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

September 24, 2012

Foundation grants $575,000 for new OpenStreetMap tools

Filed under: Geographic Data,Mapping,Maps,Open Street Map — Patrick Durusau @ 5:22 pm

Foundation grants $575,000 for new OpenStreetMap tools

From the post:

The Knight Foundation has awarded a $575,000 grant to Washington-DC-based data visualisation and mapping firm Development Seed to work on new tools for OpenStreetMap (OSM). The Knight Foundation is a non-profit organisation dedicated to supporting quality journalism, media innovation and engaging communities. The award is one of six made by the Knight Foundation as part of Knight News Challenge: Data.

The funding will be used by developers from MapBox, part of Development Seed that designs maps using OSM data, to create three new open source tools for the OSM project to “lower the threshold for first time contributors”, while also making data “easier to consume by providing a bandwidth optimised data delivery system”.

Topic maps with geographic data are a sub-set of topic maps over all but its an important use case. And it is easy for people to relate to a “map” that looks like a “map.” Takes less mental effort. (One of those “slow” thinking things.) 😉

Looking forward to more good things to come from OpenStreetMaps!

September 21, 2012

Easy and customizable maps with TileMill

Filed under: Mapping,Maps — Patrick Durusau @ 7:18 pm

Easy and customizable maps with TileMill by Nathan Yau.

From the post:

I’m late to this party. TileMill, by mapping platform MapBox, is open source software that lets you quickly and easily create and edit maps. It’s available for OS X, Windows, and Ubuntu. Just download and install the program, and then load a shapefile for your point of interest.

For those unfamiliar with shapefiles, it’s a file format that describes geospatial data, such as polygons (e.g. countries), lines (e.g. roads), and points (e.g. landmarks), and they’re pretty easy to find these days. For example, you can download detailed shapefiles for roads, bodies of water, and blocks in the United States from the Census Bureau in just a few clicks.

Very cool!

Makes me wonder about shapefiles and relating information to them as information products.

You can download a road shapefile but does it include the road blocking accidents for the last five (5) years?

September 16, 2012

In Defense of the Power of Paper [Geography of Arguments/Information]

Filed under: Geography,Mapping,Maps,Marketing — Patrick Durusau @ 10:33 am

In her recent editorial, In Defense of the Power of Paper, Phyllis Korkk quotes Richard H. R. Harper saying:

Reading a long document on paper rather than on a computer screen helps people “better understand the geography of the argument contained within,” said Richard H. R. Harper, a principal researcher for Microsoft in Cambridge, England, and co-author with Abigail J. Sellen of “The Myth of the Paperless Office,” published in 2001.

Today’s workers are often navigating through multiple objects in complex ways and creating new documents as well, Mr. Harper said. Using more than one computer screen can be helpful for all this cognitive juggling. But when workers are going back and forth between points in a longer document, it can be more efficient to read on paper, he said. (emphasis added)

To “…understand the geography of the argument….”

I rather like that.

For all the debates about pointing, response codes, locators, identifiers, etc., on the web, all that was every at stake was document as blob.

Our “document as blob” schemes missed:

  • Complex complex relationships between documents
  • Tracking influences on both authors and readers
  • Their continuing but changing roles in the social life of information, and
  • The geography of arguments they contain (with at least as much complexity as documents as blobs).

Others may not be interested in the geography of arguments/information in your documents.

What about you?

Topic maps can help you break the “document as blob” barrier.

With topic maps you can plot the geography of/in your documents.

Interested?

September 11, 2012

XML-Print 1.0

Filed under: Mapping,Visualization,XML — Patrick Durusau @ 2:46 pm

Prof. Marc W. KĂźster announced XML-Print 1.0 this week, “…an open source XML formatter designated especially for the needs of the Digital Humanties.”

Mapping from “…semantic structures to typesetting styles….” (from below)

We have always mapped from semantic structures to typesetting styles, but this time it will be explicit.

Consider whether you need “transformation” (implies a static file output) or merely a “view” for some purpose, such as printing?

Both require mappings but the later keeps your options open as it were.

Enjoy!

XML-Print allows the end user to directly interact with semantically annotated data. It consists of two independent, but well-integrated components, an Eclipse-based front-end that enables the user to map their semantic structures to typesetting styles, and the typesetting engine proper that produces the PDF based on this mapping. Both components build as much as possible on existing standards such as XML, XSL-T and XSL-FO and extend those only where absolutely necessary, e.g. for the handling of critical apparatuses.

XML-Print is a DFG-supported joint project of the FH Worms (Prof. Marc W. KĂźster) and the University of Trier (Prof. Claudine Moulin) in collaboration wiht the TU Darmstadt (Prof. Andrea Rapp). It is released under the Eclipse Public Licence (EPL) for the front-end and the Affero General Public Licence (APGL) for the typesetting engine. The project is currently roughly half-way through its intended duration. In its final incarnation the PDF that is produced will satisfy the full set of requirements for the typesetting of (amongst others) critical editions including critical apparatuses, multicolumn synoptic texts and bidirectional text. At this stage it can already handle basic formatting as well as multiple apparatuses, albeit still with some restrictions and rough edges. It is work in progress with new releases coming out regularly.

If you have questions, please do not hesitate to contact us via our website http://www.xmlprint.eu or directly to print@uni-trier.de. Any and all feedback is welcome. Moreover, if you know some people you think could benefit from XML-Print, please feel free to spread the news amongst your peers.

