Another Word For It Patrick Durusau on Topic Maps and Semantic Diversity

April 11, 2012

Open Street Map GPS users mapped

Filed under: GPS,Mapping,Maps,Open Street Map — Patrick Durusau @ 6:15 pm

Open Street Map GPS users mapped

From the post:

Open Street Map is the data source that keeps on giving. Most recently, the latest release has been a dump of GPS data from its contributors. These are the track files from Sat Nav systems which they users have sourced for the raw data behind OSM.

It’s a huge dataset: 55GB and 2.8bn items. And Guardian Datastore Flickr group user Steven Kay decided to try to visualise it.

This is the result – and it’s only an random sample of the whole. The heatmap shows a random sample of 1% of the points and their distribution, to show where GPS is used to upload data to OSM.

There are just short of 2.8 billion points, so the sample is nearly 28 million points. Red cells have the most points, blue cells have the fewest.

Great data set on its own but possibly the foundation for something even more interesting.

The intelligence types, who can’t analyze a small haystack effectively, want to build a bigger one: Building a Bigger Haystack.

Why not use GPS data such as this to create an “Intelligence Big Data Mining Test?” That is we assign significance to patterns in the data and see of the intelligence side can come up with the same answers. We can tell them what the answers are because they must still demonstrate how they got there, not just the answer.

April 9, 2012

Where am I, who am I?

Filed under: Mapping,Maps — Patrick Durusau @ 4:57 pm

Where am I, who am I?

Pete Warden writes:

Queequeg was a native of Rokovoko, an island far away to the West and South. It is not down in any map; true places never are.”

Where am I right now? Depending on who I’m talking to, I’m in SoMa, San Francisco, South Park, the City, or the Bay Area. What neighborhood is my apartment in? Craigslist had it down as Castro when it was listed. Long-time locals often describe it as Duboce Triangle, but people less concerned with fine differences lump it into the Lower Haight, since I’m only two blocks from Haight Street.

When I first started working with geographic data, I imagined this was a problem to be solved. There had to be a way to cut through the confusion and find a true definition, a clear answer to the question of “Where am I?”.

What I’ve come to realize over the last few years is that geography is a folksonomy. Sure, there’s political boundaries, but the only ones that people pay much attention to are states and countries. City limits don’t have much effect on people’s descriptions of where they live. Just take a look at this map of Los Angeles’ official boundaries:

Pete is onto a more general principle.

Semantics are folksonomy, the precision of which varies depending upon the reason for your interest and your community.

Biblical scholars split hairs, sorry, try to correct errors committed by others, by citing imagined nuances of languages used thousands of years ago. To the average person on the street, the Bible may as well have been written in King James English. Not that one is more precise than the other, just a different community and different habits for reading the text.

The question which community do you hail from and for what purpose are you asking about semantics? We can short-circuit a lot of discussion by recognition that communities vary in their semantics. Each to his/her own.

April 7, 2012

Rediscovering the World: Gridded Cartograms of Human and Physical Space

Filed under: Geographic Data,Mapping,Maps — Patrick Durusau @ 7:43 pm

Rediscovering the World: Gridded Cartograms of Human and Physical Space by Benjamin Hennig.

Abstract:

We need new maps’ is the central claim made in this thesis. In a world increasingly influenced by human action and interaction, we still rely heavily on mapping techniques that were invented to discover unknown places and explore our physical environment. Although the traditional concept of a map is currently being revived in digital environments, the underlying mapping approaches are not capable of making the complexity of human-environment relationships fully comprehensible.

Starting from how people can be put on the map in new ways, this thesis outlines the development of a novel technique that stretches a map according to quantitative data, such as population. The new maps are called gridded cartograms as the method is based on a grid onto which a density-equalising cartogram technique is applied. The underlying grid ensures the preservation of an accurate geographic reference to the real world. It allows the gridded cartograms to be used as basemaps onto which other information can be mapped. This applies to any geographic information from the human and physical environment. As demonstrated through the examples presented in this thesis, the new maps are not limited to showing population as a defining element for the transformation, but can show any quantitative geospatial data, such as wealth, rainfall, or even the environmental conditions of the oceans. The new maps also work at various scales, from a global perspective down to the scale of urban environments.

The gridded cartogram technique is proposed as a new global and local map projection that is a viable and versatile alternative to other conventional map projections. The maps based on this technique open up a wide range of potential new applications to rediscover the diverse geographies of the world. They have the potential to allow us to gain new perspectives through detailed cartographic depictions.

