Vector One’s Jeff Thurston discusses the representation part to his GIS series. He says that representation part is an integral feature and one of the primary functional capabilities of GIS. Thurston discusses the many ways GIS is represented, including tabulated spreadsheets, numerically instead of graphically, through maps, charts, etc. He also talks about visualization tools that ‘take GIS data output and use it to develop other forms of visualization.’

The Washington Post released a flashed based Google Map mashup called TimeSpace: World. The map is a compilation of world news from the newspaper, its online site – washingtonpost.com, PostGlobal, Foreign Policy magazine and other partner sites including The Associated Press. The coverage is represented by clusters around hot-spots on the map. Each cluster lets you view articles, blog posts, photos, videos and even reporter twitter feeds.

Microsoft Research India created a system called the Robust Location Search, which enables location addresses in structured formats from any country. Microsoft plans to add it into Window Live Local.

The unemployment is getting worse. “Initial jobless claims surged by 58,000 to 573,000 in the week ending Dec. 6, the highest level since 1982.” MSNBC created an interactive map that displays the unemployment rate by month for each state starting in September 2007.

Blogger added geotagging! Now the Blogger community can geotag blog entries and not just photo. Now feed readers, map applications and search engines can associate posts with their locations.

SlashGeo talks about the importance of GeoPresence, based on a piece by Ron Lake of Galdos, Inc. Ron said, “…a GeoPresence might be thought of as a visual and behavioural representative for yourself or your organization, not in a complete world of fantasy such as Second Life, but in some sort of approximation of the real world, the Virtual World. Furthermore, we can expect that this GeoPresence will reflect you or your organization more or less in real time.”

Karen Siderelis was named the first geographic officer (GIO) for the Department of Interior. Siderelis will guide the Federal Geographic Data Committee (FGDC), which coordinates the federal government’s GIS activities to provide information to people.

The MetaCarta Public Sector User Group established geotagging crime reports as one of the key applications realized by public safety organizations at their meeting yesterday. They highlighted the North Texas Fusion Centers (NTFC) as an example of how the police were able to detect cross border weapons along geographic corridors of the Texas and Mexico border by geotagging the reports to see how crime travels.

ITT released its first, color half-meter ground resolution image taken from the GeoEye-1 satellite. Check out the fusion image ‘created from blending the 0.41m panchromatic image and the 1.65m color image.’

Photo host Flickr announced a new addition to their existing features: geotagging. Users can now drag their photos to a Yahoo Map through a link provided in their profile. Flickr will still offer Organizr, and highly recommends using that tool for batch geotagging. The new feature will be used to easily tag single photos. Check out this link that has Beijing Flickr photos on top of OpenStreetMap based data. Interestingly, the base Yahoo map for Beijing has hardly any road data and no street names.

Russia-Georgia’s war has been mapped. The CatholicGauze has been keeping track of the battle locations as the war progresses. Both Google Maps and Live Maps are covering the battle areas, even though Google has been called out for not finding the correct data for regions in Georgia.

A post from Sean Gillies asks for distinction between “web GIS” and “Geoweb”. James Fee and Andrew commented on the post, saying that “WebGIS” is tools and technology while “geoweb” is a whole other “social web”.

1) people’s tags may be difficult for others to understand,
2) people may have tagged items inappropriately for others’ needs.

In short your users will not always implement tags in ways that are productive for the community – in the extreme resulting in Flickr’s 20 million unique tags. How many of those 20 million tags are misspelled words or so off the path they never get found.

In addition to the problems you encounter with folksonomies in general you have the further complications of geopspatial data. All geospatial data sets have location tags, but adding them in an unstructured way creates enough chaos that it is very difficult to leverage location tags in a thorough way. Secondly many potential users do not know the variety of geodata available. Put more simply they do not know what to search for, and having the ability to browse through data by topics is appealing.

Despite the downsides of folksonomies they are incredibly powerful and have been hugely effective in organizing vast amount of data on the web. So, as we worked on the next iteration of GeoCommons we started looking at possible hybrid approaches to folksonomies and hierarchies.

Specifically we looked at the two problems specific to geospatial data listed above 1) place tags and 2) organizing data for browsing. Solving the problems required both short term and long term solutions.

Fortunately we had a small advantage over many crowd sourced project in that we have a full time data team. They are a great group of folks that spend their day finding cool geodata and coming up with clever ways to organize it.

Through the data team and the other community members that contributed data to the first iteration of GeoCommons we had a big pool of data with a wide variety of tags to examine. What we found were some distinct trends in the tagging and titling of data. Across the data there were a commons set of tags that broke the data up into a useful set of distinct categories, but there were also many data sets that were tagged with elements that made them often indiscoverable. After the analysis we started to look at structures we could establish to help create self similarity in tagging that still had the flexibility to be adaptive.

The result was the creation of a location and topical taxonomy based on our existing corpus of data that has the intelligence to adapt as the content grows and evolves. I can’t go into the technical details in depth, but fundamentally the concept is to intelligently leverage the taxonomies and structures to provide suggestions to users to tag their data better.

In many cases this can be very simple – like providing tips on how to tag and title effectively to make your data more valuable to the community. For instance with titles we found across GeoCommons there were four key pieces of information used for datasets in the past.

1) Source name, 2) Original Name of Dataset from Source (or short description of dataset) 3) Geographic Area, 4) Time period of data

Examples:

Communicating this effectively to users is a great way to get better consistency across data contributions, while still allowing flexibility for users to be creative and bring in information that does fit the rigid mold of a hierarchy. Of course this is the most simple and you can get far more clever.

Del.icio.us for instance has a great feature that notifies a user they are putting in a new tag no one has used before and asking if that is what they meant to do. You can also suggest tags from your taxonomy that are semantically related to the data the user is contributing. This creates a consistency across tags that makes data easier to find as the system scales to larger volumes.

The nice thing about taxonomies as opposed to folksonomies is that they can be structured as trees, which means you can compute across them quite easily. With a solid and adaptive taxonomy in place you can go a long ways in intelligently guiding users towards creating better and more consistent tags. At least that is what we think and it will be fun to see how it works out after the launch.