Project homepage: http://www.xmlprint.eu
Source code: http://sourceforge.net/projects/xml-print/
Installers for Windows, Mac and Linux:
http://sourceforge.net/projects/xml-print/files/

September 10, 2012

Mapping solution to heterogeneous data sources

Filed under: Bioinformatics,Biomedical,Genome,Heterogeneous Data,Mapping — Patrick Durusau @ 2:21 pm

dbSNO: a database of cysteine S-nitrosylation by Tzong-Yi Lee, Yi-Ju Chen, Cheng-Tsung Lu, Wei-Chieh Ching, Yu-Chuan Teng, Hsien-Da Huang and Yu-Ju Chen. (Bioinformatics (2012) 28 (17): 2293-2295. doi: 10.1093/bioinformatics/bts436)

OK, the title doesn’t jump out and say “mapping solution here!” 😉

Reading a bit further, you discover that text mining is used to locate sequences and that data is then mapped to “UniProtKB protein entries.”

The data set provides access to:

  • UniProt ID
  • Organism
  • Position
  • PubMed Id
  • Sequence

My concern is what happens when X is mapped to a UniProtKB protein entry to:

  • The prior identifier for X (in the article or source), and
  • The mapping from X to the UniProtKB protein entry?

If both of those are captured, then prior literature can be annotated upon rendering to point to later aggregation of information on a subject.

If the prior identifier, place of usage, the mapping, etc., are not captured, then prior literature, when we encounter it, remains frozen in time.

Mapping solutions work, but repay the effort several times over if the prior identifier and its mapping to the “new” identifier are captured as part of the process.

Abstract

Summary: S-nitrosylation (SNO), a selective and reversible protein post-translational modification that involves the covalent attachment of nitric oxide (NO) to the sulfur atom of cysteine, critically regulates protein activity, localization and stability. Due to its importance in regulating protein functions and cell signaling, a mass spectrometry-based proteomics method rapidly evolved to increase the dataset of experimentally determined SNO sites. However, there is currently no database dedicated to the integration of all experimentally verified S-nitrosylation sites with their structural or functional information. Thus, the dbSNO database is created to integrate all available datasets and to provide their structural analysis. Up to April 15, 2012, the dbSNO has manually accumulated >3000 experimentally verified S-nitrosylated peptides from 219 research articles using a text mining approach. To solve the heterogeneity among the data collected from different sources, the sequence identity of these reported S-nitrosylated peptides are mapped to the UniProtKB protein entries. To delineate the structural correlation and consensus motif of these SNO sites, the dbSNO database also provides structural and functional analyses, including the motifs of substrate sites, solvent accessibility, protein secondary and tertiary structures, protein domains and gene ontology.

Availability: The dbSNO is now freely accessible via http://dbSNO.mbc.nctu.edu.tw. The database content is regularly updated upon collecting new data obtained from continuously surveying research articles.

Contacts: francis@saturn.yu.edu.tw or yujuchen@gate.sinica.edu.tw.

September 8, 2012

10 Productivity Tips for Working with Large Mind Maps

Filed under: Mapping,Maps,Mind Maps,Visualization — Patrick Durusau @ 1:22 pm

10 Productivity Tips for Working with Large Mind Maps by Roger C. Parker.

From the post:

A while ago, I wrote a series of posts helping individuals get the most out of their mapping efforts. Today, I’d like share 10 productivity tips and best practices for working with large mind maps.

CMI-Image

As illustrated by the image above, mind maps can become substantially difficult to work with when the number of topics exceeds 60. At this size should you try and use MindManager’s Fit Map view, the type size decreases so much so that it becomes difficult to read. If you Zoom In to increase the type size, however, you lose context, or the “big picture” ability to view each topic in relation to all the other topics. So, what do you do?

A number of useful tips while constructing graphical views of topic maps. Or even for construction of topic maps per se.

Except for suggestion #7:

7. Search for duplicates before entering new topics

Inserting a duplicate topic is always a problem. Instead of manually searching through various topics looking for duplicates try using MindManager’s Search In All Open Maps command – it will certainly save you some time.

You should not need that one with good topic map software. 😉

August 30, 2012

Physics as a geographic map

Filed under: Mapping,Maps,Science — Patrick Durusau @ 3:04 pm

Physics as a geographic map

Nathan Yau of Flowing Data points to a rendering of the subject area physics as a geographic map.

Somewhat dated (1939) but shows a lot of creativity and not small amount of cartographic skill.

Rather than calling it a “fictional” map I would prefer to say it is an intellectual map of physics.

Like all maps, the objects appear in explicit relationships to each other and there are no doubt as many implicit relationships are there are viewers of the map.

What continuum or dimensions would you use to create a map of modern ontologies?

That could make a very interesting exercise for the topic maps class. To have students create maps and then attempt to draw out what unspoken dimensions were driving the layout between parts of the map.

Suggestions of mapping software anyone?

August 29, 2012

ACLU maps cost of marijuana enforcement [Comparison]

Filed under: Mapping,Maps,Mashups — Patrick Durusau @ 3:36 pm

ACLU maps cost of marijuana enforcement

From the article:

Washington spent more than $200 million on enforcing and prosecuting marijuana laws and incarcerating the folks that violated them, the American Civil Liberties Union of Washington estimates.

The organization released an interactive map today of what it estimates each county spent on marijuana law enforcement. Although not specifically tied to Initiative 502, which gives voters a chance to legalize marijuana use for adults under some circumstances, ACLU is a supporter of the ballot measure.

I have always wondered what motivation, other that fear of others having a good time, could drive something as inane as an anti-marijuana policy.

I think I may have a partial answer.

That old American standby – keeping down competition.

In describing the $425.7 million dollars taken in by the Washington State Liquor Control Board, a map was given to show where the money went:

In Fiscal Year 2011, $345 million was sent to the General Fund, $71 million to cities and counties, $8.2 million to education and prevention, and $1.5 million to research. To see how much revenue your city or county received from the WSLCB in Fiscal Year 2011, visit www.liq.wa.gov/about/where-your-liquor-dollars-go [All the “where-your-liquor-dollars-go” links appear to be broken. Point an an FAQ and not the documentation.].