I found the reference to this dissertation in Fast Thinking and Slow Thinking Visualisation and thought it merited a high profile.

If you are interested in mapping, the history of mapping, or proposals for new ways to think about mapping projections, you will really appreciate this work.

Explore Geographic Coverage in Mapping Wikipedia

Filed under: Mapping,Maps,Ontopia,Wikipedia — Patrick Durusau @ 7:42 pm

Explore Geographic Coverage in Mapping Wikipedia

From the post:

TraceMedia, in collaboration with the Oxford Internet Institute, maps language use across Wikipedia in an interactive, fittingly named Mapping Wikipedia.

Simply select a language, a region, and the metric that you want to map, such as word count, number of authors, or the languages themselves, and you’ve got a view into “local knowledge production and representation” on the encyclopedia. Each dot represents an article with a link to the Wikipedia article. For the number of dots on the map, a maximum of 800,000, it works surprisingly without a hitch, other than the time it initially takes to load articles.

You need to follow the link to: Who represents the Arab world online? Mapping and measuring local knowledge production and representation in the Middle East and North Africa. The researchers are concerned with fairness and balance of coverage of the Arab world.

Rather than focusing on Wikipedia, an omnipresent resource on the WWW, I would rather have a mapping of who originates the news feeds more generally? Rather than focusing on who is absent. Moreover, I would ask why the Arab OPEC members have not been more effective at restoring balance in the news media?

April 5, 2012

Beautiful visualisation tool transforms maps into works of art

Filed under: Mapping,Maps — Patrick Durusau @ 3:38 pm

Beautiful visualisation tool transforms maps into works of art: Introducing Stamen maps, cartography with aesthetics at its heart

From the post:

Stamen maps, the second stage of the City Tracking project funded by the Knight News Challenge has just been released for public use.

This installment consists of three beautifully intricate mapping styles, which use OpenStreetMap data to display any area of the world* in a new and highly stylised layout.

Take a look at each of the designs below. You can click and drag the maps to view other locations.

More tools for better looking maps!

April 4, 2012

OpenStreetMap versus Google maps

Filed under: Mapping,Maps — Patrick Durusau @ 3:32 pm

OpenStreetMap versus Google maps

From the post:

Travelling to Sarajevo showed the Open Knowledge Foundation’s Lucy Chambers the overwhelming reach of crowdsourced open data

Lucy says nice things about both OpenStreetMap and Google maps.

I mention it as encouragement to try crowdsourced data in your semantic solutions where appropriate.

Depending on the subject, we are all parts of “crowds” of one sort or another.

March 29, 2012

Intro to Map Suite DynamoDB Extension Technology Preview

Filed under: Dynamo,Geo Analytics,Mapping — Patrick Durusau @ 6:40 pm

Intro to Map Suite DynamoDB Extension Technology Preview

Promotes Amazon’s DynamoDB, including pricing but an interesting presentation none the less.

A couple of suggestions:

The code mentioned in the presentation is unreadable. I am sure it worked at an actual presentation but doesn’t work on the web.

The extension is downloadable but requires MS Studio to be opened. Understand why there is a version for one of the more popular programming IDE’s but the product should not be restricted to that IDE.

Some resources that may be of interest:

http://thinkgeo.com/

Press Release on this extension.

Looking for feedback on the technology.

Great to be able to support GIS data robustly but the “killer” app for GIS data would be to integrate other data in real time.

For example, take a map of a major metropolitan area and integrate real time GIS coordinates from police and fire units, across jurisdictions during major public events. While at the same time integrating encounters, arrests, intelligence reports, both with each other as well as the GIS positions.

Mobile App Developer Competition (HaptiMap)

Filed under: Interface Research/Design,Mapping,Maps — Patrick Durusau @ 6:39 pm

Mobile App Developer Competition (HaptiMap)

From the website:

Win 4000 Euro, a smartphone or a tablet!

This competition is open for mobile apps, which demonstrate designs that can be used by a wide range of users and in a wide range of situations (also on the move). The designs can make use of visual (on-screen) elements, but they should also make significant use of the non-visual interaction channels. The competition is open both for newly developed apps as well as existing apps who are updated using the HaptiMap toolkit. To enter the competition, the app implementation must make use of the HaptiMap toolkit. Your app can rely on existing toolkit modules, but it is also possible extend or add appropriate modules (in line with the purpose of HaptiMap) into the toolkit.

