1. Copernicum, 112th element on the periodic table

    Discovered 13 years ago, and officially added to the periodic table just weeks ago, element 112 finally has a name.
    It will be called “copernicium”, with the symbol Cp, in honour of the astronomer Nicolaus Copernicus.

    Read more: http://news.bbc.co.uk/1/hi/sci/tech/8153596.stm



  2. Heart Monitors and the Limit of Self-Knowledge

    Heart Monitors and the Limit of Self-Knowledge


    The heart rate is among the earliest biometrics used by humans to take stock of themselves. Before mechanical clocks were invented, this was hard. The first doctor credited with making objective measurements of the pulse was an Alexandrian physician named Herophilos, from the 3rd century, B.C., who used a water clock as his chronometer. Using a specified outflow of water to set the time interval, he counted the heart beats of four healthy individuals of different ages, which gave him a base rate against which to compare the pulse of his patients. Genius!

    It’s easier to find our heart rate now. In fact, it’s so easy it’s become complicated again. What you used to be able to do with two fingers and a second hand now requires a cardiac monitor, sometimes with a chest strap and a wireless connection to the wearable computer on your wrist. These complications are associated with bigger benefits; we can correlate our heart rate with our exercise regime, for instance. There are more than 700 heart rate monitors listed on Amazon. Many of the best monitors require a chest strap. Why not just put this in our clothing? The one pictured below is from Numetrex. full-cardioshirt.jpg

    Pacing exercise is just one of the things we might want to do with data about the rhythm of our heart. The pattern of the heart beat is a clue to health, and, ideally, it would be tracked all the time. For monitoring serious conditions, how about if we move the monitor from our wrist or our clothing, and put it inside our body? The image below is of a tiny cardiac monitor the size of a small memory stick. It is implanted in a patient’s chest, and recorded measurements can be picked up from the outside.

    RevealDX.jpgAs we generate more data, the patterns become too complex for our brains to recognize. ECG measurements have to be read by trained physicians. Or by artificial intelligences. While reporting an upcoming story in Wired about the great inventor Ray Kurzweil, who is best known for his reading machine and his theory of the singularity, I found how that his company has also been involved in researching the use of artificial intelligence for the interpretation of ECG. His friend Martine Rothblatt, the founder of United Therapeutics hired Kurzweil’s company to contribute some improvements to the algorithm underlying CardioPal, a 24/7 cardiac monitoring system designed to provide early warning of arrhythmias. CardioPal is produced by Medicomp, a United Therapeutics subsidiary. The underlying algorithm is named Diogenes.

    Diogenes.pngThere is a lot of interesting science behind the interpretation of ECG, and it is easy to imagine a not-too-distant era when internal cardiac monitors are a normal health maintenance device, automatically warning of impending problems. The curious thing about this vision of a totally monitored future is that the algorithms that interpret data from these monitors inevitably becomes more and more complex, easily outstripping our capacity for unaided interpretation. We will get a warning of impending doom, but not fully understand why this warning is issued. We will gain more power over ourselves, but not more self-understanding. Maybe we have to adjust our idea of who we are. The artificial intelligence upon which we rely – can this be understood as part of our self?

    (via Quantified Self.)

  3. Visualizing Science & Tech Activity in Wikipedia

    Visualizing Science & Tech Activity in Wikipedia


    If you didn’t see our original Wikipedia Activity Visualization, check it out here (there’s a detailed explanation, as well).  Also, there is a Google maps style zoomable version here.

    This new version uses the same layout and images (well, slightly improved) as the original, but this time we tried to highlight activity in regions of Wikipedia that are predominately math or science or technology. 

    So we developed a program to classify Wikipedia articles as being one of these three categories (or none), based on the categories the article was assigned to and their positions in the Wikipedia category link network. 

    We were not surprised to see a tight cluster of math pages, in a region, I would add, which has little ‘hot’ activity.  In fact, the only article in that region with lots of activity is the article “Earth”.  It was also not surprising that technology articles are fairly spread out among the topics.

    What’s striking is the science-related band (green-blue) that runs diagonal through the middle of the topic map.  I won’t share my interpretation, but rather let those interested come up with there own.  Hope you enjoy, please leave comments!



    Above: The most actively edited science-related articles.

    Left: Not much science here…a good indication the algorithms are working pretty well!

    (Via A Beautiful WWW.)

  4. Components of Data Collection Matrix

    Components of Data Collection Matrix

    Extracted from “Designing and Conducting Ethnographic Research (Ethnographer’s Toolkit , Vol 1)” (LeCompte Margaret Diane):

    Components of Data Collection Matrix
    1. Which research question are to be asked
    2. Which data will answer those questions
    3. Where, and from whom, those data can be obtained
    4. In what form the data will be collected
    5. Who will be responsible for collecting, analyzing, and writing up the data
    6. When each stage of data collection, analysis and report writing will begin and end
    7. How, by whom, and to whom results will be disseminated

    The authors recommend to go through these questions and then work out 2 tables:
    1) table 1: What do I need to know? Why do I need to know this? What kind of data will answer the question? Where can I find the data? Whom do I contact for access? Timelines for acquisition
    2) Table 2: Research Questions / Process Data and Outcome Measures / Sources of Data

    Why do I blog this? being in the midst of starting new projects… it’s always good to get back to basic references about where to start when you have pending research questions.

