from Finder! and do your own analysis of the proposed projects.

We can also look at the projects compared to state unemployment rates, as is seen in the map below. The yellow and orange states are the ones shown in the graph above. To see this map click here.

Of course nobody is saying that the unemployment rates should be the only criteria as to where stimulus money should go. But if the package it going to truly address unemployment, projects that will add significant jobs to areas with high unemployment rates should be considered strong candidates for federal funding.

Harvard launched AfricaMap. The map is based on the Harvard University Geospatial Infrastructure (HUG) platform and was developed by the Center for Geographic Analysis.  AfricaMap, a OpenLayers-based app, aims to expand existing initiatives for globally sharing spatial data and technology. 

Google Maps created a fun quiz where you get to test your geographic puzzle solving skills. To play the quiz, you have to rearrange letters in a map, using visual clues in the form of a Panoramio photograph, to spell a world capital or U.S. state capital.

The USGS National Geospatial Program Office launched a new version of The National Map website. Revisions include The National Geospatial Program and The National Map web site.

Discussions about the auto industry bailout have been percolating the blogosphere. How would this affect auto industry workers? CNN created an interactive map showing the number of auto industry jobs in each state.

While this information is all available on any metadata page in Finder there is nothing that really covers if the data has been quality checked. One of the dirty secrets of all data is there are inherently errors and mistakes. If anyone tells your their data is perfect they are most likely fibbing, and also believe their armpits never smell.

The challenges of data accuracy was reinforced recently on two different blog posts where readers identified errors on maps that we posted. One was a map our data team created on “College Coaches Salaries” where there were geocoding errors and the second was Steve Chilton’s OSM coverage map that had Monaco in place of Munich.

If you’ve spent a lot of time with geospatial data you’ll know these errors happen quite easily. Errors can be happen frequently with geocoding software and often it is just easy to overlook a misplaced city name when going over hundred of columns. I’ve been thinking about how we can introduce better quality assurance into both the data we contribute and help users of GeoCommons identify issues in their shared data.

For inspiration I looked into two existing projects Wikipedia and Swivel. Wikipedia probably has the most advanced quality assurance mechanisms in place for a crowdsourced project, but it is focused on text. Swivel on the other hand deals directly with data although not geospatial data.

One of the most useful approaches I’ve seen in Wikipedia is a common set of icons for labeling articles that have issues (no citation, too long, reads biased, needs verification, etc.). With the icons and text I can quickly see issues that exist with an article, which can help me gauge the extent to which I should trust the text. While the Wikipedia taxonomy is quite thorough it is geared around articles and not geospatial data.

One of the great things about data is that many organizations release it into the public domain, so copying data does not have the same issues that copying text has (plagiarism). This provides the opportunity to have data come directly from an “official source”. Swivel had the great idea of formalizing this by creating partnerships with organizations to share their data with the community as an “official source”. This again helps users decide on the level of confidence they have in a particular data set.

So my conclusion after spending some time looking at both was creating a set of icons and labels for datasets to let users know their level of vetting could be useful when combined with a clear labeling of a data set as “official source” or transcribed by someone else. Here a few possible labels for data and icons.

Geocoding Error

Needs Citation

Data Needs Cleanup

Data has been QA’d by an Editor

Then there are the icons that Swivel has created for “official source” data managed by Swivel and “official source” data uploaded by the source organization.

These are the tags that seemed to be most relevant. Are there others that tags folks think would be useful, or does anyone see issue with these? If there is general consensus around labels and icons to tag the level of validation for a given data set they could be used by anyone that has a need.

The other bit of this that I think is critical is creating a feedback loop to identify what the issues are with a particular data set. Which opens the question should these be georeferenced annotations indicating where on the map there error is, comments on the metadata page explaining the problem, or a combination of both. This requires a bit more engineering effort than the icons, but my first take is that a combination of the two could work well. Any other suggestions out there for providing better QA on geospatial data? Would love to hear them.

You can read Obama’s technology platform overview here. The plank that really grabbed my attention was the promise to “Open Up Government to its Citizens”. The idea that data about government (Congressional voting records) and created by the government (census data) should be easily available to the public. Specifically:

“Making government data available online in universally accessible formats to allow citizens to make use of that data to comment, derive value, and take action in their own communities. Greater access to environmental data, for example, will help citizens learn about pollution in their communities, provide information about local conditions back to government and empower people to protect themselves.”

The beauty is that we (the collective GeoWeb) have so many of these tools already built. The ability to deliver the data once it is made easily available has great promise. For instance here is EPA data on power plant emissions from GeoCommons:

From the map above you can see which power plants are producing the most poisonous CO2 emissions (click the down carrot on the layers box for the filter) or zoom into your specific neighborhood to see the plant and the type of environment around it. (Still refining the embed capability, but an example of how data can be virally spread).

The report goes on to recommend that the federal government should:

“Establishing pilot programs to open up government decision-making and involve the public in the work of agencies, not simply by soliciting opinions, but by tapping into the vast and distributed expertise of the American citizenry to help government make more informed decisions.”

This strikes again at the heart of the GeoWeb – enabling collaboration of experts and citizens across the country. Several projects and companies have pioneered dynamic collaboration around maps. Below is a Google MyMap with feedback around the GeoCommons power plant data in Florida”

View Larger Map

The blue push pins are the user generated feedback linking to expert opinion and photos from the field. This is just the tip of the iceberg of what is possible with collaboration around maps. These approaches can also be leveraged inside of government agencies, which is another plank in the Obama technology platform:

“Employing technologies, including blogs, wikis and social networking tools, to modernize internal, cross-agency, and public communication and information sharing to improve government decision making.”

We’ve seen a lot of this type of work going on in the intelligence community with Intelink, Intellipedia, and A-Space. There is also data fusion and sharing concepts, like the EPA’s Central Data Exchange. I’d love to hear other projects that fit in with the three planks, and more importantly existing or planned GeoWeb technologies that could help enable the new vision. I’ve really only highlighted two and I know there are tons more out there.