Important dates:

The competition closes 15th of June 17.00 CET 2012. The winners will be announced at the HAID’12 workshop (http://www.haid.ws) 23-24 August 2012, Lund, Sweden.

In case you aren’t familiar with HaptiMap:

What is HaptiMap?

HaptiMap is an EU project which aims at making maps and location based services more accessible by using several senses like vision, hearing, and, particularly, touch. Enabling haptic access to mainstream map and LBS data allows more people to use them in a number of different environmental or individual circumstances. For example, when navigating in low-visibility (e.g., bright sunlight) and/or high noise environments, preferring to concentrate on riding your bike, sightseeing and/or listening to sounds, or when your visual and/or auditory senses are impaired (e.g., due to age).

If you think about it, what is being proposed is standard mapping but not using the standard (visual) channel.

March 11, 2012

Old-style mapping provides a new take on our poverty maps

Filed under: Mapping,Maps,Visualization — Patrick Durusau @ 8:10 pm

Old-style mapping provides a new take on our poverty maps

John Burn-Murdoch writes:

Mapping data is tricky. The normal approach – as we used with our poverty maps today – is to create a chloropleth – a map where areas are coloured. But there is another way – and it’s quite old. This intricate visualisation by Oliver O’Brien (via spatialanalysis.co.uk) illustrates the demographics of housing throughout Britain in a style dating back to the 19th Century. Echoing the work of philanthropist Charles Booth, the map highlights groups of buildings rather than block-areas. The result is a much more detailed visualisation, allowing viewers to drill down almost to household level.

The meaningful display of data isn’t a new task. I suspect there are a number of visualization techniques that lie in library stacks waiting to be re-discovered.

February 28, 2012

Map your Twitter Friends

Filed under: Mapping,Maps,Tweets — Patrick Durusau @ 10:44 pm

Map your Twitter Friends by Nathan Yau.

From the post:

You’d think that this would’ve been done by now, but this simple mashup does exactly what the title says. Just connect your Twitter account and the people you follow popup, with some simple clustering so that people don’t get all smushed together in one location.

Too bad the FBI’s social media mining contract will be secret. Wonder how much freely available capabilities will be?

Security requirements will drive up the cost. Like secure installations where the computers have R/W DVDs installed.

Not that I carry a brief for any government, other than paying ones, but I do dislike incompetence, on any side.

Really old maps online

Filed under: Mapping,Maps — Patrick Durusau @ 10:44 pm

Really old maps online by Nathan Yau.

From the post:

Maps have been around for a long time, but you might not know it looking online. It can be hard to find them. Old Maps Online, a project by The Great Britain Historical GIS Project and Klokan Technologies GmbH, Switzerland, is a catalog of just that.

I do wonder when the organization of information in its various forms will be recognized as maps? Or for that matter, visualized as maps?

February 21, 2012

Maps with R

Filed under: Mapping,Maps,R — Patrick Durusau @ 8:01 pm

Maps with R (I)

From the post:

This is the first post of a short series to show some code I have learnt to produce maps with R.

Some time ago I found this infographic from The New York Times (via this page) and I wondered how a multivariate choropleth map could be produced with R. Here is the code I have arranged to show the results of the last Spanish general elections in a similar fashion.

Which was followed by:

Maps with R (II)

In my last post I described how to produce a multivariate choropleth map with R. Now I will show how to create a map from raster files. One of them is a factor which will group the values of the other one. Thus, once again, I will superpose several groups in the same map.

What do you want to map today?

February 16, 2012

Metrography: London Reshaped to Match the Classic Tube Map

Filed under: Mapping,Maps,Visualization — Patrick Durusau @ 6:58 pm

Metrography: London Reshaped to Match the Classic Tube Map.

From the post:

In Metrography [looksgood.de], interaction design students Benedikt Groß [looksgood.de] and Bertrand Clerc [bertrandclerc.com] and presents us with an alternative view on London. What if the street map was reshaped according to the positions of the tube stations as placed on the Tube map?

The result is a ‘warped’ or ‘morphed’ map of London, that highlights the discrepancy between the stylized metro map and the geographically correct depiction. The resulting high-resolution prints can be viewed online in all detail.

I am not sure I agree there is a “geographically correct depiction” of London or any other locale. Depends on whose “geography” you are using. We are so schooled in some depictions being “correct,” that we fail to speak up when lines of advantage/disadvantage are being drawn. That is “just the way things fall on the map,” no personal motive involved. Right.

Topic maps are one way to empower alternative views, geographic or otherwise.