    [tags]research, data, datamining, knowledge[/tags]

    (Via pasta and vinegar.)

  5. Random Generation

    Random Generation: “

    lust1.jpgIn The Hague, Dutch graphic designers LUST are celebrating their 10th anniversary with an exhibition at contemporary art platform <>TAG. They present their decade of work in an ‘an interactive visual catalogue that explores new ways of archiving. The exhibition is not primarily aimed at summing up, it strives to highlight the actual process of design in which failure and success exist side by side. It addresses the issue of data storage, access, exchange and modification that has become increasingly relevant in the digital age’.

    The visual catalogue actually consists of a 2m by 1m touchscreen and an archive of boxes with RFID-tags attached to them. When you place a box on the screen the related items within the box will be shown on the screen. When you place another box on top of the first one the info combines and so on. With this experiment in archiving, LUST also want to give a nod to Paul Otlet, lust2.jpgthe great pioneer of data accessibility who in 1910 founded the Mundaneum in Brussels, as an archive of humanity’s collective intellectual capital, made accessible by a system allowing users to find data to the most specific level.

    Today and tomorrow there’s also a workshop by David Reinfurt and on Saturday the 24th, LUST and Luna Maurer will take participants on a ‘rhizomatic city tour’ in The Hague. Get in touch with <>TAG for both events.

    Exhibition through March 31st.

    [tags]knowledge, archive, mind, intelligence, classification, system, ontology, mundaneum[/tags]

    (Via we make money not art.)

  6. Geo: All geo coordinates from Wikipedia

    Geo: All geo coordinates from Wikipedia

    Stefan Kühn, a cartographer at the University Trier, Germany, has extracted all the geo coordinates embedded in articles on [Wikipedia->http://www.wikipedia.com/]. The [WikiProject Geographical coordinates->http://en.wikipedia.org/wiki/Wikipedia:WikiProject_Geographical_coordinates] is a Wikipedia project for ensuring standardized geocoding of locations in its articles.

    Google Earth fans bent on instant gratification can simply download a KMZ file and start surfing. But more importantly, coders and infoviz geeks can get a comma-separated text file (CSV) with coordinates, titles and Wikipedia categories for all points.

    Link: [Geocoordinates from Wikipedia for Google Earth->http://www.webkuehn.de/hobbys/wikipedia/geokoordinaten/index_en.htm]

    (via Code & form.)

    [tags]data, database, geo, coordinates, geolocation, knowledge, mapping, map, gps, wikipedia[/tags]

  7. Science & Technology at Scientific American.com: The Semantic Web — A new form of Web content that is meaningful to computers will unleash a revolution of new possibilities

    Science & Technology at Scientific American.com: The Semantic Web — A new form of Web content that is meaningful to computers will unleash a revolution of new possibilities

    The entertainment system was belting out the Beatles’ “We Can Work It Out” when the phone rang. When Pete answered, his phone turned the sound down by sending a message to all the other local devices that had a volume control. His sister, Lucy, was on the line from the doctor’s office: “Mom needs to see a specialist and then has to have a series of physical therapy sessions. Biweekly or something. I’m going to have my agent set up the appointments.” Pete immediately agreed to share the chauffeuring.

    [tags]semantic, web, online, software, theory, process, knowledge[/tags]

  8. Wikipedia for Google Earth and WikiSearch Tool

    Wikipedia for Google Earth and WikiSearch Tool

    The Wikipedia is a wonderful source of information which is frequently referenced in stories here. And, there are tools for tying Google Earth to Wikipedia like Placeopedia (which allows people to placemark good Wikipedia articles). Recently, a Google Earth Community member called KASSPER, posted a very interesting Google Earth network link which allows you to see the “best described” 80 wikipedia stories in your current view. Apparently someone named Stefan Kuhn processed a database with about 34,000 wikipedia story locations and ranked them according to description file size. KASSPER then created a network link allowing you to view the locations as placemarks in Google Earth. There are more details about the process and how to participate in the project to georeference Wikipedia stories in his post.

    In the same GEC thread, KASSPER also posted a nifty web page tool for searching the Wikipedia database for locations. It dynamically generates place results based on what you type in the search window. This highlights the need for better search in Google Earth. GE’s current search is pretty weak. Kind of weird when you consider it’s from Google. For example, a search for “Richmond” produces one result in GE, but 20 results in the Wikipedia search above.

    (Via Google Earth Blog.)

    [tags]maps, mapping, database, interface, knowledge[/tags]