Archive for the ‘Mashup’ Category

Where 2.0 2010 Dates and Location Announced (O’Reilly)

Thursday, August 20th, 2009

where2-2010

Republished from O’Reilly.

March 30 – April 1, 2010 at the San Jose, Marriott, CA.

The 2010 O’Reilly Where 2.0 Conference Call for Participation Is Now Open

Become Location Enabled at Where 2.0

Location awareness is everywhere now, baked into our desktops, iPhones, cameras–even our oil rigs–right from the start. We expect our tools to sense and interpret data to help us locate and visualize everything from a new restaurant to the source of a new millennium plague. Who is leading the charge to the next mapping frontier? How are companies large and small jumping in change the rules in mid-game? And where is the money?

O’Reilly Media is seeking proposals for sessions and workshops from the builders and innovators in the location industry. Are you a mobile maven creating rich information overlays? A GIS veteran mashing up temporal data with maps? An open source developer hacking up a cool visualization tool? A CIO using location information to revamp a public transit system?

If you’re passionate about enabling location awareness in our lives and our work, we want to hear from you. Submit a proposal to speak at Where 2.0 by October 13, 2009.

Topics we’ll be exploring at Where 2.0 2010 include:

  • Mobile Trends and Devices
  • Rich Analysis Tools
  • Augmented Reality
  • Temporal Information
  • Government 2.0
  • Machine Learning
  • Crisis Mapping and Disease Awareness
  • Local Search
  • Cartography
  • Geo Support in Web Application Frameworks
  • GeoStack and GeoBrowsers
  • Mapping APIs
  • GeoTargeting
  • Data Management
  • Local Search and Advertising
  • Protocols and Formats

Where 2.0 is one of the world’s foremost events dedicated to exploring the emerging technologies in the geospatial industry. At Where 2.0, we expose the tools pushing the boundaries of the location frontier, track the emergence of new business models and services, and examine new sources of data and the platforms for collecting them.

Happening March 30-April 1, 2010 at the San Jose Marriott in San Jose, California, Where 2.0 brings together the people, projects, and issues building the new technological foundations and creating value in the location industry. Join with other developers, technologists, CTOs, researchers, geographers, academics, business developers, and entrepreneurs to debate and discuss what’s viable now, and what’s lurking just below the radar. Learn more about Where 2.0.

Important Dates

The submission deadline for all proposals is October 13, 2009.
Early registration opens in December 2009.
Standard registration begins February 2010.

More information at O’Reilly . . .

Being the Fastest Is Not Enough (InfoGraphicsNews)

Wednesday, August 19th, 2009

mapita22

[Editor’s note: You’ll start seeing more mashups on The Washington Post site the next month. Staff are being trained to use a new mashup maker tool I made that churns out decent maps in 5 minutes flat. Just like in print, normal rules about accuracy in reporting apply. The bottom line, don’t show more location detail than you know to be true, as this blog post from InfoGraphicsNews illustrates. Thanks Laris!]

Republished from the InfoGraphicsNews blog.
Original on 12/04/2008.

Yesterday, the terrosrist group ETA killed another person in Spain. In this cases, as most of the cases, internet media have the initative. The first idea is to place the new. Shw where it took place. But the problem is that in this kind of news all the information is changing all the time during the first hour, and the data are not accurate. Yesterday, we only knew that Ignacio Uria was killed while he was going to his favourite restaurant, Kiruri. We didn’t even knew if he came form his house or form his job.

The punch line:

None of those that placed the killing on a exact place were right.

Some rectified later, others didn’t even change it. Being the fastest can’t go before telling the truth. On reconstructions many editors use to say that “the reader know this is not exactly the truth, that we’re just guessing”. I don’t want the reader to not trust us. I prefer to have a reader who really think that when we say something we know it and we’re not guessing.
These are screenshots from some spanish websites two hours after the agencies gave the news:

Continue to view screenshots at InfoGraphicsNews blog . . .

How Do You Pronounce That Placename? (Forvo)

Friday, August 7th, 2009

forvologo

Forvo.com is an amusing site allowing users to upload recordings of how they say names (try Appalachian) around the world and compare it with others (and see everyone on a map). We all have accents, yo!

One Planet Many People: Atlas of Our Changing Environment (UNEP)

Friday, July 31st, 2009

unatlas

[Editor's note: Fun site from the United Nations Environment Programme highlighting changes in the natural environment with side-by-side remotely sensed imagery and full write up of each place. Done both in Google Maps and available as a Google Earth feed. Map is fairly decent.]

Republished from United Nations Environment Programme.

Increasing concern as to how human activities impact the Earth has led to documentation and quantification of environmental changes taking place on land, in the water, and in the air. Through a combination of ground photographs, current and historical satellite images, and narrative based on extensive scientific evidence, this publication illustrates how humans have altered their surroundings and continue to make observable and measurable changes to the global environment.

Continue to Interactive Atlas: Google Maps | Google Earth

Map: Where has Obama been in Washington? Where do you want him to go? (Wash Post)

Tuesday, July 21st, 2009

[Editor’s note: This interactive Google mashup builds off some code I programmed last year. I still like how the map snaps back to the original position after the info window closes. Kudos to Gene Thorp!]

