Each of these arrows can be like the telephone game, something important and subtle lost. Which of these is a better model
The greatest thing about relational databases is they store everything loose in some kind of homogeneous level playing field. It is only be establishing relationships between data that anyone is able to see anything in context. Without context, they are just data. In context they are messages, thoughts, ideas, studies, results, and work products.
If an idea is very complex sometimes it helps to break it down into component parts. Systematically taking it apart to understand what makes this idea tick.
Taking an idea apart can be very informative. Especially when various parts need to be updated and optimized, continually changing like software releases. If the watch above was wordpress, the Swift theme, and the internet each gear changes sooner or later but the whole watch still needs to work together if it is to continue functioning. Putting things back together offers it’s own set of challenges. There is an opportunity to purge elements that are no longer useful during this process. Like a hoarder moving everything out of their house onto the curb then back into the house, maybe some of those items are not worth saving after all. Or fixing a car engine, or someones medical condition, when it is unclear exactly what the problem is but simply by taking it apart and putting it back together, whatever was not working gets repaired.
Instructions are needed, parts need to be labeled. A sequence of reassembly is needed to ensure the reassembled whole still is the same. It can be difficult to see how the parts fit together when viewed too close.
Because everyone’s perception and experience is different, the exact same elements, in almost exactly the same combination may be understood a different way from different points of view. The receiving end may be “reading something into” what the sender intended. It may not be possible for two different people to consistently see the same things the same ways.
However, this is not true for machines like computers or networks like the internet because machines have no prejudices, emotions, or previous experiences. They simply process the information, break up whole ideas into packets, send them somewhere, another machine puts them back together. For this to be reliable everything on both ends needs to be a repeatable process. It would be so helpful to have a mold with the end result packed in with every packet to ensure consistency. MIT has just started a project to map controversies that may be useful to understand multiple interpretations of the same information.
This project is important today because we are surrounded by so many controversies, and so much data, it’s difficult to sort out which parts are actually valid, worth processing, keeping in the information houses where we store things. For example the Washington Post had an article today about the disconnect between science and the general public entitled “Not Blinded by Science, but Ideology” where global warming is a perfect example.
To avoid using information the wrong way, or putting together messages, thoughts, and ideas that may be different than original authors intended, especially while processing the data in emotionless machines – repeatable processes are needed.
Today the primary representation of how pieces of information are to be put back together need to work with SQL. Looking at the relationships is usually just miles and miles of code. However, there is a company at http://mkweb.bcgsc.ca who makes Schemaball, a Schema Viewer for SQL Databases where the relationships themselves can be put under a microscope and examined across the whole database in one glance.
It’s curious why geometry proper is not used more often to direct the arc, layouts and relationships. Something like a mold could be useful to ensure the reassembly is 100 percent correct on the receiving end, to match exactly, what the sender intended.
But how would you store and encode that geometry?
When organizing large quantities of resources and information in the digital world… putting things into groups, determining what goes where and assigning boundaries, it can be helpful to look at the real world for lessons learned. Imposing boundaries in unnatural locations is bound to fail sooner or later, the results can be disastrous taking generations to overcome.
Take for example Southern Africa. Oceans, mountains, deserts, vegetation and other natural features determined where people lived and worked.
Over time, people settled in various areas surrounded by their culture. Learning the best ways to be productive based on the conditions in their area – whether it was a jungle with vast resources or a desert with very few.
From Africa Expat
Ancient people such as the Shona in modern day Zimbabwe congregated and stuck together in different areas. Many of these languages and traditions continue today. But these curving, natural, and emergent boundaries don’t match boundaries imposed from outside cultures.
From Wikimedia Commons
Occasionally, an imposed boundary may coincide with a natural boundary such as a river. More often though, imposed boundaries are designed to work within larger more global schemes, without paying enough attention to the local impact.
From Wikimedia Commons
Anyone can see where arbitrarily drawing lines has gotten us today. What can be learned from history to avoid similar situations in the fresh, clean, brand new digital world where ideas and information are still patterning out and have no where in particular to belong except where they are emerging as “next to something else” or arranged for convenient, all encompassing, upper level views
Linked Open Data, Colored, as of March 2009
What about situations where digital terrain and intellectual data boundaries are being purposefully laid out. For example Master Web of Science, mapofscience.com and Places & Spaces where navigating the data is like exploring uncharted territory, and Katy Borner and collaborators seek to enable the discovery of new worlds while also marking territories inhabited by unknown monsters.
The difference in the semantic world versus the physical world should be that the digital world has no constraints like rivers or mountains. Eventually all of the layout can be determined. Attention does need to be paid to where cultures are emerging, and how this can benefit everyone both globally and locally.
Not only watch how the semantic web is emerging, but to direct it’s flow in productive ways, geared for people in different areas that may vary widely in their density and resources, rather than as one empire. Because that only causes trouble in the long run.
Random Layout Algorithm at Cell System Markup Language (CSML) an XML format for modeling, visualizing and simulating biopathways.
The advantage of paying attention to this is, reaching an appropriate balance between random emergence and directed flow will ultimately serve end users and programmers better than any other option, and the solutions will last for a long time.