Consider Pierce County: Spend on anti-marijuana – $21,138,797.

If you can guess the direct URL to the county by county liquor proceeds: http://liq.wa.gov/publications/releases/2011CountiesRevenue/fy2011-PIERCE.pdf (for Pierce county), you will find in 2011, the entire county got $7,489,073.

I’m just a standards editor and semantic integration enthusiast and by no means a captain of industry.

But, spending three times the revenue from competitors to marijuana on anti-marijuana activities makes no business sense.

If you can find the liquor revenue numbers for 2011, what other comparisons would you draw?

August 17, 2012

In Maps We Trust

Filed under: Mapping,Maps — Patrick Durusau @ 3:29 pm

In Maps We Trust by James Cheshire.

From the post:

Of all the different types of data visualisation, maps* seem to have the best reputation. I think people are much less likely to trust a pie chart, for example, than a map. In a sense, this is amazing given that all maps are abstractions from reality. They can never tell the whole truth and are nearly all based on data with some degree of uncertainty that will vary over large geographic areas. An extreme interpretation of this view is that all maps are wrong- in which case we shouldn’t bother making them. A more moderate view (and the one I take) is that maps are never perfect so we need to create and use them responsibly – not making them at all would make us worse off. This responsibility criterion is incredibly important because of the high levels of belief people have in maps. You have to ask: What are the consequences of the map you have made? Now that maps are easier than ever to produce, they risk losing their lofty status as some of the most trusted data visualisations if those making them stop asking themselves this tough question.
…
*here I mean maps that display non-navigational data.

I posted a response over at Jame’s blog:

How do you identify “non-navigational data” in a map?

Your comment made me think of convention and some unconventional maps.

Any data rendered in relationship to other data can be used for “navigation.” Whether I intend to “navigate” as “boots on the ground” or between ideas.

Or to put it another way, who is to say what is or is not “non-navigational data?” The map maker or the reader/user of the map? Or what use is “better” for a map?

Great post!

Patrick

Curious, would you ask: “What are the consequences of the map you have made?”

July 29, 2012

National Cooperative Geologic Mapping Program

Filed under: Geologic Maps,Mapping,Maps — Patrick Durusau @ 4:56 am

National Cooperative Geologic Mapping Program

From this week’s Scout Report:

The National Cooperative Geologic Mapping Program (NCGMP) is “the primary source of funds for the production of geologic maps in the United States.” The NCGMP was created by the National Geologic Mapping Act of 1992 and its work includes producing surficial and bedrock geologic map coverage for the entire country. The program has partnered with a range of educational institutions, and this site provides access to many of the fruits of this partnership, along with educational materials. The place to start here is the What’s a Geologic Map? area. Here visitors can read a helpful article on this subject, authored by David R. Soller of the U.S. Geological Survey. Moving on, visitors can click on the National Geologic Map Database link. The database contains over 88,000 maps, along with a lexicon of geologic names, and material on the NCGMP’s upcoming mapping initiatives. Those persons with an interest in the organization of the NCGMP should look at the Program Components area. Finally, the Products-Standards area contains basic information on the technical standards and expectations for the mapping work.

More grist for your topic map mill!

July 26, 2012

The Parsons Journal for Information Mapping (PJIM)

Filed under: Graphics,Mapping,Visualization — Patrick Durusau @ 12:40 pm

The Parsons Journal for Information Mapping (PJIM)

A publication of the Parsons Institute for Information Mapping (PIIM), which hosts this journal and other information mapping resources.

The journal has a rolling, open call for papers and projects, the closest one being the October 2012 issue:

Abstract due: August, 20, 2012

Final Submissions due: September 24, 2012

From the journal homepage:

The Parsons Journal for Information Mapping (PJIM) is an academic journal and online forum to promote research, writing, and digital execution of theories in the field of information mapping and its related disciplines. Our mission is to identify and disseminate knowledge about the fields of information mapping, information design, data visualization, information taxonomies/structures, data analytics, informatics, information systems, and user interface design.

PJIM focuses on both the theoretical and practical aspects of information visualization. With each issue, the Journal aims to present novel ideas and approaches that advance the field of Knowledge Visualization through visual, engineering, and cognitive methods.

We have an rolling, open-call for submissions for original essays, academic manuscripts, interactive and non-interactive projects, and project documentation that address representation, processing, and communication of information. We encourage interdisciplinary thinking and approaches and are open to submissions regarding, but not limited to, the following disciplines:

  • Visual analysis and interpretation
  • Social, political, or economic discourse surrounding information, distribution and use
  • Cognition, thinking, and learning
  • Visual and perceptual literacy
  • Historical uses of information in imagery
  • Semiotics

Links to research papers and other resources await you at the PIIM homepage.

July 21, 2012

Mapping Public Opinion: A Tutorial

Filed under: Mapping,Maps,R — Patrick Durusau @ 8:00 pm

Mapping Public Opinion: A Tutorial by David Sparks.

From the post:

At the upcoming 2012 summer meeting of the Society of Political Methodology, I will be presenting a poster on Isarithmic Maps of Public Opinion. Since last posting on the topic, I have made major improvements to the code and robustness of the modeling approach, and written a tutorial that illustrates the production of such maps.

This tutorial, in a very rough draft form, can be downloaded here [PDF]. I would welcome any and all comments on clarity, readability, and the method itself. Please feel free to use this code for your own projects, but I would be very interested in seeing any results, and hope you would be willing to share them.

An interesting mapping exercise, even though I find political opinion mapping just a tad tedious. Hasn’t changed significantly in years, which explains “safe” seats for both Republicans and Democrats in the United States.

Still, the techniques are valid and can be useful in other contexts.