February 12, 2012

New mapping tools bring public health surveillance to the masses

Filed under: Collation,Health care,Mapping,Maps,Marketing — Patrick Durusau @ 5:13 pm

New mapping tools bring public health surveillance to the masses by Kim Krisberg.

From the post:

Many of us probably look into cyberspace and are overwhelmed with its unwieldy amounts of never-ending information. John Brownstein, on the other hand, sees points on a map.

Brownstein is the co-founder of HealthMap, a team of researchers, epidemiologists and software developers at Children’s Hospital Boston who use online sources to track disease outbreaks and deliver real-time surveillance on emerging public health threats. But instead of depending wholly on traditional methods of public health data collection and official reports to create maps, HealthMap enlists helps from, well, just about everybody.

“We recognized that collecting data in more traditional ways can sometimes be difficult and the flow of information can take a while,” said Brownstein, also an assistant professor of pediatrics at Harvard Medical School. “So, the question was how to collect data outside the health care structure to serve public health and the general public.”

HealthMap, which debuted in 2006, scours the Internet for relevant information, aggregating data from online news services, eyewitness reports, professional discussion rooms and official sources. The result? The possibility to map disease trends in places where no public health or health care infrastructures even exist, Brownstein told me. And because HealthMap works non-stop, continually monitoring, sorting and visualizing online information, the system can also serve as an early warning system for disease outbreaks.

You need to read this post and then visit HealthMap.

Collating information from diverse sources is a mainstay of epidemiology.

Topic maps are an effort to bring the benefits of collating information from diverse sources to other fields.

(I first saw this on Beyond Search.)

February 3, 2012

Great Maps with ggplot2

Filed under: Ggplot2,Graphics,Mapping,Maps — Patrick Durusau @ 5:03 pm

Great Maps with ggplot2

I have mentioned ggplot2 before but this item caught my eye because of its skillful use with a map of cycle tours of London.

Not that I intend to take a cycle tour of London any time soon but it occurs to me that creating maps to resturants, entertainment, etc., from conference sites would be a good use of it. Coupled with a topic map, as the conference progresses, reviews/tweets about those locations could become available to other participants.

Other geographic locations/information could be plotted as well.

January 11, 2012

Designing Google Maps

Filed under: Geographic Information Retrieval,Mapping,Maps — Patrick Durusau @ 8:07 pm

Designing Google Maps by Nathan Yau.

From the post:

Google Maps is one of Google’s best applications, but the time, energy, and thought put into designing it often goes unnoticed because of how easy it is to use, for a variety of purposes. Willem Van Lancker, a user experience and visual designer for Google Maps, describes the process of building a map application — color scheme, icons, typography, and “Googley-ness” — that practically everyone can use, worldwide.

I don’t normally disagree with anything Nathan says, particularly about design but I have to depart from him on why we don’t notice the excellence of Google Maps.

I think we have become accustomed to its excellence and since we don’t look elsewhere (most of us), then we don’t notice that it isn’t commonplace.

In fact for most of us it is a universe with one inhabitant, Google Maps.

That takes a lot of very hard work and skill.

The question is do you have the chops to make your topic map of one or more infoverses the “only” inhabitant, by user choice?

January 8, 2012

Mapping the Iowa caucus results: how it’s done with R

Filed under: Mapping,Maps,R — Patrick Durusau @ 7:22 pm

Mapping the Iowa caucus results: how it’s done with R

David Smith writes:

If you’ve been following the presidential primary process here in the US, you’ve probably seen many maps of the results of the Iowa caucuses by now (such as this infamous one from Fox News). But you might be interested to learn how such maps can be made using the R language.

BTW, David includes pointers to Offensive Politics, which self-describes as:

offensive politics uses technology and math to help progressives develop strategy, raise money and target voters to win elections.

A number of interesting projects and data sets that could be used with topic maps.

Other sources of political data, techniques or software?

January 2, 2012

Clickstream Data Yields High-Resolution Maps of Science

Filed under: Citation Indexing,Mapping,Maps,Visualization — Patrick Durusau @ 6:30 pm

Clickstream Data Yields High-Resolution Maps of Science Citation: Bollen J, Van de Sompel H, Hagberg A, Bettencourt L, Chute R, et al. (2009) Clickstream Data Yields High-Resolution Maps of Science. PLoS ONE 4(3): e4803. doi:10.1371/journal.pone.0004803.

