Trent Sherrell's List: Taxonomy

• Taxonomies are relevant to various applications, implementations, software products, disciplines, and industries, whereas taxonomy itself is not really a discipline or industry.  This is apparent in how taxonomy shows up as a topic in presentation session in many different conferences. These include conferences and fields of: knowledge management, enterprise search, content management, digital asset management, semantic technologies, text analytics, document management, records management, indexing, information architecture and user experience.

• Enterprise systems are available with either perpetual or subscription licenses.
• Enterprise systems start at $25,000 and can be scaled up from single to unlimited taxonomy systems as needed.
• Express systems start at $1,200 per year and can be scaled up from single to multiple taxonomy systems as needed.

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• Calais is a rapidly growing toolkit of capabilities that allow you to readily incorporate state-of-the-art semantic functionality within your blog, content management system, website or application.

• Metadata is one of the most important ways to add value to online media and publications and achieve product differentiation in the market.

• Our software is a robust and scalable

   application that is based upon numerous open standards that make enterprise integration fast and reliable.
• Textual searching alone will never deliver the best results. Typically, when you type in a search query you will get back some of the information you wanted and a lot of information you didn't want.
• The root cause of this is that language is elastic. One word can mean many things and one thing can be described by many words. Taxonomies, also known as controlled vocabularies, help computers resolve the elasticity of language and find the relevant information while filtering out the noise. Taxonomy visualization and facetted navigation also enable people to browse in a way that they discover related information they might not otherwise have known existed.
• Making taxonomies useful requires that the centralized taxonomy management system be integrated with other IT components, including search, semantic search, facetted navigation, automatic or machine-aided indexing, content management and meta-tagging.
• The semantic web may be about to dwarf the social media revolution as a disruptive technology that will change the way people and computers relate to each other. With semantic search, people can find the things and ideas they are looking for, regardless of whether the words they use match the text on the page.

  
  

  Your websites, product catalogs, databases, publications and internal information assets can be optimized for semantic search by adding taxonomies and semantic metadata.

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• Knowledge "stewards" are information   professionals that work on the front lines to help teams achieve specific   business objectives -- land a client, implement a project, develop a   product, solve a problem.
• companies realize that the only sustainable advantage comes from connecting   good people with relevant knowledge. The knowledge that matters most   (because it's unique to the firm) is the know-how that employees and   teams accumulate through success and failure.
• But the most valuable information is   useless unless it's deployed and applied to solve problems. That usually   happens in teams in the outer layers of the corporate organization,   close to customers and suppliers. Knowledge stewards help "mine"   the firm's unique information and deploy it when and where it's needed.

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• Resource Description Language (aka RDF) is a data model useful for asserting facts about things.
• A triple is a simple assertion about a thing made in the form of subject-verb-object statement.
• A couple notes on terminology: a collection of triples share the that same subject is called a graph of triples. A triple with a literal-valued object (e.g. "@smyles") is called a data triple. A triple with a URI valued object (e.g. http://stuartmyles.blogspot.com) is called an object triple.

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• but provides no mechanism for asserting that a block of text     is    an article's headline.
• HTML is a language for specifying how content should look, not for specifying what the content means.
• search, social and aggregation sites that news publishers rely on for referral traffic can't automatically show a headline when linking to an article.
• HTML 5 Microdata and RDFa allow web authors to indicate that a certain portion of a page has a certain meaning.  It is up to the author, however, to provide the vocabulary used for enumerating and indicating such meanings.
• rNews is a data model for embedding machine-readable publishing metadata in web documents and a set of suggested implementations in both HTML 5 Microdata and RDFa.

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• rNews has been developed by the IPTC, a consortium of the world's major news agencies, news publishers and news industry vendors.
• rNews is an approved standard for using semantic markup to annotate news-specific metadata in HTML documents.
• Semantic markup allows publishers to attach specific meanings to various regions of an article page.
• rNews specifies the terminology and data model required to embed news specific metadata into HTML documents

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• hNews is a microformat for news content developed by the Associated Press and the Media Standards Trust.
• hNews extends hAtom, introducing a number of fields that more completely describe a journalistic work. hNews also introduces rel-principles (a format that describes the journalistic principles upheld by the journalist or news organization that has published the news item).

• parsers

  • A parser is a computer program that divides code up into functional components; "compilers must parse source code in order to translate it into object code"
• hNews extends hAtom. As the hAtom draft format notes, "Atom provides a lot more functionality than we need for a 'blog post' microformat, so we've taken the minimal number of elements needed." News stories typically introduce more fields (for instance, the publishing organization) than the current 0.1 draft of hAtom, and those fields are very important when reading or evaluating a news story. We focus on those fields that enable the development of semantic actions around news: license, principles, dateline (geo) and source organization.