July 18, 2012

Three.js: render real world terrain from heightmap using open data

Filed under: Mapping,Maps,Three.js,Visualization — Patrick Durusau @ 7:11 pm

Three.js: render real world terrain from heightmap using open data by Jos Dirksen.

From the post:

Three.js is a great library for creating 3D objects and animations. In a couple of previous articles I explored this library a bit and in one of those examples I showed you how you can take GIS information (in geoJSON) format and use D3.js and three.js to convert it to a 3D mesh you can render in the browser using javascript. This is great for infographic, but it doesn’t really show a real map, a real terrain. Three.js, luckily also has helper classes to render a terrain as you can see in this demo: http://mrdoob.github.com/three.js/examples/webgl_terrain_dynamic.html

This demo uses a noise generator to generate a random terrain, and adds a whole lot of extra functionality, but we can use this concept to also render maps of real terrain. In this article I’ll show you how you can use freely available open geo data containing elevation info to render a simple 3D terrain using three.js. In this example we’ll use elevation data that visualizes the data for the island of Corsica.

Rendering real world terrain, supplemented by a topic map for annotation, sounds quite interesting.

Assuming you could render any real world terrain, what would it be? For what purpose? What annotations would you supply?

July 17, 2012

Making maps, part 1: Less interactivity

Filed under: Mapping,Maps — Patrick Durusau @ 6:37 pm

Making maps, part 1: Less interactivity

A six part series on making maps from the Chicago Tribune that has this gem in the first post:

Back to the beer-fueled map talk… so, how can we do this better? The answer quickly became obvious: borrow from paper. What’s great about paper maps?

  • Paper maps are BIG
  • Paper maps are high resolution (measured by DPI *and* information-density)
  • Paper maps are general at a distance and specific up close

What if most things on your page design didn’t jump, spin or flop on mouse-over?

Could you still delivery your content effectively?

Or have you mistaken interactivity for being effective?

On the other hand, are paper maps non-interactive?

I ask because I saw a book this past weekend that had no moving parts, popups, etc., but reading it you would swear it was interactive.

More on that in a future post.

I first saw this at PeteSearch.

July 12, 2012

Real-time Twitter heat map with MongoDB

Filed under: Mapping,Maps,MongoDB,Tweets — Patrick Durusau @ 1:54 pm

Real-time Twitter heat map with MongoDB

From the post:

Over the last few weeks I got in touch with the fascinating field of data visualisation which offers great ways to play around with the perception of information.

In a more formal approach data visualisation denotes “The representation and presentation of data that exploits our visual perception abilities in order to amplify cognition“

Nowadays there is a huge flood of information that hit’s us everyday. Enormous amounts of data collected from various sources are freely available on the internet. One of these data gargoyles is Twitter producing around 400 million (400 000 000!) tweets per day!

Tweets basically offer two “layers” of information. The obvious direct information within the text of the Tweet itself and also a second layer that is not directly perceived which is the Tweets’ metadata. In this case Twitter offers a large number of additional information like user data, retweet count, hashtags, etc. This metadata can be leveraged to experience data from Twitter in a lot of exciting new ways!

So as a little weekend project I have decided to build a small piece of software that generates real-time heat maps of certain keywords from Twitter data.

Yes, “…in a lot of exciting new ways!” +1!

What about maintenance issues on such a heat map? The capture of terms to the map is fairly obvious, but a subsequent user may be left in the dark as to why this term and not some other term? Or some then current synonym for a term that is being captured?

Or imposing semantics on tweets or terms that are unexpected or non-obvious to a casual or not so casual observer.

You and I can agree red means go and green means stop in a tweet. That’s difficult to maintain as the number of participants and terms go up.

A great starting place to experiment with topic maps to address such issues.

I first saw this in the NoSQL Weekly Newsletter.

July 10, 2012

Visualization Tools for Understanding Big Data

Filed under: BigData,Mapping,Maps,Visualization — Patrick Durusau @ 10:01 am

Visualization Tools for Understanding Big Data by James Cheshire.

From the post:

I recently co-wrote an editorial (download the full version here) with Mike Batty (UCL CASA) in which we explored some of the current issues surrounding the visualisation of large urban datasets. We were inspired to write it following the CASA Smart Cities conference and we included a couple of visualisations I have blogged here. Much of the day was devoted to demonstrating the potential of data visualisation to help us better understand our cities. Such visualisations would not have been possible a few years ago using desktop computers their production has ballooned as a result of recent technological (and in the case of OpenData, political) advances.

In the editorial we argue that the many new visualisations, such as the map of London bus trips above, share much in common with the work of early geographers and explorers whose interests were in the description of often-unknown processes. In this context, the unknown has been the ability to produce a large-scale impression of the dynamics of London’s bus network. The pace of exploration is largely determined by technological advancement and handling big data is no different. However, unlike early geographic research, mere description is no longer a sufficient benchmark to constitute advanced scientific enquiry into the complexities of urban life. This point, perhaps, marks a distinguishing feature between the science of cities and the thousands of rapidly produced big data visualisations and infographics designed for online consumption. We are now in a position to deploy the analytical methods developed since geography’s quantitative revolution, which began half a century ago, to large datasets to garner insights into the process. Yet, many of these methods are yet to be harnessed for the latest datasets due to the rapidity and frequency of data releases and the technological limitations that remain in place (especially in the context of network visualisation). That said, the path from description to analysis is clearly marked and, within this framework, visualisation plays an important role in the conceptualisation of the system(s) of interest, thus offering a route into more sophisticated kinds of analysis.

Curious if you would say that topic maps as navigation artifacts are “descriptive” as opposed to “explorative?”

What would you suggest as a basis for “interactive” topic maps that present the opportunity for dynamic subject identification, associations and merging?

