format-number(number(.), '00000').
Here is an example of the input and output:
Input | Output |
---|---|
1 | 00001 |
12 | 00012 |
123 | 00123 |
1234 | 01234 |
12345 | 12345 |
Ruminations on NoSQL, XRX, XQuery, Semantics, STEM, Arduino, Internet-of-Things (IoT) and empowering the non-programmer.
Input | Output |
---|---|
1 | 00001 |
12 | 00012 |
123 | 00123 |
1234 | 01234 |
12345 | 12345 |
I had several good comments about my posting about the increasing role of semantics in the "Era of Tera". I did not mention some of the key concepts that the Intel paper discussed and the impact these concepts will have on IT strategy. Here is an excerpt:
The problem is ordinary computers don't model things. Aside from supercomputers, today's computers aren't capable of developing mathematical models of complex objects, systems or processes. Nor are they powerful or fast enough to perform such tasks at speeds people demand. We can't plug in a statistical model for a rare malignant tumor or the behavioral pattern of a shoplifting employee and search for similar instances of the model in a data set. To benefit from the wealth of data building up in the world, we need to be able to communicate with computers in more abstract terms (high-level concepts or semantics). We need to speak in terms of models.
I believe that the core problem is that there will be a HUGE demand for highly-skilled data-modelers/ontologists in five years. But there will not be a large supply since this skill is not something that can be learned from a single class in college. Rather it is more of a tacit skill that is not easily codifiable.
That being said, there are many best practices that ARE codifiable. You can already purchase books on OWL/RDF and metadata registries, although most of them are mired in relational database models or written by academics with little real-world experience. You can read the Wikipedia articles on “Data Stewardship”. What is still needed is a single set of best practices and tools for creating families of machine-readable data models that can be use as a basis for creating exchange models. And we need to do this without having to learn how to represent all 12 types of UML diagrams in XMI and transform them. The NIEM subset generator is a good example of the solid XML-Schema-driven front-end of this process of selecting elements from a metadata registry and putting them in your shopping cart.
The bottom line is that this is really about empowerment. And unless organizations introduce semantic web technologies into their organizations at a grass-root level and support them at the CEO level, many organizations will be left behind in the Era of the Tera.
I read in the New York Times yesterday that Intel has produced a chip with 80 core processors giving it a total computing power of 1.3 teraflops. So the natural question is what could you use 80 CPUs for? The article referred to a 2005 Intel Paper titled Recognition, Mining and Synthesis Moves Computers to the Era of Tera by Pradeep Dubey. This article opened with the following quote: “The great strength of computers is that they can reliably manipulate vast amounts of data very quickly. Their great weakness is that they don’t have a clue as to what any of that data actually means.” Stephen Cass, “A Fountain of Knowledge,” IEEE Spectrum, January 2004. When I saw this quote, I realized even the hardware engineers agree semantics is now the critical factor limiting our ability to effectively use computers I realized that we must continue our mission to promote semantic mapping concepts. So let me summarize my feelings after reading this article:
If want to be able to leverage the power coming in the Era of the Tera, you must start with semantics – recoding the meaning of your data.
And if you don’t yet have a metadata registry…get one!
Right next to the CEO, CIO, and CFO in the board room should be your CDO (Chief Data Officer).