• "Core" refers to the metadata terms as "broad and generic being usable for describing a wide range of resources".
• "Dublin" refers to Dublin, Ohio, USA where the work originated during the 1995 invitational OCLC/NCSA Metadata Workshop
• The Dublin Core Metadata Initiative (DCMI)^[9] provides an open forum for the development of interoperable online metadata standards for a broad range of purposes and of business models.
• The Dublin Core standard includes two levels: Simple and Qualified. Simple Dublin Core comprises 15 elements; Qualified Dublin Core includes three additional elements (Audience, Provenance and RightsHolder), as well as a group of element refinements (also called qualifiers) that refine the semantics of the elements in ways that may be useful in resource discovery.

• The Simple Dublin Core Metadata Element Set (DCMES) consists of 15 metadata elements:^[4]

   
   
  1. Title
   
  2. Creator
   
  3. Subject
   
  4. Description
   
  5. Publisher
   
  6. Contributor
   
  7. Date
   
  8. Type
   
  9. Format
   
  10. Identifier
   
  11. Source
   
  12. Language
   
  13. Relation
   
  14. Coverage
   
  15. Rights
• Audience, Provenance and RightsHolder are elements, but not part of the Simple Dublin Core 15 elements. Use Audience, Provenance and RightsHolder only when using Qualified Dublin Core.
• metadata is in a form suitable for interpretation both by machines and by human beings.
• The Dublin Core Abstract Model^[14] provides a reference model against which particular Dublin Core encoding guidelines can be compared, independent of any particular encoding syntax. Such a reference model allows implementers to gain a better understanding of the kinds of descriptions they are trying to encode and facilitates the development of better mappings and translations between different syntaxes.

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• A carefully crafted taxonomy improves the usability and searchability of your website.
• good taxonomy will force a healthy examination of the relationship between your content, your readers, and your business.
• A taxonomy is a top-down, controlled vocabulary.
• the bottom-up, many-to-many practice of readers tagging content with keywords. The collection of descriptive metadata that accumulates in this process is called a "folksonomy."
• There is also the practice of letting editors and contributors manually tag content as they go rather than forcing them to choose from a structured taxonomy. This is what I call a mess, and it pretty much destroys the main benefits of a real taxonomy, while not having sufficient scale to have the benefits of a folksonomy. Avoid this at all costs.
• Terms (or categories) may be used for navigation elements, ad serving, site search, and related article recommendation. So, taxonomy is much more than navigation. Rather, it is a way to add additional layers of structured information to your editorial assets so that you can do more interesting and profitable things with those assets.

• How to leverage a taxonomy

   
   
  •   Display related content and resources next to articles.
   
  •   Leverage "term pages," or pages with lists of all the stories with a common taxonomy term to create both a reader resource and critical mass for search engines.
   
  •   Encourage readers to dive deeper into your content by displaying the terms with each article, linked to the term pages
   
  •   Create taxonomy-based ad targeting by passing taxonomy terms from a story into your ad tags.
   
  •   Create taxonomy-based sponsorship opportunities or category sponsorships. As long as you have content and traffic to support it, you can keep narrowing the focus of popular categories to create highly-targeted branding or response campaigns.

  • Do we do all these things? In particular, the advertising component?
• Well-designed taxonomies increase page views, improve ad response and attract sponsorships.
• A good place to start is to look at both internal search queries and external search queries. If there are certain keyword phrases that appear with some frequency, those are probably excellent candidates for inclusion in your taxonomy.
• Make sure your taxonomy includes terms that map to advertiser needs so that ads can be targeted and sponsorships sold.  The best possible scenario is categories that are in demand by both readers and advertisers.  

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• there is consensus that information architecture has organization at its root. Basing my understanding on Morville and Rosenfeld’s approach, I define information architecture as: “the art and science of organizing information so that it is findable, manageable, and useful.”
• It also draws on the information retrieval roots of library science, emphasizing the importance of being able to find that which one seeks, whether known or unknown.
• In terms of the fields that I think most profoundly influence IA and are the best fodder for ongoing learning: Library and information science (my bias, obviously), HCI, cognitive psychology, ethnography and linguistics are among those I consider most critical.
• Metadata, at its broadest, is descriptive information about information. In the traditional library world, metadata is most commonly thought of as the big 3 from the traditional card (now online) catalog: Author, Title, Subject. But there are other fields as well-year published, publisher, shelf list number (administrative info for the library). In the online world, we use metadata for administrative purposes (to know when a document is “stale” and needs to be updated or deleted or to know the nature of a file so we know if we have the correct software to open it) and for retrieval purposes (the subject or keyword).
• That leaves us with keywords-what are they? Well, they’re a kind of descriptive metadata, generally describing the nature of the information. Keywords may be extracted directly from the text or they may be extrapolated-selected because they describe the text (subject, topic). The context in which keywords are selected and used is important for this reason. Keywords are by their nature fairly granular-a specific word applied to a specific item, often a narrow subset of a document (like a page or a paragraph), but even this granularity can vary in specificity (e.g., does the keyword describe the element in question specifically or generally?). Keywords are typically used for retrieval, as opposed to for administration.
• When keywords are applied to html pages-which is generally done for descriptive and retrieval purposes-they are typically applied via a metatag.
• Taxonomies have been around for a long time – they are hierarchical schemes for classifying things.
• taxonomy is generally associated with biology and systematics
• when people were talking about taxonomy on the web they were often talking about the traditional LIS definitions for classification schemes, controlled vocabularies, or thesauri.
• A strict interpretation of the definition of taxonomy would demand that the scheme be a pure hierarchy with one to one relationships.
• Polyhierarchy being the concept that something can “live” in more than one place in a hierarchy. The most common example of this is “piano” in a scheme of musical instruments; it is both a stringed instrument and a percussion instrument.
• A correlation of the different functional languages used by the enterprise to support a mechanism for navigating and gaining access to the intellectual capital of the enterprise.
• hierarchical taxonomy (a place for everything and everything in one place only), a polyhierarchical taxonomy (a Yahoo!-like scheme where items can be placed in more than one category), or a flat classification scheme (as with the simplest brochure sites), etc.
• Good labels (even in the form of rollovers for icons) can make a significant difference in the users’ ability to understand and use the tools.