On 10 July 2009 Steve Kehlet said: “For a while I’ve been reading I Love Typography, which describes itself as a means of bringing the subject of Typography to the masses. I am definitely part of the masses, I know I don’t have the critical eye and patience needed for good page design, as made evident by my site with its uninspired look, horrible colors, blocky layout, and general failure to render properly in any browser but Safari. But as I Love Typography says, it is truly inspiring at times to see these beautiful fonts and what people have done with them. Each article showcases numerous typefaces and sometimes works of art created with them. It’s a fascinating read on a beautiful topic I now realize I know so little about.” So he starts to look at it:
See the sticker on the tire. It is a discrete rectangle. A fixed piece of information, it is not continuous.
However, once the wheel goes in motion, the sticker can no longer be seen – the discrete shape appears to be a continuous blur.
Therefore, discrete elements put into dynamic motion only appear to be continuous. How can this be useful to take discrete instances of knowledge and make them continuous?
Continuity, even if only simulated, can benefit the digital age in many ways. For example, look at all the discrete papers published every day. Each one is a set of information like the sticker but what would happen if groups of paper were set in motion, to force continuity between them? What shape would serve this purpose best? A circle like the tire? Some shared, continuous knowledge would require far more complex geometry.
Please refer to this video Blaise Aguera y Arcas: Photosynth Demo wherein Flickr images are assembled to construct the Notre Dame Cathedral. The only way to do this is to know the geometry of the cathedral.
What is the geometry of knowledge? How can continuity be implied using shared geometry and many points of view more productively?
There is no way to address the topic without also thinking about slightly different versions of the same thing. Examples using music are below. The same notes and words are used but the songs and performances, even the performance requirements, are different. Each piece of music is discrete, the continuity is the fact they are the same song by different artists ~ in different times and places.
I Will Survive by Gloria Gaynor and Cake
Krzysztof Penderecki communicates flow in his musical compositions through his own annotation system. Eventually his drawings are translated into traditional notes and lines so performers can play the work. But for his own purposes, and maybe to explain the details and overall patterns to performers and patrons – Penderecki’s own system captures his ideas best.
The scores above are from wood s lot, Sinepost, and the gallery of music at WFMU.
A set of images from Mattmo‘s Inspiration Set on Flickr are presented in contrast below. They also capture flow. At one point maybe only to the artist or mathematicians but at some point later, perhaps to others interpreting or performing the work…..maybe even machines performing work that has a flow.
Saul Steinberg Untitled 1980 above, 1983 middle, 1964 below.
Red and Blue America by Sara Fabrikant
From Science News
HEADLINE NEWS. The geographical distribution of news stories isn’t uniform, Newman and Gastner show. Even allowing for population, a few cities?New York and Washington, in particular?get a surprisingly large fraction of the attention. The researchers extracted the dateline from about 72,000 wire-service news stories from 1994 to 1998 and changed a standard map (top) into a cartogram (bottom) in which the sizes of states are proportional to the frequency of their appearance in datelines. SOURCE: Newman and Gastner/PNAS
To Figure: To form or shape, to trace, to reckon or calculate, to represent in a diagram or picture, to ornament or adorn with a design or pattern.
The Institute for Figuring does not yet have a physical space. Their location in the conceptual landscape is permanently located on the edge of this iconic fractal.
Institute for Figuring (IFF) Mandelbrot set location: (-0.7473198, i0.1084649) with detail (color inset.)
Crochet model of hyperbolic plane by Daina Taimina
In 1997 Cornell University mathematician Daina Taimina finally worked out how to make a physical model of hyperbolic space that allows us to feel, and to tactilely explore, the properties of this unique geometry. The method she used was crochet. See  Hyperbolic Space Crochet Models for more information.
 It is one thing to know that something is possible, it is quite another to understand what it is. Like the blind man and the elephant, hyperbolic space appears in different guises depending on how we approach it. One way of visualizing this enigmatic space was discovered by the great French mathematician Henri Poincar?. In the Poincar? disc model the entire hyperbolic space is depicted inside a circle.
Poincare Disc Model of Hyperbolic Space
Image and text above from the website of the Institute For Figuring (www.theiff.org)
Brings to mind topological knots. Images below by Sofia Lambropoulou.
Mongolian knots on stamps
This is an image from the Standard Upper Ontology Working Group (SUO WG) Also shown as Fig. 3 in Accuracy&Aesthetic director Kenneth Field‘s upcoming publication “Ontologies, Categories, Folksonomies: An Organised Language of Sound” to be published in the fall and copyrighted by Organised Sound, an International Journal of Music and Technology, Cambridge Journals.
Ken is interested in aesthetic outcomes of the structures and coined the new term “Ontoform” while stating “I’m after living/conscious ‘ontoforms’ that float invisibly in our environment until you put on your x-ray specs.”
Debbie is beginning to collect images like the ones above simply to examine standard upper ontologies as forms, functions, and overall designs. The purpose is to devise a method of making ontoforms, designs, and functions more beautiful and locally driven by treating them like building designs communicated through drawings, measurements, models, and special means of specifying.
Emerging Complexity and Cellular Automata, Wolfram Science
From Simon’s Computing Stuff: The Dripping Rail rule is a 1D CA rule which is simply an averaging over neighbours and an increment. This module shows the time progression of the CA.
Dripping Springs by Kevin Caron