July 4, 2012

JQVMap

Filed under: JQuery,Mapping,Maps,SVG — Patrick Durusau @ 7:35 pm

JQVMap

From the post:

JQVMap is a jQuery plugin that renders Vector Maps. It uses resizable Scalable Vector Graphics (SVG) for modern browsers like Firefox, Safari, Chrome, Opera and Internet Explorer 9. Legacy support for older versions of Internet Explorer 6-8 is provided via VML.

I saw this at Pete Warden’s Five Links, along with the Plane Networks.

July 3, 2012

Mapping Research With WikiMaps

Filed under: Mapping,Maps,WikiMaps,Wikipedia — Patrick Durusau @ 5:12 am

Mapping Research With WikiMaps

From the post:

An international research team has developed a dynamic tool that allows you to see a map of what is “important” on Wikipedia and the connections between different entries. The tool, which is currently in the “alpha” phase of development, displays classic musicians, bands, people born in the 1980s, and selected celebrities, including Lady Gaga, Barack Obama, and Justin Bieber. A slider control, or play button, lets you move through time to see how a particular topic or group has evolved over the last 3 or 4 years. The desktop version allows you to select any article or topic.

Wikimaps builds on the fact that Wikipedia contains a vast amount of high-quality information, despite the very occasional spot of vandalism and the rare instances of deliberate disinformation or inadvertent misinformation. It also carries with each article meta data about the page’s authors and the detailed information about every single contribution, edit, update and change. This, Reto Kleeb, of the MIT Center for Collective Intelligence, and colleagues say, “…opens new opportunities to investigate the processes that lie behind the creation of the content as well as the relations between knowledge domains.” They suggest that because Wikipedia has such a great amount of underlying information in the metadata it is possible to create a dynamic picture of the evolution of a page, topic or collection of connections.

See the demo version: http://www.ickn.org/wikimaps/.

For some very cutting edge thinking, see: Intelligent Collaborative Knowledge Networks (MIT) which has a download link to “Condor,” a local version of the wikimaps software.

Wikimaps builds upon a premise similar to the original premise of the WWW. Links break, deal with it. Hypertext systems prior to the WWW had tremendous overhead to make sure links remained viable. So much overhead that none of them could scale. The WWW allowed links to break and to be easily created. That scales. (The failure of the Semantic Web can be traced to the requirement that links not fail. Just the opposite of what made the WWW workable.)

Wikimaps builds upon the premise that the “facts we have may be incomplete, incorrect, partial or even contradictory. All things that most semantic systems posit as verboten. An odd requirements since our information is always incomplete, incorrect (possibly), partial or even contradictory. We have set requirements for our information systems that we can’t meet working by hand. Not surprising that our systems fail and fail to scale.

How much information failure can you tolerate?

A question that should be asked of every information system at the design stage. If the answer is none, move onto a project with some chance of success.

I was surprised at the journal reference, not one I would usually scan. Recent origin, expensive, not in library collections I access.

Journal reference:

Reto Kleeb et al. Wikimaps: dynamic maps of knowledge. Int. J. Organisational Design and Engineering, 2012, 2, 204-224

Abstract:

We introduce Wikimaps, a tool to create a dynamic map of knowledge from Wikipedia contents. Wikimaps visualise the evolution of links over time between articles in different subject areas. This visualisation allows users to learn about the context a subject is embedded in, and offers them the opportunity to explore related topics that might not have been obvious. Watching a Wikimap movie permits users to observe the evolution of a topic over time. We also introduce two static variants of Wikimaps that focus on particular aspects of Wikipedia: latest news and people pages. ‘Who-works-with-whom-on-Wikipedia’ (W5) links between two articles are constructed if the same editor has worked on both articles. W5 links are an excellent way to create maps of the most recent news. PeopleMaps only include links between Wikipedia pages about ‘living people’. PeopleMaps in different-language Wikipedias illustrate the difference in emphasis on politics, entertainment, arts and sports in different cultures.

Just in case you are interested: International Journal of Organisational Design and Engineering, Editor in Chief: Prof. Rodrigo Magalhaes, ISSN online: 1758-9800, ISSN print: 1758-9797.

June 30, 2012

Station Maps: Browser-Based 3D Maps of the London Underground

Filed under: Mapping,Maps,Merging,Topic Maps — Patrick Durusau @ 6:47 pm

Station Maps: Browser-Based 3D Maps of the London Underground

From Information Asthetics:

Station Maps [aeracode.org] by programmer Andrew Godwin contains a large collection of browser-based (HTML5) 3D maps depicting different London Underground/DLR stations.

Most of the stations are modelled from memory in combination with a few diagrams found online. This means that the models are not totally accurate, but they should represent the right layout, shape and layering of the stations.

Every map has some underlying structure/ontology onto which other information is added.

Real time merging of train, security camera, security forces, event, etc., information onto such maps is one aspect of merging based on location/interest. Not all information is equally useful to all parties.

June 22, 2012

Hacking and Trailblazing

Filed under: Mapping,Maps,Security — Patrick Durusau @ 4:22 pm

Ajay Ohri has written two “introduction” posts on hacking:

How to learn to be a hacker easily

How to learn Hacking Part 2

I thought “hacker/hacking” would be popular search terms.

“Hot” search terms this week: “Lebron James” 500,000+ searches (US), “Kate Upton” 50,000+ searches (US). (Shows what I know about “hot” search terms.)

What Ajay has created, as we all have at one time or another, is a collection of resources on a particular subject.

If you think of the infoverse as being an navigable body of information, Ajay has blazed a trail to particular locations that have information on a specific subject. More importantly, we can all follow that trail, which saves us time and effort.