  • The UX team is always in need of this service.

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• Does that mean that publishers, aggregators, and other content owners should police the Web to ensure that their content is not freely distributed? Not at all – one needs only look at the recent case of Wikileaks to see that it will be impossible to keep any content from showing up freely on the Web.
• the only logical step is figuring out how to make money in the current environment. This is where taxonomies can add value – by enabling the creation of new information products that connect disparate pieces of content with high-value applications and new markets.
• The most successful companies in the new Web paradigm, like Google, Facebook, and LinkedIn, are those that are building their businesses around the connectivity of content, people, and products. While in those examples, this connectivity is derived largely out of the behavior of people, conceptual connections are more appropriately the domain of taxonomies.

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• Information architecture involves many different aspects of web site creation and organization, but its principal tools are information organization techniques developed in other disciplines. Most of these techniques come from library science, such as thesauri, taxonomies, and faceted classification.
• Metadata is generally defined as "data about data,"
• in content management and information architecture, metadata generally means "information about objects" ("objects" here used as defined above), that is, information about a document, an image, a reusable content module, and so on
• The best-known vocabulary for metadata is Dublin Core [DC], which is a set of 13 properties that may be applied to information resources to describe them. These properties contain information such as "title", "creator", "subject", "description", "publisher", "date", "language", etc.

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• Metadata” describes an asset and provides a meaningful set of attributes that can be used to further classify or consume content. A “controlled vocabulary” is a restricted list of words or terms used for indexing or categorizing, often with cross-references pointing from a non-preferred term to the preferred term. To make it more fuzzy, the taxonomy (hierarchical structure) is also metadata.
• In general, taxonomy is a hierarchical structure for the classification or organization of data, historically used by biologists to classify plants or animals according to a set of natural relationships.

• In content management and information architecture, taxonomies are typically leveraged as a tool for organizing content. Strictly, a taxonomy is just the hierarchical structure of the content, but with most complex content ecosystems, the term also often refers to metadata and controlled vocabularies.

   
• Though people often use the term taxonomy to describe a site’s organization, for larger sites where content is used in multiple places – or for enterprise content management systems where data can be consumed on various platforms – taxonomy and IA are more often distinct from one another.

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• Taxonomies are quintessential to information architecture
• taxonomy is ancient Greek for "arrangement method"
• Information Architects tend to use the term in a more general sense to refer to just about any kind of hierarchical ordering of items into groups based on similarities and/or differences.
• One case where I do often use the word taxonomy is when referring to a controlled vocabulary of terms used for describing content.

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• As the structured/adaptive content conversation progresses, metadata and taxonomies will also become more and more important.
• The information provided in metadata makes the content findable and understandable to either a human or a computer.
• metadata as “information about the content that provides structure, context, and meaning.”

• There are three main types of metadata:

   
   
  • Structural: Defines the metadata elements that need to be collected; labels like title, author, date created, subject, purpose, etc. Defining these structural elements is typically based on a mix of organizational and system needs, along with standard schemas like Dublin Core.
   
  • Administrative: Often created automatically when content is entered into the CMS, these values are used to manage the content. Administrative metadata includes things like date created or author. They can sometimes include sub-elements about rights-management or preservation.
   
  • Descriptive: These values describe aspects specific to each content component, like title, subject, audience, and/or purpose.
• If you think of it like a form, the structural metadata supports which information needs to be collected (fields on the page), and the descriptive and administrative metadata provide the values for those form fields.
• Term list: A standardized list of terms created to insure consistent tagging and indexing. Think of it as a list of “preferred language.”
• Hierarchies: Often called a “taxonomy,” a hierarchy defines the structural framework used to classify terms into parent/child or broad-to-narrow relationships.
• Thesauri typically address three types of relationships: equivalent (synonyms), hierarchical (broad-to-narrow terms), and/or associative (related terms).
• At its simplest, a taxonomy organizes information, and metadata describes it. For the taxonomy to be able to organize the information, terms need to be stored as metadata. It all works together to make the content findable, recognizable, and useful.

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