Thursday, January 29, 2015
Information presented to customers must be capable of meeting near-instant information demands in a multitude of perspectives. This includes all end users, internal and external. Organizations will need to continue to be versatile and clever in their approach to data management.
Digital marketers are becoming quite clever in dealing with data, using it to persuade their (or their clients’) customers or potential customers. Taking principles from usability, marketers now use terms such as “user design”, “user experience” (UX) and “user interaction” (UI) and develop specialty roles to turn data into the most pleasant user experience possible. The food, beverage and hospitality industries aren’t the only ones in the experience this issue. Every industry is.
Build to Further Understand
Taxonomy and information architecture is not just about designing a great way to organize content for the end user. Taxonomy can also be used to understand data. Information, its structure and agility are keys to modern design techniques where such vast volumes of data exist.
Your organization can benefit from developing taxonomy for your organization’s information. Designing your information flow isn’t always as easy as it sounds. Consulting with a trusted professional that can analyze various aspects of your business is often needed to alleviate the stresses of a complex business taxonomy. A specialist can take your data and help you make sense of it. Whether you are a hospital that needs to define protocols for accessing patient data or a retail website seeking comprehensive analysis of information about web traffic, an internal audit of information systems can help to get you on the right track toward efficiency.
Start with assessing your digital (and even non-digital) tools to determine problem areas within the organization such as incomplete records or inconsistent rules or terms. The way in which systems communicate with customers, employees or other stakeholders is important to consider as well. Check that these systems can perform essential functions properly and that proper access and other rules are clearly defined. A master data management solution will help with this. Many fortune 1000 companies are going this route to deal with their organization’s information.
Agile Systems Will Assist in Achieving Maximum Comprehension
The right information asset management tools make all the difference. Having software for terms and concepts will provide users within the organization the right context for use. Thesaurus management, ontology software, metadata or cataloging software, auto-categorization, search, and other tools used in concert will keep the stability.
For example, in dealing appropriately with taxonomy, an agile system including auto-categorization and search tools (including text mining) would contain pre-installed user editable and non-editable taxonomies, be able to auto-generate editable taxonomies, support import of editable and non-editable taxonomies. To be agile for any number of end user type, these must be able to play out in several different varying combinations.
The same principle applies to other software categories like content management or thesaurus software. Search functions, for example, are more useful to the end user when they contain spell-checking functions or multiple display options. Remember, these principles apply to both the internal and external users. Remember that information architecture mastered on the inside will translate better to the outside.
Taxonomy and information architecture should be the foundation of an enterprise view of the customer. So how must an organization view its own vocabulary? Ensure that your master data management is interpreting terms consistently and includes context for those terms. Without context, people are often left searching for clues instead of getting the information they came for.
Maintaining Culture While Establishing Order
The above phrase sounds more like a political statement than one of taxonomy. However, when you think about it from a business perspective, it makes some sense. When you are implementing your agile system for taxonomy and information architecture, you don't want to disrupt the critical flow of business nor the information that is required to actually do business.
What you do want is to be able to open the pipeline of information further to increase productivity and enable efficient processes within the organization. That statement sums up the general need to implement an agile system for handling information.
Part of the solution to this is governance and compliance controls. By introducing hard controls for governance and compliance, you are forming a backbone with controls for how systems are using and integrating data. Your taxonomy, metadata and other information may connect business processes or even use content to complete or help complete a variety of tasks.
The exact structure of any organization varies from enterprise to enterprise and in parallel does their culture. This contrast can be reckoned with reason. The key to being able to harness information collectively, selectively and to varying degree is what will make the major difference in opening that pipeline up with controls in place to establish order.
Taxonomy Soup: Collaboration, Integration and Access
Here is analogy to social science: Just as the language of a region or culture may vary in dialect, so too does the language of business. The language of business can be quite diverse. Between industries, organizations, departments, fields of study/practice and a wide variety of other factors, confusion exists. The real benefit to a system with agility is the ability to communicate more efficiently. The combination of collaboration, integration, and access are the key ingredients to making the perfect taxonomy soup.
The ability to sort terms is very important and will become even more important in the big data era. A great system will be one that can differentiate taxonomy with due diligence. Collaborating will become more efficient this way.
By integrating data that does not fit into the dialect of terms, the organization will be able to make better use of its information assets, whatever they may be. This includes getting all of the information into the right places and ultimately into the right hands in the correct way. Policies and procedures are important examples of such data.
Analyze Your Needs Carefully
Take a look around your organization. Take notes on every detail you can to make an informed decision about what to implement and where. Consulting with a professional is the next step. The aforementioned details of creating an agile environment for taxonomy and information architecture within an enterprise of nearly any size are helpful in beginning to form a strategy for handling your enterprise information. Consulting a professional will help alleviate the overwhelming and burdensome task of data complexity.
Monday, January 12, 2015
Taxonomy is becoming so much more important in the digital age that entire enterprises may one day develop out of the need just to classify information. The many ways we have traditionally classified content has exponentially grown in the digital age to a size un-imagined and continually growing.