Like a research/survey article in a technical journal, Ajay’s trail blazing suffers from two critical and related shortcomings:

First, we as human readers are the only ones who can take advantage of the branches and pointers in his trail. For example, when Ajay says:

The website 4chan is considered a meeting place to meet other hackers. The site can be visually shocking http://boards.4chan.org/b/
 (http://www.decisionstats.com/how-to-learn-to-be-a-hacker-easily/)

Written as a prose narrative, it isn’t possible to discover 4chan and other hacker “meeting” sites. Not difficult for us, but then each one of us has to read the entire article for that pointer. I suppose this must be what Lars Marius means by “unstructured.” I stand corrected. (“visually shocking?” Only if you are really sensitive. Soft porn, profanity, juvenile humor.)

Second, where Ajay says:

Lena’s Reverse Engineering Tutorial-”Use Google.com for finding the Tutorial” (http://www.decisionstats.com/how-to-learn-hacking-part-2/)

I can’t add an extension, Reverse Engineering, a five-day course on reverse engineering.

Or, a warning that http://www.megaupload.com/?d=BDNJK4J8, displays:

seizure banner

Ajay’s trail stops where Ajay stopped.

I can write a separate document as a trail, but have no way to tie that trail to Ajay’s.

At least today, I would ask the design questions as:

  1. How do we blaze trails subject to machine-assisted navigation?
  2. How do we enable machine-assisted navigation across trails?

There are unspoken assumptions and questions in both of those formulations but it is the best I can do today.

Suggestions/comments?

PS: Someone may be watching the link that leads to the Megaupload warning. Just so you know.

PPS: Topic maps need a jingoistic logo for promotion.

Like a barracuda, wearing only a black beret, proxy drawing from the TMRM as a tatoo, a hint that its “target” is just in front of it.

Top: Topic Maps. Reading under the barracuda: “If you can map it, you can hit it….”

Research Data Australia down to Earth

Filed under: Geographic Data,Geographic Information Retrieval,Mapping,Maps — Patrick Durusau @ 2:47 pm

Research Data Australia down to Earth

From the post:

Context: free cloud servers, a workshop and an idea

In this post I look at some work we’ve been doing at the University of Western Sydney eResearch group on visualizing metadata about research data, in a geographical context. The goal is to build a data discovery service; one interface we’re exploring is the ability to ‘fly’ around Google Earth looking for data, from Research Data Australia (RDA). For example, a researcher could follow a major river and see what data collections there are along its course that might be of (re-)use. True, you can search the RDA site by dragging a marker on a map but this experiment is a more immersive approach to exploring the same data.

The post is a quick update on a work in progress, with some not very original reflections on the use of cloud servers. I am putting it here on my own blog first, will do a human-readable summary over at UWS soon, any suggestions or questions welcome.

You can try this out if you have Google Earth by downloading a KML file. This is a demo service only – let us know how you go.

This work was inspired by a workshop on cloud computing: this week Andrew (Alf) Leahy and I attended a NeCTAR and Australian National Data Service (ANDS) one day event, along with several UWS staff. The unstoppable David Flanders from ANDS asked us to run a ‘dojo’, giving technically proficient researchers and eResearch collaborators a hand-on experience with the NeCTAR research cloud, where all Australian University researchers with access to the Australian Access Federation login system are entitled to run free cloud-hosted virtual servers. Free servers! Not to mention post-workshop beer[i]. So senseis Alf and and PT worked with a small group of ‘black belts’ in a workshop loosely focused on geo-spatial data. Our idea was “Visualizing the distribution of data collections in Research Data Australia using Google Earth”[ii]. We’d been working on a demo of how this might be done for a few days, which we more-or less got running on the train from the Blue Mountains in to Sydney Uni in the morning.

When you read about “exploring” the data, bear in mind the question of how to record that “exploration?” Explorers used to keep journals, ships logs, etc. to record their explorations.

How do you record (if you do), your explorations of data? How do you share them if you do?

Given the ease of recording our explorations, no more long hand with a quill pen, is it odd that we don’t record our intellectual explorations?

Or do we want others to see a result that makes us look more clever than we are?

June 21, 2012

Mapping and Monitoring Cyber Threats

Filed under: Malware,Mapping,Security — Patrick Durusau @ 4:05 pm

Mapping and Monitoring Cyber Threats

From the post:

Threats to information security are part of everyday life for government agencies and companies both big and small. Monitoring network activity, setting up firewalls, and establishing various forms of authentication are irreplaceable components of IT security infrastructure, yet strategic defensive work increasingly requires the added context of real world events. The web and its multitude of channels covering emerging threat vectors and hacker news can help provide warning signs of potentially disruptive information security events.

However, the challenge that analysts typically face is an overwhelming volume of intelligence that requires brute force aggregation, organization, and assessment. What if significant portions of the first two tasks could be accomplished more efficiently allowing for greater resources allocated to the all important third step of analysis?

We’ll outline how Recorded Future can help security teams harness the open source intelligence available on various threat vectors and attacks, activity of known cyber organizations during particular periods of time, and explicit warnings as well as implicit risks for the future.

Interesting but I would add to the “threat” map known instances where recordable media can be used, email or web traffic traceable to hacker lists/websites, offices or departments with prior security issues and the like.

Security can become too narrowly focused on technological issues, ignoring that a large number of security breaches are the result of human lapses or social engineering. A bit broader mapping of security concerns can help keep the relative importance of threats in perspective.

June 12, 2012

Dreams of Universality, Reality of Interdisciplinarity [Indexing/Mapping Pidgin]

Filed under: Complexity,Indexing,Mapping — Patrick Durusau @ 12:55 pm

Complex Systems Science: Dreams of Universality, Reality of Interdisciplinarity by Sebastian Grauwin, Guillaume Beslon, Eric Fleury, Sara Franceschelli, Jean-Baptiste Rouquier, and Pablo Jensen.