A bit dated but interesting none the less:

Abstract

Background

Intricate maps of science have been created from citation data to visualize the structure of scientific activity. However, most scientific publications are now accessed online. Scholarly web portals record detailed log data at a scale that exceeds the number of all existing citations combined. Such log data is recorded immediately upon publication and keeps track of the sequences of user requests (clickstreams) that are issued by a variety of users across many different domains. Given these advantages of log datasets over citation data, we investigate whether they can produce high-resolution, more current maps of science.

Methodology

Over the course of 2007 and 2008, we collected nearly 1 billion user interactions recorded by the scholarly web portals of some of the most significant publishers, aggregators and institutional consortia. The resulting reference data set covers a significant part of world-wide use of scholarly web portals in 2006, and provides a balanced coverage of the humanities, social sciences, and natural sciences. A journal clickstream model, i.e. a first-order Markov chain, was extracted from the sequences of user interactions in the logs. The clickstream model was validated by comparing it to the Getty Research Institute’s Architecture and Art Thesaurus. The resulting model was visualized as a journal network that outlines the relationships between various scientific domains and clarifies the connection of the social sciences and humanities to the natural sciences.

Conclusions

Maps of science resulting from large-scale clickstream data provide a detailed, contemporary view of scientific activity and correct the underrepresentation of the social sciences and humanities that is commonly found in citation data.

An improvement over traditional citation analysis but it seems to be on the coarse side to me.

That is to say users don’t request nor do authors cite papers as a whole. In other words, there are any number of ideas in a particular paper which may merit citation and a user or author may be interested in only one.

Tracing the lineage of an idea should be getting easier, yet I have the uneasy feeling that it is becoming more difficult.

Yes?

December 22, 2011

Experimental isarithmic maps visualise electoral data

Filed under: Mapping,Maps,Visualization — Patrick Durusau @ 7:40 pm

Experimental isarithmic maps visualise electoral data

From the post:

David B. Sparks, a fifth-year PhD candidate in the Department of Political Science at Duke University, has today published a fascinating set of experiments using ‘Isarithmic’ maps to visualise US party identification. Isarithmic maps are essentially topographic/contour maps and offer an alternative approach to plotting geo-spatial data using choropleth maps. This is a particularly interesting approach for the US with its extreme population patterns.

Very impressive work. Read this post and then David’s original.

FYI:

Choropleth maps use city, county, etc. boundaries, within which colors appear.

Isarithmic maps use color to present the same information but without the legal boundaries that appear in choropleth maps.

December 21, 2011

Opaque Attribute Alignment

Filed under: Mapping,Ontology — Patrick Durusau @ 7:22 pm

Opaque Attribute Alignment by Jennifer Sleeman, Rafael Alonso, Hua Li, Art Pope, and Antonio Badia.

Abstract:

Ontology alignment describes a process of mapping ontological concepts, classes and attributes between different ontologies providing a way to achieve interoperability. While there has been considerable research in this area, most approaches that rely upon the alignment of attributes use label based string comparisons of property names. The ability to process opaque or non-interpreted attribute names is a necessary component of attribute alignment. We describe a new attribute alignment approach to support ontology alignment that uses the density estimation as a means for determining alignment among objects. Using the combination of similarity hashing, Kernel Density Estimation (KDE) and Cross entropy, we are able to show promising F-Measure scores using the standard Ontology Alignment Evaluation Initiative (OAEI) 2011 benchmark.

Just in case you run across different ontologies covering the same area, however unlikely that seems 10+ years after the appearance of the Semantic Web.

December 18, 2011

Subway Map Visualization jQuery Plugin

Filed under: JQuery,Mapping,Maps,Visualization — Patrick Durusau @ 8:47 pm

Subway Map Visualization jQuery Plugin by Nik Kalyani.

From the post:

I have always been fascinated by the visual clarity of the London Underground map. Given the number of cities that have adopted this mapping approach for their own subway systems, clearly this is a popular opinion. At a conference some years back, I saw a poster for the Yahoo! Developer Services. They had taken the concept of a subway map and applied it to create a YDN Metro Map. Once again, I was in awe of the visual clarity of this map in helping one understand the various Yahoo! services and how they inter-related with each other. I thought it would be awesome if there were a pseudo-programmatic way in which to render such maps to convey real-world ecosystems. A few examples I can think of:

  • University departments, offices, student groups
  • Government
  • Open Source projects
  • Internet startups by category

More examples on this blog: Ten Examples of the Subway Map Metaphor.

