Alfredo Covaleda,
Bogota, Colombia
Stephen Guerin,
Santa Fe, New Mexico, USA
James A. Trostle,
Trinity College, Hartford, Connecticut, USA
Fascinating display of global statistics on site, Gapminder The homepage currently has some dynamic displays related to Human Development Trends: 2005. Well worth watching, but be sure to scroll down the page to scan all the useful articles and presentations available.Then, perhaps saving the best for last, go to the Gapminder Tool at http://tools.google.com/gapminder. Note that you can play with the axes to change (a) what is graphed and (b) how it is graphed (log or linear), and hit the play button on the bottom to see how the numbers changed over the past years. [Thanks Patti Schank for this good tip.]
Subscribe or go straight to the graph.
Contact gapworld@gapminder.org with questions or suggestions for improvements.
From the good folks at Internet Scout:
Interesting new tool from the folks at Google. If Sketchup follows the evolutionary line of Google Maps, we can expect to see some interesting mash-ups in coming weeks. We are looking forward to some flowchart models that can be annotated with URL and comments. But until then….
Long-time IAJ friend George Dailey, ESRI's K-12 Education Program manager, contributes a fine, basic article to the current issue of ArcUser on how to normalize census data. It's would make an especially good handout to have while teaching.See “Normalizing Census Data Using ArcMap” athttp://www.esri.com/news/arcuser/0206/files/normalize2.pdf
Comes this interesting post on the Complexity and Social Networks Blog….
By Alexander Schellong
Social Network Theory and its principles are applied by more and more companies in a way that some of us might not be aware of yet. So what we buy, how we rate products/services, post in forums, pictures we upload or present of ourselves on the web is significantly influencing other, likeminded individuals. In return we are influenced by the network cluster we belong to for a specific habit and the like. Collaborative filtering is a key component of using social networks for different purposes. Further information can be found here. Below you will find a list of various industry and application examples:
Social Networking plattforms There are the obvious social networking online plattforms. Among them are the open business and personal contact manegement oriented like Tribe.net , openbc, friendster or the inivitation only communities like asmallworld. Either planned or already implemented users can take advantage of added services (search functionality, messaging) by paying a monthly fee 10< USD. Furthermore, there are the rather dating/partner match making plattforms like match or eharmony.
Retail/eCommerce Most of today's ecommerce sites use collaborative filtering to improve sales, cross-,up- and downselling. A prominent example are Amazon's recommendations based on various user behaviours on their website.
Music/Radio Tapping into our musical tastes Last FM, Genielab or Pandora present us with streaming music. Here the main business model lies in linking to the respective ecommerce sites like Apple's iTunes.
Books The same applies to the area of what we might want to read next which also serves ecommerce purposes.
Movies and moreMovieLens is a free service provided by GroupLens Research at the University of Minnesota. Whether, you want to book a hotel, whole vacation there are numerous examples of collaborative filtering apps on websites.
Pictures The most prominent example for sharing, managing and searching for pictures is Flickr or myspace. The latter gaining revenues from online-ads.
Search engines As I have elaborated in an earlier entry on google bombs the network structure (ties) play an important role in search engine algorithms.
Knowledge Base and OpenSource The online encyclopedia Wikipedia builds on the power of decentralized, voluntary collaboration building an enourmous depository of multi-language information. Whether it was the development of Linux, Mozilla/Firefox or MySQL all rely on and consist of social networks. Further examples of openSource projects can be found at Sourceforge.
SNA Consulting As we can see the character and concepts of networks is mainly utilized for recommendations. Actual applications of SNA is done by a few companies and consultants like Rob Cross, IBM, Orgnet or Visiblepath. These companies try to uncover the informal networks within organisations to improve knowledge sharing, initiate change or bridging silos.
Finally, you can always follow latest trends in social network analysis at PNG's subpage on SNA by Ines Mergel.
