OK – the title is a bit over the top sensationalistic, but the metadata debate opens up the larger topic of technology being used to increase participation. There is a long history of technology increasing participation – the PC Revolution with the microcomputer, word processor, spreadsheet, etc – Web 1.0 with online auctions, web home pages, online communities, etc. – Web 2.0 with blogs, social networks, citizen journalism etc. If you really wanted to push the argument you could go back to the assembly line, the steam engine, or really stretch it back to crop rotation. I’d argue that the real power of Web 2.0 has been the democratization of participation through technology. Blogs are allowing anyone to have a voice – participatory media sites like Digg, Newsvine, StumbledUpon, Furl are allowing the public to vote what is news – self broadcasting platforms like YouTube, Vimeo, Blip.tv will put anyone on TV – participatory office applications like Writely and Google Spreadsheets are all changing the face of how the public interacts with technology and each other.

Mapping has very much been a part of this story, with Google Earth/Maps, Microsoft Virtual Earth, Yahoo! Maps and new projects like Open Street Maps all playing a role. In fact it was mapping applications that kicked off the mashup phenomenon with the combination of Google Maps and Craig’s List rental listings. Not surprisingly participatory mapping mashups sprung up in short order with innovative sites like Platial, Tagzania, Frappr and others. In these applications anyone could create a location on a map and tag it with social information like photos or descriptions about why they created it. These efforts were very much in the Web 2.0 model of mass participation where anyone could contribute information. For the most part, though, the data was fun and not what the GIS world would consider substantive. Sometimes this movement is called neogeography, web mapping, or a leading part of the larger geoweb.

In the GIS world it is a much different model where a small number of highly trained professionals have access to data and tools with which they render maps to be distributed to everyone else. As technology has advanced these maps started to be delivered to web browsers and have some interactivity. The model always remained the same though – professional gate keepers that brokered knowledge out to the masses. As Google and other mapping applications API’s have proliferated, the worlds of neogeography and traditional GIS have begun to intersect. Now the major GIS vendors are offering API’s to their technologies and there are new more dynamic ways for maps and information to be delivered. While the new technologies coming from the GIS vendors all have the right buzz words they still work on the very same model. A small group of trained professionals acting as gate keepers to the masses – whether their maps are delivered to you as piece of paper or a rich media Ajax application.

This is the crux, I believe, of the metadata debate. Let’s be honest adding a metadata link to a system like ours or anyone else’s is not really the issue. Adding in the link is not so tough and we’ll figure out an effective way to link to metadata if it is there. The issue is opening up geographic data and analysis tools to the masses. Metadata is a convenient barrier to entry as is the expense of software, training, and infrastructure to even get your foot in the proverbial geospatial door. The big goal of GeoCommons is to break down those barriers, so that geographic data and analysis can become accessible and participatory to everyone. I think that technology inexorably moves in this direction, but in my mind that is not why it is crucial to open up geographic data and analysis. The vast majority of geographic data is a public good. It is paid for and created by governments and nongovernmental organizations (NGOs). The mission of the data creators is to have the data readily available and consumable by the public, because they are inherently the ones that have paid for it. Yet we have a huge middleman that has grown up between the public and the data. A middle man that requires you to buy software, take training classes to use it, and support their ecosystem in order to access and consume the data. This ecosystem has in turned created a profession of people who have taken the courses, put in the time, and understands the often complicated world of geographic data and analysis. Neither the ecosystem nor the profession wants to see that cozy arrangement disrupted. Yet that is exactly what we are on the brink of.

Don’t get me wrong I am not advocating the end of Geographic Information Science or Systems. There is sophistication in the discipline that will never be comprehensible to the masses and that will always be the case. I spent way too long in grad school trying to sort it all out to have delusions that my Mom is going to be computing Voronoi tessellations. There are great things that the GIS world has and will continue to contribute, but it should not be an all or nothing monopoly. I do believe that access to geographic data and simple analysis tools should be made available to everyone, and I should not have to jump through the ridiculous barriers of entry to consume the data my tax dollars have already paid for. That all said there is an incredible amount of work that needs to be done to make this happen. We may or may not figure it all out, but we’ll push the ball forward and I’d put all the money in my piggy bank on the model changing through one innovation or another.