Fast-forward to now. Finally, with the advent of HTML5 <canvas> element and jQuery, I felt it was now possible to implement this in a way that with a little bit of effort, anyone who knows HTML can easily create a subway map. I felt a jQuery plugin was the way to go as I had never created one before and also it seemed like the most well-suited for the task.

A complete step-by-step example follows and is the sort of documentation that while difficult to write, saves every user of the software time further down the road.

The plug-in has any number of uses, a traditional public transportation map for your locale or as used by the author, a map that lays out a software project.

If you use this for a software project, you will need to make your own icons for derailment, track hazards and the causes of the same. 😉

Error Handling, Validation and Cleansing with Semantic Types and Mappings

Filed under: Expressor,Mapping,Semantics,Types — Patrick Durusau @ 8:41 pm

Error Handling, Validation and Cleansing with Semantic Types and Mappings by Michael Tarallo.

From the post:

expressor ETL applications can setup data validation rules and error handling in a few ways. The traditional approach with many ETL tools is to build in the rules using the various ETL operators. A more streamlined approached is to also use the power of expressor Semantic Mappings and Semantic Types.

  • Semantic Mappings specify how a variety of characteristics are to be handled when string, number, and date-time data types are mapped from the physical schema (your source) to the logical semantic layer known as the Semantic Type.
  • Semantic Types allow you to define, in business terms, how you want the data and the data model to be represented.

The use of these methods both provide a means of attribute data validation and invoking corrective actions if rules are violated.

  • Data Validation rules can be in the form of pattern matching, value ranges, character lengths, formatting, currency and other specific data type constraints.
  • Corrective Actions can be in the form of null, default and correction value replacements as well as specific operator handling to either skip records or reject them to another operator.

NOTE: Semantic Mapping rules are applied first before Semantic Type rules.

Read more here:

I am still trying to find time to test at least the community edition of the software.

What “extra” time I have now is being soaked up configuring/patching Eclipse to build Nutch, to correct a known problem between Nutch and Solr. I suspect you could sell a packaged version of open source software that has all the paths and classes hard coded into the software. No more setting paths, having inconsistent library versions, etc. Just unpack and run. Store data in separate directory. New version comes out, simply rm – R on the install directory and unpack the new one. That should also include the “.” files. Configuration/patching isn’t a good use of anyone’s time. (Unless you want to sell the results. 😉 )

But I will get to it! Unless someone beats me to it and wants to send me a link to their post that I can cite and credit on my blog.


Two things I would change about Michael’s blog:

Prerequisite: Knowledge of expressor Studio and dataflows. You can find tutorials and documentation here

To read:

Prerequisites:

  • expressor software (community or 30-day free trial) here.
  • Knowledge of expressor Studio and dataflows. You can find tutorials and documentation here

And, well, not Michael’s blog but on the expressor download page, if the desktop/community edition is “expressor Studio” then call it that on the download page.

Don’t use different names for a software package and expect users to sort it out. Not if you want to encourage downloads and sales anyway. Surveys show you have to wait until they are paying customers to start abusing them. 😉

December 15, 2011

Google Map Maker Opens Its Editing Tools To Everyone

Filed under: Mapping,Maps — Patrick Durusau @ 7:50 pm

Google Map Maker Opens Its Editing Tools To Everyone By Jon Mitchell.

From the post:

Google announced a major redesign of Google Map Maker today. This is the tool that allows anyone to propose edits to the live Google map, so that locals can offer more detail than Google’s own teams can provide. The new tools offer simple ways to add and edit places, roads and paths, as well as reviewing the edits of others.

That peer review element is key to Google Maps’ new direction. In September, Google rearranged the Map Maker review process, deputizing regional expert reviewers to expand its capacity to handle crowd-sourced edits. Today’s new tools take that a step further, allowing anyone to review proposed edits before they’re incorporated into the live map.

Is there a lesson for crowd-topic map here?

Or do we have to go through the painful cycles of peer review + editors, only to eventually find that the impact on quality is nearly nil? At least for public maps. Speciality maps, where you have to at least know the domain, may, emphasis on may, be a different issue.

If you are a professional in a field, consider how many “peer-reviewed” articles from twenty (20) years ago are still cited today? They were supposed to be the best papers to be read at a conference or published in your flagship journal. Yes?

Some still are cited. Now that’s peer review. But it took twenty years to kick in.

I suspect the real issue for most topic maps is going to be too few contributors and not too many of the unwashed.

Mapping, like vocabularies, is a question of who gets to decide.