The Canadian Cartographic Association today points us to another interesting application of data collecting, analysis and charting. See: http://ccablog.blogspot.com/2006/03/index-of-economic-freedom.html
In recent weeks a sub-set of journalists have begun working with the problem of how do we quantify and illustrate speech. Or speeches. The Cyberjournalist.net newsletter (at the American Press Institute) reports:
They list commonly-occurring words in the speeches, giving greater visual weight to those that appear more often. Arranged side-by-side, they show some interesting contrasts (and similarities).”
Sorta interesting, when it's working. We applaude the attempt as a fine beginning, but what's missing is some context and explanation, the “So what?” factor. In fairness, the site's author recognizes the shortcoming, saying: “Of course, they lack any kind of context, but who needs that? (We're kidding.)“
On the other coast, ever-inventive Matt Ericson takes another bite of the State of the Union apple and offers up a more interesting visual, “The Words That Were Used.” [Look in the left column for link to graphic. But the toned “bubbles” actually show up better in print than online, so if you can't see it well online, try this (and may the copyright gods forgive us).
Three-Day Serieshttp://www.charlotte.com/mld/charlotte/news/special_packages/foreclosure/summary stolen from (http://www.thescoop.org/)Charlotte Mortgage ForeclosuresPosted by Derek on January 18th, 2006. Filed under Fed Data, Mapping. Lisa Hammersly Munn, Binyamin Appelbaum and Ted Mellnik of theCharlotte Observer have a three-part series on mortgage foreclosures,finding that home loan failures have more than quadrupled in MecklenburgCounty since 1999. More foreclosures are filed here, per person, than anyother county in the state. On average, 11 Mecklenburg houses are sold inforeclosure auctions every business day. The owners are evicted, theircredit ruined, and they face thousands in court fees and moving expenses. Included with the series is an interactive map of Mecklenburg Countyforeclosures and a sidebar reporting that local loans from the FederalHousing Administration are failing at almost twice the national rate.
From Complexity Digest:
Excerpts: You like a certain song and want to hear other tracks like it, but don't know how to find them? Ending the needle-in-a-haystack problem of searching for music on the Internet or even in your own hard drive is a new audio-based music information retrieval system. Currently under development by the SIMAC project, it is a major leap forward in the application of semantics to audio content, allowing songs to be described not just by artist, title and genre but by their actual musical properties such as rhythm, timbre, harmony, structure and instrumentation. This allows comparisons between songs to be made (…). Source: Semantic Descriptors To Help Should this come to fruition, might there be stories in patterns — regional patterns — in music? How could we map this? And when?
Kudos to Derek Willis and Adrian Holovaty of The Washington Post for the Washingtonpost.com site “U.S. Congress Votes Database.” One element we find of recent and special interest is the “late night votes” variables for both the House and Senate. With a little more probing and data slicing and dicing, it would make an interesting bit of visual statistics/infographics to do a longitudinal comparison of the time of votes in various congresses. This site/searchable database is a fine example of how investing in some basic data preparation can create the potential for a ton of stories. Why, for example, do Democrats have such a preponderance (18 out of 20) of Representatives on the “missed votes” list, but only 9 out of 20 on the similar list for the Senate? This is also a fine example of how a newspaper can do good things for itself while doing good things for the community and readers. This database gives the WP reporters and editors a quick look-up of Congressional activity, the kind of fact and detail that can enrich a story. At the same time, citizens can turn to this value-added form of the public record to answer their own questions. Derek Willis wrote to the news librarians listserv: “Folks, It's not part of a story or series, but the Post today launched a site that may prove useful to your newsrooms or even as an inspiration to learn Python: a congressional votes database that covers the 102nd-109th congresses (1991-present). Currently browsable, we're working on adding a search engine and other features to it. Adrian Holovaty, who works for washingtonpost.com, and I assembled the data and he built the web framework to display it. All of the data is gathered using Python, the database backend is PostgreSQL and the web framework is Django.”
