Tag: Concept mapping

E-discovering Language to Launch Your Taxonomy

New enterprise initiatives, whether for implementing search solutions or beginning a new product development program, demand communication among team leaders and participants. Language matters; defining terminology for common parlance is essential to smooth progress toward initiative objectives.

Glossaries, dictionaries, taxonomies, thesauri and ontologies are all mechanisms we use routinely in education and work to clarify terms we use to engage and communicate understanding of any specialized domain. Electronic social communication added to the traditional mix of shared information (e.g. documents, databases, spreadsheets, drawings, standardized forms) makes business transactional language more complex. Couple this with the use of personal devices for capturing and storing our work content, notes, writings, correspondence, design and diagram materials and we all become content categorizing managers. Some of us are better than others at organizing and curating our piles of information resources.

As recent brain studies reveal, humans, and probably any animal with a brain, have established cognitive areas in our brains with pathways and relationships among categories of grouped concepts. This reinforces our propensity for expending thought and effort to order all aspects of our lives. That we all organize differently across a huge spectrum of concepts and objects makes it wondrous that we can live and work collaboratively at all. Why after 30+ years of marriage do I arrange my kitchen gadget drawer according to use or purpose of devices while my husband attempts to store the same items according to size and shape? Why do icons and graphics placed in strange locations in software applications and web pages rarely impart meaning and use to me, while others “get it” and adapt immediately?

The previous paragraph may seem to be a pointless digression from the subject of the post but there are two points to be made here. First, we all organize both objects and information to facilitate how we navigate life, including work. Without organization that is somehow rationalized, and established accordingly to our own rules for functioning, our lives descend into dysfunctional chaos. People who don’t organize well or struggle with organizing consistently struggle in school, work and life skills. Second, diversity of practice in organizing is a challenge for working and living with others when we need to share the same spaces and work objectives. This brings me to the very challenging task of organizing information for a website, a discrete business project, or an entire enterprise, especially when a diverse group of participants are engaged as a team.

So, let me make a few bold suggestions about where to begin with your team:

  • Establish categories of inquiry based on the existing culture of your organization and vertical industry. Avoid being inventive, clever or idiosyncratic. Find categories labels that everyone understands similarly.
  • Agree on common behaviors and practices for finding by sharing openly the ways in which members of the team need to find, the kinds of information and answers that need discovering, and the conditions under which information is required. These are the basis for findability use cases. Again, begin with the usual situations and save the unusual for later insertion.
  • Start with what you have in the form of finding aids: places, language and content that are already being actively used; examine how they are organized. Solicit and gather experiences about what is good, helpful and “must have” and note interface elements and navigation aids that are not used. Harvest any existing glossaries, dictionaries, taxonomies, organization charts or other definition entities that can provide feeds to terminology lists.
  • Use every discoverable repository as a resource (including email stores, social sites, and presentations) for establishing terminology and eventually writing rules for applying terms. Research repositories that are heavily used by groups of specialists and treat them as crops of terminology to be harvested for language that is meaningful to experts. Seek or develop linguistic parsing and term extraction tools and processes to discover words and phrases that are in common use. Use histograms to determine frequency of use, then alphabetize to find similar terms that are conceptually related, and semantic net tools to group discovered terms according to conceptual relationships. Segregate initialisms, acronyms, and abbreviations for analysis and insertion into final lists, as valid terms or synonyms to valid terms.
  • Talk to the gurus and experts that are the “go-to people” for learning about a topic and use their experience to help determine the most important broad categories for information that needs to be found. Those will become your “top term” groups and facets. Think of top terms as topical in nature (e.g. radar, transportation, weapons systems) and facets as other categories by which people might want to search (e.g. company names, content types, conference titles).
  • Simplify your top terms and facets into the broadest categories for launching your initiative. You can always add more but you won’t really know where to be the most granular until you begin using tags applied to content. Then you will see what topics have the most content and require narrower topical terms to avoid having too much content piling up under a very broad category.
  • Select and authorize one individual to be the ultimate decider. Ambiguity of categorizing principles, purpose and needs is always a given due to variations in cognitive functioning. However, the earlier steps outlined here will have been based on broad agreement. When it comes to the more nuanced areas of terminology and understanding, a subject savvy and organizationally mature person with good communication skills and solid professional respect within the enterprise will be a good authority for making final decisions about language. A trusted professional will also know when a change is needed and will seek guidance when necessary.

Revisit the successes and failures of the applied term store routinely: survey users, review search logs, observe information retrieval bottlenecks and troll for new electronic discourse and content as a source of new terminology. A recent post by taxonomy expert Heather Hedden gives more technical guidance about evaluating and sustaining your taxonomy maintenance.

Ontologies and Semantic Search

Recent studies describe the negative effect of media including video, television and on-line content on attention spans and even comprehension. One such study suggests that the piling on of content accrued from multiple sources throughout our work and leisure hours has saturated us to the point of making us information filterers more than information “comprehenders”. Hold that thought while I present a second one.

Last week’s blog entry reflected on intellectual property (IP) and knowledge assets and the value of taxonomies as aids to organizing and finding these valued resources. The idea of making search engines better or more precise in finding relevant content is edging into our enterprises through semantic technologies. These are search tools that are better at finding concepts, synonymous terms, and similar or related topics when we execute a search. You’ll find an in depth discussion of some of these in the forthcoming publication, Beyond Search by Steve Arnold. However, semantic search requires more sophisticated concept maps than taxonomy. It requires ontology, rich representations of a web of concepts complete with all types of term relationships.
My first comment about a trend toward just browsing and filtering content for relevance to our work, and the second one about the idea of assembling semantically relevant content for better search precision are two sides of a business problem that hundreds of entrepreneurs are grappling with, semantic technologies.

Two weeks ago, I helped to moderate a meeting on the subject, entitled Semantic Web – Ripe for Commercialization? While the assumed audience was to be a broad business group of VCs, financiers, legal and business management professionals, it turned out to have a lot of technology types. They had some pretty heavy questions and comments about how search engines handle inference and its methods for extracting meaning from content. Semantic search engines need to understand both the query and the target content to retrieve contextually relevant content.

Keynote speakers and some of the panelists introduced the concept of ontologies as being an essential backbone to semantic search. From that came a lot of discussion about how and where these ontologies originate, how and who vets them for authoritativeness, and how their development in under-funded subject areas will occur. There were no clear answers.

Here I want to give a quick definition for ontology. It is a concept map of terminology which, when richly populated, reflects all the possible semantic relationships that might be inferred from different ways that terms are assembled in human language. A subject specific ontology is more easily understood in a graphical representation. Ontologies also help to inform semantic search engines by contributing to an automated deconstruction of a query (making sense out of what the searcher wants to know) and automated deconstruction of the content to be indexed and searched. Good semantic search, therefore, depends on excellent ontologies.

To see a very simple example of an ontology related to “roadway”, check out this image. Keep in mind that before you aspire to implementing a semantic search engine in your enterprise, you want to be sure that there is a trusted ontology somewhere in the mix of tools to help the search engine retrieve results relevant to your unique audience.

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