Republished from The Washington Post.
Related articles:

According to whom you ask, President Obama has either embraced the D.C. area more than any other recent president or is falling well short of the full Washingtonian-status they had hoped the city-loving First Family might embrace. This map highlights most of the president’s stops in and around Washington to date, as well as some suggestions for the Obamas’ future dining from Post restaurant critic Tom Sietsema. Click on an icon to learn more about the president’s visit or Sietsema’s recommendation. And please use the comments box to suggest eateries, date-night venues, cultural events and other local outings for the president. We’ll add the most promising recommendations to the map on Monday.

Screenshot below. Interact with the original at The Washington Post . . .

obamaeats

Travellr: Behind the Scenes of our Region-Based Clusters (Google GeoDev)

Monday, July 6th, 2009

[Editor’s note: The age-old rule for cloropleth mapping that suggests aggregation by multi-scale areal units based on the map’s zoom level is slowly seeping into “clustering” for the point-based mashup geo community. This overview from Travellr published on the Google GeoDevelopers blog includes two illustrations that show the power of this technique. I used such a technique (different implementation) on The Washington Post’s recent swine flu mapping.]

Republished from Google GeoDevelopers Blog.
Monday, June 22, 2009

Recently, there has been a lot of interest in clustering algorithms. The client-side grid-based MarkerClusterer was released in the open source library this year, and various server-side algorithms were discussed in the Performance Tips I/O talk. We’ve invited the Travellr development team to give us insight on their unique regional clustering technique.

Travellr is a location aware answers service where people can ask travel-related questions about anywhere in the world. One of its features is a map-based interface to questions on the site using Google Maps.

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Figure 1. An example of the Travellr Map, showing question markers for Australia.

Clustering for usability
We learned that the best way to display markers without cluttering our map was to cluster our questions depending on how far you zoom in. If the user was looking at a map of the continents, we would cluster our questions into a marker for each continent. If the user zoomed-in to France we would then cluster our questions into a marker for each region or city that had questions. By clustering our data into cities, regions/states, countries, and continents, we could display relevant markers on the map depending on what zoom level the user was looking at.

Optimizing for Clustering
Our next challenge was how to extract clustered data from our database without causing excessive server load. Every time the user pans and zooms on the map, we need to query and fetch new clustered data in order to display the markers on the map. We also might have to limit the data if the user has selected a tag, as we’re only interested in a questions related to a topic (ie: “surfing”). To execute this in real-time would be painstakingly slow, as you would need to to cluster thousands of questions in thousands of locations with hundreds of tags on the fly. The answer? Pre-cluster your data of course!

Step 1. Structure your location data
When a question is asked about a city on Travellr, we also know its region/state, country and continent. We store more than 55,000 location points as a hierarchy, with each location “owning” its descendent nodes (and all of their data). Our locations are stored in a Modified Preorder Tree (also called Nested Sets). Modified Preorder Trees are a popular method of storing hierarchical data in a flat database table, having a focus on efficient data retrieval, and easy handling of sub trees. For each location we also keep a record of its depth within the tree, its location type (continent, country, region/state, or city), and its co-ordinates (retrieved using the Google Maps geocoder).

Step 2. Aggregate your data
We calculate aggregate data for every branch of our locations tree ahead of time. By storing aggregate data for cities, regions/states, countries, and continents, we provide an extremely fast and inexpensive method to query our locations database for any information regarding questions asked about a particular location. This data is updated every few minutes by a server-side task.

Our aggregations include:

  • Total question count for a location
  • Most popular tags for that location
  • Number of questions associated with each of those tags.

How we query our structured, aggregate data on the map
Whenever the user zooms or pans the map we fire off a query to our (unpublished ;) API with the tags they are searching for, the current zoom level, and the edge co-ordinates of the map’s bounding box. Based on the zoom level (Figure 2) we work out whether we want to display markers for continents, countries, states, or cities. We then send back the data for these markers and display them on the map.

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Figure 2. Clustering at different zoom levels (blue = continents, countries, pink = states, cities)

Everyone Wins
So what is the result of structuring and aggregating our data in such a way? It means that we have nicely organized, pre-clustered data that can be read from cheaply and easily. This allows us to provide a super-fast map interface for Travellr that puts minimal load on our infrastructure. Everyone is happy!

Comments or Questions?
We’d love to hear from you if you have any questions on how we did things, or suggestions or comments about Travellr’s map. This article was written by Travellr’s performance and scalability expert Michael Shaw (from Insight4) and our client-side scripting aficionado Jaidev Soin.

You can visit Travellr at www.travellr.com, or follow us on Twitter at twitter.com/travellr.

Using Data Visualization as a Reporting Tool Can Reveal Story’s Shape (Poynter)

Friday, June 26th, 2009

[Editor’s note: My colleague Sarah Cohen at The Washington Post was recently interviewed by Poynter about creating data visualizations to help readers understand and reporters research complicated stories. Sarah is on her way to a big new gig at Duke University.]