The Library of Congress and other libraries, large and small, have gone to using digital tools to classify and re-classify information about books, documents, texts and even multimedia content. The Internet was, of course, developed to help more easily share and organize documents and other content across a computer network. Now, here we are with the cloud and big data.
Where to begin?
The proportion of data-to-enterprise, or even data-to-individual, can become difficult or even unmanageable without the right tools or experience to guide you. As humans and consumers, we tend to expect that our options will be categorized into specific types based on the larger type. For instance, if we buy a computer, the choices are usually as follows: brand, device type, operating system, etc.
Then we get into Apple vs Dell, Desktop vs Tablet or BlackBerry vs Android. The more immediate platforms that come to mind are Google or Bing search engines, hashtags or networks on social media like Twitter and Facebook. These are the most recent consumer examples of classifying information in a multitude of ways using software. Enterprises of all industries, however, are becoming more dependent on systems to help them manage information to scale.
The time it takes members of an organization to find important or relevant information is productivity lost. It also adds to personnel frustration, even at management level.
Time to Give Industries Options for Information Management
Companies are responding to the needs of industry. Taxonomy, metadata, ontology, data virtualization and data governance are some of the key areas of need for many organizations dealing with vast amounts of data coming from customers, partners, legal or other channels.
Top Quadrant, who released a web-based taxonomy solution recently, is an example of how these enterprise needs are so far being addressed, according to KMWorld.
TopBraid, the software referenced, is able to help end users reference data with more easily accessible visual models of the data, laid out in a clean way.
Much more emphasis on visual representation of data is becoming an IT industry-wide way to tackle some of the problems associated with extrapolating and explaining complex data sets. Asian countries have had a great deal of success, in fact, in using visual models to teach mathematics and transition students into new topics easier, which Americans have had some difficulty with in many educational settings.
TopQuadrant is just one recent example. There are tools and software being developed in the market to deal with this exponentially growing challenge.
Taxonomy Time for Taxonomists
So what does a taxonomist do that can help arrange and set a standard for all of this enterprise information that we are dealing with in ever increasing amounts? Well, for one, taxonomists are tasked, not only with categorization of terms, but also governance and definition of those terms as well.
They often use a commercial software that is dedicated to this work, such as a dedicated thesaurus or taxonomy management application. Some of these can be developed internally as well, for the right organization, as long as it fits their particular needs.
Sometimes taxonomy management tools are part of another suite or software, in which taxonomy is a feature. In the case of Drupal, a website content management software tool to build and maintain websites, taxonomy is used to define or classify content, which can then be configured to display nodes, pages, etc. to the end user. Sometimes, other software can be used, such as spreadsheets or other types of software tools.
Lastly, open source software for taxonomy and ontology are becoming available for use as well.
The benefits to having a system or person that maintains taxonomy within the enterprise are several. One benefit is that information is organized, as I have already alluded to. Another is that this information can also be made easier to find for customers, personnel, vendors, supply partners, etc., which I have also discussed. One reason that we have not discussed is standardization.
This refers to terminology and jargon within your particular company. Every company can create a manual of terms, glossary, thesaurus, etc. But a taxonomist or someone working with taxonomy software can refine this process and create a standard that efficiently works across the company, so everyone is in compliance. It is kind of like having a style guide, but only for key terms of the business.
Compliance is another key benefit to all of this. Regulations need to be followed and adhered. There are other legal and regulatory impacts that information has and taxonomy, ontology and information management are a few ways to stay ahead of the mess. Information audits can be a great way to find holes in your system and develop ways to patch those holes for greater governance and compliance. All of this can save us time and money on our business operations in one way or another.
Techniques for Creating a Great Information Structure
Taxonomy and information management starts with a few basic techniques to help guide end users to information they have are trying to navigate to. The less time to navigate, the better.
Not only are terms important, but so are their relationships. Sometimes information can be found using one term or another, depending on the scenario. If you are looking for blue cars that are fast, you could search cars by color or by speed, as one example illustrates this point.
Standards should also weed out content that is irrelevant or invalid. Other types of information related to terms can be used in conjunction with taxonomy. There should be clear hierarchies of information within the enterprise as well.
All of this data should be able to be used with other tools like content management, indexing, search and others. It should always support ANSI/NISO Z39.19 or ISO 2788 thesaurus standards. Different classes of information may apply to sets or subsets even.
Make sure that any software you use will generate reports for you on analytics (of terms) and so forth. This is very important.
There are a variety of ontology and thesaurus options available. They are available in a multitude of platform formats. Here are a few: MultiTes Pro (Microsoft Windows), Cognatrix (Apple Mac OS X), One-2-One (Windows) and TheW32 (multi-platform). There don't appear to be many options for the mobile platforms yet (iOS, Android, BlackBerry and Windows Phone).
The information management problem in the world of big data seems pervasive, but there is a growing trend toward developing new ways of dealing with it. Now is the time to start looking at creating a plan to develop a system for dealing with taxonomy, oncology and information management to help your organization users to access data more quickly, efficiently and sensibly.
The more content builds up, the more the organization needs to change, adapt and most importantly, handle of the big data involved.