Abstract:

Using a large database (~ 215 000 records) of relevant articles, we empirically study the “complex systems” field and its claims to find universal principles applying to systems in general. The study of references shared by the papers allows us to obtain a global point of view on the structure of this highly interdisciplinary field. We show that its overall coherence does not arise from a universal theory but instead from computational techniques and fruitful adaptations of the idea of self-organization to specific systems. We also find that communication between different disciplines goes through specific “trading zones”, ie sub-communities that create an interface around specific tools (a DNA microchip) or concepts (a network).

If disciplines don’t understand each other…:

Where do the links come from then? In an illuminating analogy, Peter Galison [32] compares the difficulty of connecting scientifi c disciplines to the difficulty of communicating between diff erent languages. History of language has shown that when two cultures are strongly motivated to communicate – generally for commercial reasons – they develop simpli ed languages that allow for simple forms of interaction. At first, a “foreigner talk” develops, which becomes a “pidgin” when social uses consolidate this language. In rare cases, the “trading zone” stabilizes and the expanded pidgin becomes a creole, initiating the development of an original, autonomous culture. Analogously, biologists may create a simpli ed and partial version of their discipline for interested physicists, which may develop to a full-blown new discipline such as biophysics. Specifi cally, Galison has studied [32] how Monte Carlo simulations developed in the postwar period as a trading language between theorists, experimentalists, instrument makers, chemists and mechanical engineers. Our interest in the concept of a trading zone is to allow us to explore the dynamics of the interdisciplinary interaction instead of ending analysis by reference to a “symbiosis” or “collaboration”.

My interest is in how to leverage “trading zones” for the purpose of indexing and mapping (as in topic maps).

Noting that “trading zones” are subject to emprical discovery and no doubt change over time.

Discovering and capitalizing on such “trading zones” will be a real value-add for users.

June 11, 2012

Flowchart: Connections in Stephen King novels

Filed under: Flowchart,Humor,Mapping — Patrick Durusau @ 4:24 pm

Flowchart: Connections in Stephen King novels by Nathan Yau.

For your modeling exercise and amusement, a flowchart of connections in Stephen King novels (excluding the Dark Tower series). I not sure what impact excluding the Dark Tower series has on the flowchart. If you discover it, please report back.

Topic map and other semantic modeling groups could use this flowchart as the answer to Google employment questions. 😉

Speaking of modeling, I wonder how many degrees of separation there are between characters in novels?

And how would they be connected? Family names, places of employment, physical locations, perhaps even fictional connections?

That could be an interesting mapping exercise.

May 31, 2012

Large Heterogeneous Data 2012

Filed under: Conferences,Heterogeneous Data,Mapping,Semantics — Patrick Durusau @ 12:56 pm

Workshop on Discovering Meaning On the Go in Large Heterogeneous Data 2012 (LHD-12)

Important Dates

  • Deadline for paper subsmission: July 31, 2012
  • Author notification: August 21, 2012
  • Deadline for camera-ready: September 10, 2012
  • Workshop date: November 11th or 12th, 2012

Take the time to read the workshop description.

A great summary of the need for semantic mappings, not more semantic fascism.

From the call for papers:

An interdisciplinary approach is necessary to discover and match meaning dynamically in a world of increasingly large data sources. This workshop aims to bring together practitioners from academia, industry and government for interaction and discussion. This will be a half-day workshop which primarily aims to initiate discussion and debate. It will involve

  • A panel discussion focussing on these issues from an industrial and governmental point of view. Membership to be confirmed, but we expect a representative from Scottish Government and from Google, as well as others.
  • Short presentations grouped into themed panels, to stimulate debate not just about individual contributions but also about the themes in general.

Workshop Description

The problem of semantic alignment – that of two systems failing to understand one another when their representations are not identical – occurs in a huge variety of areas: Linked Data, database integration, e-science, multi-agent systems, information retrieval over structured data; anywhere, in fact, where semantics or a shared structure are necessary but centralised control over the schema of the data sources is undesirable or impractical. Yet this is increasingly a critical problem in the world of large scale data, particularly as more and more of this kind of data is available over the Web.

In order to interact successfully in an open and heterogeneous environment, being able to dynamically and adaptively integrate large and heterogeneous data from the Web “on the go” is necessary. This may not be a precise process but a matter of finding a good enough integration to allow interaction to proceed successfully, even if a complete solution is impossible.

Considerable success has already been achieved in the field of ontology matching and merging, but the application of these techniques – often developed for static environments – to the dynamic integration of large-scale data has not been well studied.

Presenting the results of such dynamic integration to both end-users and database administrators – while providing quality assurance and provenance – is not yet a feature of many deployed systems. To make matters more difficult, on the Web there are massive amounts of information available online that could be integrated, but this information is often chaotically organised, stored in a wide variety of data-formats, and difficult to interpret.

This area has been of interest in academia for some time, and is becoming increasingly important in industry and – thanks to open data efforts and other initiatives – to government as well. The aim of this workshop is to bring together practitioners from academia, industry and government who are involved in all aspects of this field: from those developing, curating and using Linked Data, to those focusing on matching and merging techniques.

Topics of interest include, but are not limited to:

  • Integration of large and heterogeneous data
  • Machine-learning over structured data
  • Ontology evolution and dynamics
  • Ontology matching and alignment
  • Presentation of dynamically integrated data
  • Incentives and human computation over structured data and ontologies
  • Ranking and search over structured and semi-structured data
  • Quality assurance and data-cleansing
  • Vocabulary management in Linked Data
  • Schema and ontology versioning and provenance
  • Background knowledge in matching
  • Extensions to knowledge representation languages to better support change
  • Inconsistency and missing values in databases and ontologies
  • Dynamic knowledge construction and exploitation
  • Matching for dynamic applications (e.g., p2p, agents, streaming)
  • Case studies, software tools, use cases, applications
  • Open problems
  • Foundational issues

Applications and evaluations on data-sources that are from the Web and Linked Data are particularly encouraged.

