Commercial Implementation of XML

Commercial Implementation of XML

A multitude of industries utilize XML in one form or another, and often for different reasons:

• Some industries use XML because of its standardization of information transferal. In other words, information sent between different people, computers, or companies can be easily understood by all parties. They all use XML, and perhaps some type of specialized XML vocabulary to interpret data.

• The other obvious reason is the natural object and hierarchical structural aspects of XML documents. Object methodologies lend themselves to management of complex information much better than do relational database modeling techniques. Why is this the case? The answer is simple. The more an object data model is divided into its smallest divisible parts, the simpler and more manageable it becomes. When dividing a relational database model into its simplest and most detailed parts , the relational model can begin to fail. This failure is often seen only in commercial environments. Commercial environments usually have massively uncontrollable quantities of data. The more a relational database is divided into self-contained elements, the larger and more complex the queries against that data can become. The result is nearly always abominable performance. Poor performance is unacceptable in industry because companies must turn a profit in order to remain viable concerns.

The result is that, commercially, XML is more likely to be used in order to simplify data transfer operations. There are many commercial environments that do utilize XML to handle complex data issues. However, they tend to be either bleeding edge technology, such as bioinformatics and genetic engineering, or perhaps smaller parts of larger database implementations . For example, some military applications include native XML database installations for a specific function on a naval vessel, for instance as opposed to running the entire ship . In other words, XML is used specifically where it can provide the best benefit.

Common industrial and commercial uses of XML and XML databases are as follows :

• Data Transfer and B2B (Business to Business):  Information portals or data transfer mechanisms in the corporate world.

• Catalog and document management:  Catalogs of data such as storage of scientific textual documents and research papers, requiring extensive searching facilities both as document titles and within those documents.

• Manufacturing:  Manufacturing has always been a complex issue for relational databases and any application development. A high degree of complexity is one of the primary motivating factors for use of XML. The mind boggles at the complexity of all the parts that go into manufacturing a commercial aircraft. This could include manufacturer suppliers, even their suppliers, pricing, where parts are located, how and where parts fit, and measurements. A list like this can go on and on. Even manufacturing something as simple as bricks will likely involve raw materials, where they come from, oven temperatures , a multitude of types of bricks. Again, the list can go on and on.

• Medicine:  Medical information often includes diagnoses with specialized multimedia data, such as imaging, and even imaging annotations. Again, complexity is the issue for use of XML.

• Personalization:  Whenever you go to a website, such as Amazon or eBay, you might get a personalized web page if not now then in the future. XML can handle this personalization by providing a generic framework for interpreting what is specific to yourself. When you surf to that web page you will get something that says Hi specifically to you, and the site might try to market at you based on what you have purchased in the past (even from other vendors ). This type of web page could probably be more irritating than anything else a little like junk email. It might be more useful than you think, working on a subliminal level.

• Web services and feeds:  Any kind of Web Service providing real-time data can utilize XML to standardize both transfer and display (see Chapter 7). News feeds, stock market feeds, flight information and booking systems are some more common examples of many other varying applications.

• Bioinformatics and genetics :  This type of data is particular complex and highly volatile. Volatility implies that these fields of research are still very much research, and they can change dramatically, and repeatedly. The flexibility and complexity-handling capabilities of XML can benefit these fields immensely.

• Incomplete and inconsistent data:  Any information, including data such as customer profiling and entertainment data can often be incomplete, and is potentially inconclusive. XML is flexible enough to allow you to leave stuff out and mix different things together. For example, entertainment could include data about restaurants , night clubs, hotels, or even the crumbly candy bars you purchase in a movie house. In other words, describing the flavor and ingredients of goodies purchased in a movie house is very different from the swimming pool and restaurant facilities of a swanky downtown hotel. XML allows for this type of flexibility because both its data and metadata structure are both flexible and directly available. In other words, data and metadata are both in the same place (in the same XML document).

• Geographical, geospatial, and geological data:  Geographical data is locational data such as countries , cities, population, and demographics (used in this book) data. Quite often, this information involves one thing inside another, within a multiple-layered hierarchy. Generally, one does not necessarily need to access this type of data, unless one is looking through the parent information. This is not always the case. Geospatial data applies to locations in three-dimensional space, such as both above and below the earths surface. For example, known oil and natural gas deposits are below the earths surface. Climatological data is above the surface of the earth. Geological data might be about mapping prospective resources based on satellite data (visible and otherwise ) even ground-based data, such as geophysical research. A large part of geophysical data is putting sticks of dynamite into holes in the ground, and then lighting the fuses , running away fast! and measuring the vibrations through different densities of materials (using special instruments, of course). For example, shock waves produced by dynamite pass through granite differently as compared to passing through oil. Earthquakes produce shock waves as well. Just much bigger ones.

• Cartographical data:  Cartography is the science of drawing maps. It can be quite complex. Given the capability of online mapping services to provide detailed driving directions between two points anywhere in America, the complexity of these systems is quite unimaginable. Often mentioned with the subject of online cartography are subject areas and buzzwords , such as XML Topic Maps (XTM) and Global Positioning Systems (GPS). There are also many different types of maps, and also different types of projections. For example, a political map shows capital cities and the borders of countries. A topographical map concentrates on elevations and topography. Topography includes things such as rivers, mountain ranges, valleys, and anywhere that it might be good to go swimming or skiing. Topography is the lay of the land with respect to the inorganic part of the natural world. The organic parts are the fauna and flora, and thus represented. A topographical map might show countries, borders, and cities but they are less of a priority than the topographical features. Back to projects. Different types of projections are vastly different. If you take a globe and flatten it out onto a two-dimensional map, the picture is quite different from reality. To make it look nice, you get what is called a mercator projection, which spreads things out more the closer you get to the poles. The result is that the distances at the poles, on the flattened out map, look much greater than they are in reality. Traveling from pole to pole, according to the map, has no distance whatsoever if you go from one map edge to the other. This is quite obviously completely silly. To the untrained eye, why not? This can be done from left to right. So why not up and down? If one can go from side to side instantaneously, why not up and down? A road map is just that: a road map where online services provide directions as well. Just imagine trying to figure out all directions between all addresses in every country in the world. Yoiks! The point I am trying to make is that cartography is far more complex and far more data intensive than it might seem at first glance.

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