The Xplor View - October 2008 - (Page 23)

What are the latest developments in knowledge management for large organisations? - Part three One example of the use of RDF is the web service MusicBrainz. MusicBrainz MusicBrainz is a web service operated by the nonprofit making organisation MetaBrainz, based in California. MusicBrainz classifies itself as a ‘user-maintained community music metadatabase.’ Examples of music metadata include information such as artist name, track name, year of release, and the track listing of a particular album. This information is stored in a database that can be edited and updated by users. At the time of writing, the database contained details of 277,385 artists and 5,263,358 tracks. The information in MusicBrainz database is available in both HTML and RDF format. The information in the database—for example artist, album, or track details—is given a Uniform Resource Identifier (URI). An RDF-based application programming interface is also available. This allows references to separate pieces of information in the database to be made to each other, as well as allowing the information to be accessed by external applications and websites. Examples of the use of this database access by third-party organisations include: • The Spanish-based Linkara Música, a social networking site • Last.fm, an Internet radio and social networking site allowing people to share their listening habits and get recommendations based on the songs they listen to Organisations have realised the importance of sourcing knowledge from all data types Unstructured data includes file systems and what is found in file systems (e.g. individual documents) as well as a whole new class of content proliferated by new digital systems such as PDAs, iPods, and mobile voice mail. Of the three types of data, the unstructured category is growing the fastest and large organisations are beginning to awaken to the possibilities it holds for storing and communicating tacit knowledge. Whether this is mission-critical or not, is yet to be determined. Unstructured data consists of two basic categories: • Bitmap objects: Inherently non-language based, such as image, video, or audio files • Text-based strings: Based on a written or printed language, such as Microsoft Word documents, and e-mails Both of these can be classified as data, but the technology and methodology for harnessing relevant information from bitmap objects is still in its infancy. Most of today’s technology addresses text-based strings. Semi-structured data such as e-mail, has some form of hierarchy and relational characteristics, but is still freeform and its proliferation is not easy to forecast. The business world has recently recognized that this class of information is mission-critical. This category of data requires organisations to formulate policy and defence against compliance demands and litigation, which means companies are expected to identify, isolate, and quarantine groups of information for court and evidence purposes. It also requires organisations to set policies for spam e-mails. Structured data is the food for most databases and applications that leverage databases. It is usually stored in a series of rows and columns organised according to a set of rules to enable efficient storage and easy retrieval. It is straightforward to tackle structured data and achieve large cost savings through a tiered architecture. Enterprise Information Integration products are making it easier to access data and content Enterprise Information Integration (EII) is a data integration technology, which can be used to facilitate BPM. It links information within the organisation from different data sources, such as warehouses and databases, in real-time, upon demand. The EII products do this by forming an intermediary level of data, which enables it to access and federate all relevant information from scattered and different data sources. They do this in a standard and unified way, by using one entry-point, instead of connecting multiple times, directly with each source. Due to this capacity EII has become the latest term associated with the concept of the ‘virtual centralised database.’ Figure 3.3 illustrates the theory of how EII technology works. Recent studies have shown that the main organisational drivers for using EII technology are because it can be run and operated alongside other data integration endeavours and provides enhanced information access. Large organisations use EII because it can combine data from various sources, which results in betterinformed decision-making. The information extracted can also support business intelligence and analysis. The ultimate vision for this technology is that it should enable organisations to have access to current information from integrated data sources, with horizontalaccess across both databases and platforms creating a holistic view of its internal and external environment, while providing strong data consistency. In the past, this would have been considered impossible to achieve. Now, however, it is just seen as being hard to do but a real possibility for the future. One example of an organisation that managed to bring together its different data types by using EII technologies is ING. ING Worldwide ING Worldwide—a financial organisation that deals with banking, asset management, and insurance—realised the importance of having consolidated data formats which are of greater use in transactions, business analyses, and especially for business intelligence. It decided to use EII within a business intelligence architecture to help it achieve this goal. ING wanted to be able to get a constant and reliable view of their data, processing it through an adaptable architecture so that the technology could be reused in as many combinations and variations as possible. However the structure of their organisation with its many different business units made this a complex task. The EII route was a difficult one due to a shortage of qualified suppliers and vendors. No one technology could cover all the different priorities. Some vendors could address certain aspects of their architecture and, in other cases, there was no existing solution. Despite this challenge, ING successfully adjusted and refined its information architecture. In the usual data creation path for an organisation, once data is extracted from source it is then sent to a central 23 Issue 6 October 2008 The VIEW Journal Xplor European Edition http://www.Last.fm

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The Xplor View -� October 2008 Contents TPE Master Class: Three Ways to Tame your Print-to-Mail Workflow Right Now Mission Impossible: Embracing Environmental Concerns TPE Master Class: Implementing a Lean Working Environment Improving Business Processes Yields Award-Winning Business Performance How Do� You Effectively Win New Business Writing a Marketing Plan to Win New Printing Clients How Buying Strategies Have Affected How the Industry Sells Let's Talk About Integrated Customer Communications Management:�Transpromo...It Takes a Village! Knowledge Management Part 3 XDU: Leading the Education Revolution Kodak plus Xplor equals XDU Around the World Xplor Europe News:�Short News Items for the Xplor UK�Programme and Europe News

The Xplor View - October 2008

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