November 24, 2011

ASTER Global Digital Elevation Model (ASTER GDEM)

Filed under: Geographic Data,Geographic Information Retrieval,Mapping — Patrick Durusau @ 3:42 pm

ASTER Global Digital Elevation Model (ASTER GDEM)

From the webpage:

ASTER GDEM is an easy-to-use, highly accurate DEM covering all the land on earth, and available to all users regardless of size or location of their target areas.

Anyone can easily use the ASTER GDEM to display a bird’s-eye-view map or run a flight simulation, and this should realize visually sophisticated maps. By utilizing the ASTER GDEM as a platform, institutions specialized in disaster monitoring, hydrology, energy, environmental monitoring etc. can perform more advanced analysis.

In addition to the data, there is a GDEM viewer (freeware) at this site.

All that is missing is your topic map and you.

October 24, 2011

MUTU: An Analysis Tool…

Filed under: Mapping,Ontology — Patrick Durusau @ 6:44 pm

MUTU: An Analysis Tool for Maintaining a System of Hierarchically Linked Ontologies (pdf)

Abstract

We consider ontology evolution in a system of light-weight Linked Data ontologies, aligned with each other to form a larger ontology system. When one ontology changes, the human editor must keep track of the actual changes and of the modifications needed in the related ontologies in order to keep the system consistent. This paper presents an analysis tool MUTU, by which such changes and their potential effects on other ontologies can be found. Such an analysis is useful for the ontology editors for understanding the differences between ontology versions, and for updating linked ontologies when changes occurred in other components of an ontology system.

Not available on the web, yet, but sounds interesting.

October 23, 2011

Tweet Topic Explorer

Filed under: Mapping,Visualization — Patrick Durusau @ 7:22 pm

Tweet Topic Explorer by Jeff Clark.

From the post:

One problem I face on a daily basis is to decide for a given Twitter account whether I want to follow it or not. I consider many factors when making the decision such as language of their tweets, frequency, whether they interact on twitter with other people I admire, or if I have some personal or geographic connection with them. But the most critical factor for me is whether they tweet about things that match my interests. Sometimes you can get a hint about this by looking at their short one line twitter bio but the best way is usually to scan their latest tweets.

I have created a new tool to help see which topics a person tweets about most often. It also shows the other twitter users that are mentioned most frequently in their tweets. I call it the Tweet Topic Explorer. I’m using the recently described Word Cluster Diagrams to show the most frequently used words in their tweets and how they are grouped together. This example below is for my own account, @JeffClark, and shows one word cluster containing twitter,data, visualization, list, venn, and streamgraph. Another group has word, cloud, shaped, post etc. It’s a bit hard to see in this small image but there is a cluster about Toronto where I live and mentions of run, marathon, soccer. Also, there are bubbles for some of the people on Twitter I mention the most often: @flowingdata, @eagereyes, @blprnt, @moritz_stefaner, @dougpete.

This is an interesting exercise in visualization and potentially a very useful tool.

The US ZIPScribble Map

Filed under: Mapping,Maps — Patrick Durusau @ 7:22 pm

The US ZIPScribble Map

From the post:

What would happen if you were to connect all the ZIP codes in the US in ascending order? Is there a system behind the assignment of ZIP codes? Are they organized in a grid? The result is surprising and much more interesting than expected.

The idea for the ZIPScribble came from playing with Ben Fry’s excellent zipdecode. That little applet allows you to explore the ZIP codes interactively, and reveals some very interesting patterns. What it does not give you, however, is an idea of the overall structure of the ZIP space. Jeffrey Heer has reimplemented zipdecode using his prefuse toolkit, and provides a file containing ZIP codes and coordinates. So off I went on a little programming exercise to see what simply connecting the dots would do.

Not recent (2006) but an interesting exercise. Serves as encouragement to map data to see what, if any, interesting patterns result.

October 1, 2011

Web Schemas Task Force

Filed under: Mapping,Schema,W3C — Patrick Durusau @ 8:29 pm

Web Schemas Task Force, chaired by R.V. Guha (Google).

Here is your opportunity to participate in some very important work at the W3C without a W3C membership.

From the wiki page:

This is the main Wiki page for W3C’s Semantic Web Interest Group Web Schemas task force.

The taskforce chair is R.V.Guha (Google).

In scope include collaborations on mappings, tools, extensibility and cross-syntax interoperability. An HTML Data group is nearby; detailed discussion about Web data syntax belongs there.