Republished from Poynter.
By Steve Myers at 6:12 AM on Apr. 14, 2009

Readers have come to rely on interactive presentations to understand complicated stories, using them to zoom in on periods of time and highlight areas of interest. Yet to investigate these stories, reporters often create what amounts to handcrafted investigative art: flow charts with circles and arrows, maps shaded with highlighters and stuck with pins.

More and more, though, some reporters are using data visualization tools to find the story hidden in the data. Those tools help them discover patterns and focus their reporting on particular places and times. Many of the presentations, which can have rough interfaces or less-than-sleek design, are never published.

At the recent National Institute for Computer-Assisted Reporting (NICAR) conference, Sarah Cohen, database editor for The Washington Post‘s investigative team — and recently named professor of computational journalism at Duke University — showed how reporters can use interactive graphics for their exploratory reporting. [PDF]

Cohen described this approach to me via e-mail. Here’s an edited version of our exchange.

Steve Myers: How would creating a digital, visual representation of data help a reporter? What does it tell you that you wouldn’t be able to find otherwise?

Sarah Cohen
Sarah Cohen

Sarah Cohen: The same way that visualizations and graphics help readers cut through a lot of clutter and display dense information in an efficient way. The most common things that early visualizations help with are place and time — two of the most important elements in reporting a complex story. Those two things are really hard to see in text. They’re really, really hard to see in combination. So the graphics can show you where to go to find your subjects or where to go to find the most typical subjects. They can also show you when the story you are trying to find peaked. Put them together, and you can start finding the very best examples for your story.

That’s pretty general, so let me give you a couple of examples. During a story on disaster payments in the farm subsidy system, we wanted to make sure that we went to places that had received the payments year after year after year. Using a database, we could find farms that had received multiple payments pretty easily. But looking at repeated images of density maps that I made of the payments, it was really obvious where to go — specific areas of North Dakota and Kansas.

Crop payments
Sarah Cohen/Poynter illustration
Cohen used density maps to figure out what areas of the country had received disaster payments year after year.


In another example, we were working last year on a story on practices used by landlords to empty their buildings, partly in order to avoid strict laws on condo conversions (visualizations: research version, published version. We knew one neighborhood of the city was Ground Zero — an area called Columbia Heights, in Northwest D.C. But making an interactive map with a slider that showed the timing, we could see that it was moving into other areas of the city, especially in Southeast. We could also quickly see that the most affluent areas of the city had none of them.

Continue reading at Poynter . . .

Bounding Boxes for World Countries (Berkeley GADM)

Tuesday, June 23rd, 2009

[Editor's note: Knowing the longitude-latitude (latLng) bounding box of a feature gives us a clue as to what map scale or zoom level is required to fit the feature into our display area and thus what base map scale set to draw from. While this image does not provide actual coordinates, it visually establishes what such bounding boxes look like (further refinements can be had with respect to crossing the 180° meridian, note New Zealand). ]

Republished from Berkeley GADM (Global Administrative Areas).

Here is a map of all countries and their bounding boxes (when using a lat/long “projection”), highlighting those countries that cross the international date line, and for which these bounding boxes make little sense (this map is provided for diversion only).

insidethebox

UK Addressing, The Non Golden Rules of Geo or Help! My County Doesn’t Exist (Yahoo!)

Monday, June 22nd, 2009

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[Editor's note: Amusing and practical example of geographic taxonomy, topology with the example of England versus United Kingdom.]

Republished from Yahoo! Geo.
By Gary Gale, Head of UK Engineering, Yahoo! Geo Technologies

George Bernard Shaw once said the golden rule is that there are no golden rules and at Geo Technologies we understand that there is no one golden rule for Geo and so we try to capture and express the world’s geography as it is used and called by the world’s people. Despite the pronouncement on golden rules, a significant proportion of the conversations we have with people about Geo lend themselves to the Six Non Golden Rules of Geo, namely that:

  1. Any attempt to codify a series of geo rules into a formal, one size fits all, taxonomy will fail due to Rule 2.
  2. Geo is bizarre, odd, eclectic and utterly human.
  3. People will in the main agree with Rule 1 with the exception of the rules governing their own region, area or country, which they will think are perfectly logical.
  4. People will, in the main, think that postal, administrative and colloquial hiearachies are one and the same thing and will overlap.
  5. Taking Rule 4 into account, they will then attempt to codify a one size fits all geo taxonomy.
  6. There is no Rule 6, see Rule 1.

I codified these rules after a conversation last week, via Twitter and Yahoo! Messenger, with Andrew Woods, a US based developer who was, understandably, confused by the vagaries of the how addresses work in the UK. Andrew’s blog contains the full context but can be distilled into three key questions:

  • If the country is The United Kingdom, how come the ISO 3166-2 code is GB?
  • If the country is The United Kingdom, is England a country?
  • If England is a country, do I use it in an address?

As a US developer, Andrew is naturally fluent with the US style of addressing, with all of its’ localised and regional exceptions. This is a good example of both Rules 3 and 4 in the real world; most people in the US will use number, street, city, State and ZIP for specifying an address. But how does this transfer to the UK? What’s the equivalent of a State … England, Scotland or Wales? Let’s try to answer some of these problems:

Continue reading at Yahoo! Geo . . .