Popularity: 9% [?]

The previous post on health care had some confusing and contradictory statistics. Without getting in to details of those, one can say that there is enough evidence (anectodal or otherwise) to show that the number of immigrants without insurance is not insubstantial. And yet its a moot point to say how much of that contributes to the lack of “affordable health care” in the U.S. In other words, there are many more factors that contribute to the health care problem than immigration alone.

As an aside, in my opinion, immigrants shoud not expect the host country to bear the burden of subsidizing or providing free health care. Any such expectation is sure to muddle the issue of how much they are part of the health care problem.

Just now realized that the term “affordable health care” is such a loaded one that its sure to open more cans of worms!

Popularity: 3% [?]

In response to the previous post, Uninsured in America – Certainly, there are many variables we could map to explore the issue of health care reform and access to insurance. Percents, levels, rates and different indicators – Each will tell a different aspect of the story and in whole, will provide a richer understanding of the issue. The list of related datasets in Geocommons that I am providing on my weekly Wednesday post is designed to allow anyone to go about this type exploration.

The idea to map percentages comes from an article I read last week that talks about a study that was just released by the Commonwealth Fund on health care in America (Aiming Higher: Results from a State Scoreboard on Health System Performance). They rank states based on 20 or so variables (one being percent uninsured). What caught my attention is that Texas ranks the highest in terms of percent uninsured. I was curious about this and what a more fine-grained geographical analysis would show and indeed the results of my mapping were consistent with the findings of the Commonwealth Fund study, at least in terms of the percent who are uninsured. The areas of the country where there are high percentages of individuals without health insurance are in the south and southwest.

When I initially created the map, it sparked another wave of curiosity. Are these immigrants who are the uninsured? What I found is that access to health care insurance is very much tied to immigration and the Hispanic population. Here are some of the statistics I found through the U.S. Census: 1. Immigrants (including naturalized citizens) comprise roughly 26% of the uninsured 2. Foreign borns are 2.5 more likely to not have insurance than native Americans 3. A little over 43% of non-citizens are without insurance and 4. Hispanics, the largest minority group in America, are 3 times more likely than non-Hispanic to have health insurance.

The map in the previous post, showing the numbers of uninsured by county sparked yet another wave of curiosity. I wondered if those counties that ranked high in terms of the numbers were also counties with high concentrations of immigrants and/or Hispanics. When I took a look at some numbers from the Census, I found that indeed, this is the case. A map of the number of uninsured immigrants by county would be an interesting next step in the exploration process!

And there’s the value of sharing analysis and maps online in a collaborative forum – I learned something. It looks like the debate on health care reform is very much tied to the debate on immigration.

Popularity: 5% [?]

In my opinion, percentages (in this case percentage of uninsured by county) tell a point of view that shows the non-native (immigrant) population along the U.S.-Mexico border is a major contributing factor to the problem of uninsured. In reality, nearly 45 million or so uninsured are scattered across major population centers in the U.S. When ranked by uninsured population, the top ten counties are:

1. Los Angeles Co., CA
2. Cook Co., IL
3. Harris Co., TX
4. Maricopa Co., AZ
5. Kings Co., NY
6. Orange Co., CA
7. San Diego Co., CA
8. Queens Co., NY
9. Dallas Co., TX
10. San Bernandino Co., CA

Nearly 10.5 million (23%) uninsured live in just 25 counties out of total 3,108 counties/jurisdictions in the lower 48. As part of disclosure, let me say this: I am a little skeptical about the whole issue of “Universal Health Care,” especially with federal govt playing the role of a mother hen. However, if there is going to be a political debate about the issue, then as a start, it would help to identify concentrations of uninsured based on actual numbers. The map below shows just that, pan around and explore the world of the uninsured.

I would not wish this on anybody, however, it would be interesting to explore spatial distribution of the unfortunate subset from the world of the insured who have gone bankrupt due to escalating health care cost when faced with life threatening diseases in their families. But that would have to wait for another post another day when such data is compiled!

Popularity: 3% [?]