Several years from now, how will you find this conference (and its proceedings)?

  • Large Heterogeneous Data 2012
  • Workshop on Discovering Meaning On the Go in Large Heterogeneous Data 2012
  • LHD-12

Just curious.

April 30, 2012

See California kills by Wildlife Services

Filed under: Mapping,Maps — Patrick Durusau @ 3:17 pm

See California kills by Wildlife Services

From the post:

Wildlife Services is a little-known federal agency of the Department of Agriculture charged with managing wildlife, particularly the intersection between humans — ranchers and farmers — and animals.

This map shows where Wildlife Services made the most kills of three commonly-killed animals — beavers, coyotes and bears. The charts below show the type of method used to kill those animals.

You can select beavers, coyotes, or bears, with other display options.

There appears to be no merging on other names for beavers, coyotes or bears, as well as the means of their, ah, control.

A good illustration that sometimes a minimal amount of merging is sufficient for the task at hand.

Mapping locations of control activities onto a map with changeable views is sufficient.

Readers aren’t expecting links into scientific/foreign literature where mapping of identifiers would be an issue.

Good illustrations, including maps, have a purpose.

So should your topic map and its merging.

April 26, 2012

DATA Act passes House

Filed under: DATA Act,Mapping,Topic Maps — Patrick Durusau @ 6:30 pm

DATA Act passes House

Alice Lipowicz writes:

Open government watchdog groups are applauding the House passage of the Digital Accountability and Transparency Act (DATA Act) on April 25 that would require federal agencies to consistently report spending information on a new, searchable Web platform.

The legislation passed by a voice vote and will now go before the Senate. If it becomes law, it will establish standards for identifying and publishing electronic information about federal spending.

The federal government would need to spend $575 million over five years to create new structures and systems under the DATA Act, according to a Congressional Budget Office report issued last year.

If I have ever heard of an opportunity for topic maps, this is one.

Not law, yet, but as soon as it is, there will be a variety of tooling up exercises that will set the parameters for later development.

The Digital Accountability & Transparency Act (DATA), H.R. 2146 (as of this data)

BTW, they mention ISO:

Common data elements developed and maintained by an international voluntary consensus standards body, as defined by the Office of Management and Budget, such as the International Organization for Standardization. [Sec. 3611(a)(3)(A)]

Two thoughts:

First, the need of agencies for mapping solutions to report their current systems in the new target form.

Second, the creation of “common data elements” that have pre-defined hooks for mapping, using topic maps.

April 25, 2012

NYC BigApps

Filed under: Contest,Mapping,Marketing — Patrick Durusau @ 6:25 pm

NYC BigApps

From the webpage:

New York City is challenging software developers to create apps that use city data to make NYC better.

There are three completed contests (one just ended) that resulted in very useful applications.

NYC BigApps 3.0 resulted in:

NYC Facets: Best Overall Application – Grand Prize – Explores and visualizes more than 1 million facts about New York City.

Work+: Best Overall Application – Second – Prices – Working from home not working for you? Discover new places to get things done.

Funday Genie: Investor’s Choice Application – The Funday Genie is an application for planning a free day. Our unique scheduling and best route algorithm creates a smart personalized day-itinerary of things to do, including events, attractions, restaurants, shopping, and more, based on the user’s preferences. Everyday can be a Funday.

among others.

Quick question: How would you interchange information between any two of these apps? Or if you like, any other two apps in this or prior contests?

Second question: How would you integrate additional information into any of these apps, prepared for use by another application?

Topic maps can:

  • collate information for display.
  • power re-usable and extensible mappings of data into other formats.
  • augment data for applications that lack merging semantics.

Where is your data today and where would you like for it to be tomorrow?

April 17, 2012

How can we get our map colours right?

Filed under: Graphics,Mapping,Maps,Visualization — Patrick Durusau @ 7:11 pm

How can we get our map colours right? How open journalism helped us get better

Watch the debate as it unfolds over Twitter with argument for and against color schemes, plus examples!

Did the map get better, worse, about the same?

The Guardian writes:

How can you get the colour scales right on maps? It’s something we spend a lot of time thinking about here on the Datablog – and you may notice a huge variety of ones we try out.

This isn’t just design semantics – using the wrong colours can mean your maps are completely inaccessible to people with colour blindness, for instance and actually obscure what you’re trying to do.

It’s distinct to problems expertly faced by the Guardian graphics team – who have a lot of experience of making maps just right.

But on the blog, making a Google Fusion map in a hurry, do we get it right?

What avenues for public contribution do you allow for your topic maps?

April 11, 2012

Timeline Maps

Filed under: Mapping,Maps,Time,Timelines — Patrick Durusau @ 6:17 pm

Timeline Maps

From the post:

Mapping time has long been an interest of cartographers. Visualizing historical events in a timeline or chart or diagram is an effective way to show the rise and fall of empires and states, religious history, and important human and natural occurrences. We have over 100 examples in the Rumsey Map Collection, ranging in date from 1770 to 1967. We highlight a few below.

Sebastian Adams’ 1881 Synchronological Chart of Universal History is 23 feet long and shows 5,885 years of history, from 4004 B.C. to 1881 A.D. It is the longest timeline we have seen. The recently published Cartographies of Time calls it “nineteenth-century America’s surpassing achievement in complexity and synthetic power.” In the key to the map, Adams states that timeline maps enable learning and comprehension “through the eye to the mind.”

Below is a close up detail of a very small part of the chart: (click on the title or the image to open up the full chart)

Stunning visuals.

Our present day narratives aren’t any less arrogant than those of the 19th century but the distance is great enough for us to laugh at their presumption. Which unlike our own, isn’t “true.” 😉

Worth all the time you can spend with the maps. Likely to provoke insights into how you have viewed “history” as well as how you view current “events.”

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