See the charter for more details.

The group uses the public-vocabs@w3.org mailing list

  • See public-vocabs@w3.org archives
  • To subscribe, send a message to public-vocabs-request@w3.org with Subject: subscribe (see lists.w3.org for more details).
  • If you are new to the W3C community, you will need to go through the archive approval process before your posts show up in the archives.
  • To edit this wiki, you’ll need a W3C account; these are available to all

Groups who maintain Web Schemas are welcome to use this forum as a feedback channel, in additional to whatever independent mechanisms they also offer.

The following from the charter makes me think that topic maps may be relevant to the task at hand:

Participants are encouraged to use the group to take practical steps towards interoperability amongst diverse schemas, e.g. through development of mappings, extensions and supporting tools. Those participants who maintain vocabularies in any format designed for wide-scale public Web use are welcome to also to participate in the group as a ‘feedback channel’, including practicalities around syntax, encoding and extensibility (which will be relayed to other W3C groups as appropriate).

September 30, 2011

Semantic Integration: N-Squared to N+1 (and decentralized)

Filed under: Data Integration,Mapping,Marketing,Semantics,TMDM,Topic Maps — Patrick Durusau @ 7:02 pm

Data Integration: The Relational Logic Approach pays homage to what is called the N-squared problem. The premise of N-squared for data integration is that every distinct identification must be mapped to every other distinct identification. Here is a graphic of the N-squared problem.

Two usual responses, depending upon the proposed solution.

First, get thee to a master schema (probably the most common). That is map every distinct data source to a common schema and all clients have to interact with that one schema. Case closed. Except data sources come and go, as do clients so there is maintenance overhead. Maintenance can take time to agree on updates.

Second, no system integrates every other possible source of data, so the fear of N-squared is greatly exaggerated. Not unlike the sudden rush for “big data” solutions whether the client has “big data” or not. Who would want to admit to having “medium” or even “small” data?

The third response that is of topic maps. The assumption that every identification must map to every other identification means things get ugly in a hurry. But topic maps question the premise of the N-Squared problem, that every identification must map to every other identification.

Here is an illustration of how five separate topic maps, with five different identifications of a popular comic book character (Superman), can be combined and yet avoid the N-Squared problem. In fact, topic maps offer an N+1 solution to the problem.

Each snippet, written in Compact Topic Map (CTM) syntax represents a separate topic map.


en-superman
http://en.wikipedia.org/wiki/Super_man ;
- "Superman" ;
- altname: "Clark Kent" .

***


de-superman
http://de.wikipedia.org/wiki/Superman ;
- "Superman" ;
- birthname: "Kal-El" .

***


fr-superman
http://fr.wikipedia.org/wiki/Superman ;
- "Superman" ;
birthplace: "Krypton" .

***


it-superman
http://it.wikipedia.org/wiki/Superman ;
- "Superman" ;
- altname: "Man of Steel" .

***


eo-superman
http://eo.wikipedia.org/wiki/Superman ;
- "Superman" ;
- altname: "Clark Joseph Kent" .

Copied into a common file, superman-N-squared.ctm, nothing happens. That’s because they all have different subject identifiers. What if I add to the file/topic map, the following topic:


superman
http://en.wikipedia.org/wiki/Super_man ;
http://de.wikipedia.org/wiki/Superman ;
http://fr.wikipedia.org/wiki/Superman ;
http://it.wikipedia.org/wiki/Superman ;
http://eo.wikipedia.org/wiki/Superman .

Results in the file, superman-N-squared-solution.ctm.

Ooooh.

Or an author know one other identifier. So long as any group of authors uses at least one common identifier between any two maps, it results in the merger of their separate topic maps. (Ordering of the merges may be an issue.)

Another way to say that is that the trigger for merging of identifications is decentralized.

Which gives you a lot more eyes on the data, potential subjects and relationships between subjects.

PS: Did you know that the English and German versions gives Superman’s cover name as “Clark Kent,” while the French, Italian and Esperanto versions give his cover name as “Clark Joeseph Kent?”

PPS: The files are both here, Superman-Semantics-01.zip.

September 14, 2011

Simple Search Is Not Enough!! (Homeland Security)

Filed under: Mapping,Searching — Patrick Durusau @ 7:00 pm

Simple Search Is Not Enough!! Map Necessity by Luc Quoniam

Very pictorial review of why simple search is inadequate.

Topical too since the examples all concern “homeland security.”

« Newer PostsOlder Posts »

Powered by WordPress