Enterprise Knowledge is continuing our new webinar series, The Semantic Exchange with the fourth session. This session is designed for a variety of audiences, ranging from those working in the semantic space as taxonomists or ontologists, to folks who are just starting to learn about structured data and content, and how they may fit into broader initiatives around artificial intelligence or knowledge graphs.

This 30-minute session invites you to engage with Yumiko Saito’s case study, A Semantic Layer to Enable Risk Management at a Multinational Bank. Come ready to hear and ask about:

• The challenges financial firms encounter with risk management;
• The semantic solutions employed to mitigate these challenges; and
• The value created by employing semantic layer solutions.

This webinar will take place on Thursday July 17th, from 1:00 – 1:30PM EDT. Can’t make it? The session will also be recorded and published to registered attendees. View the recording here!

The post The Semantic Exchange: A Semantic Layer to Enable Risk Management at a Multinational Bank appeared first on Enterprise Knowledge.

Enterprise Knowledge is pleased to introduce a new webinar series, The Semantic Exchange. This session is the third of a five part series where we invite fellow practitioners to tune in and hear more about work we’ve published from the authors themselves. In these moderated sessions, we invite you to ask the authors questions in a short, accessible format. Think of the series as a chance for a little semantic snack!

This session is designed for a variety of audiences, ranging from those working in the semantic space as taxonomists or ontologists, to folks who are just starting to learn about structured data and content, and how they may fit into broader initiatives around artificial intelligence or knowledge graphs.

This 30-minute session invites you to engage with Kathleen Gollner’s blog, Metadata Within the Semantic Layer. Come ready to hear and ask about:

• Why metadata is foundational for a semantic layer;
• How to optimize metadata for use across knowledge assets, systems, and use cases; and
• How metadata can be leveraged in AI solutions.

This webinar will take place on Wednesday July 9th, from 1:00 – 1:30PM EDT. Can’t make it? The session will also be recorded and published to registered attendees. View the recording here!

The post The Semantic Exchange: Metadata Within the Semantic Layer appeared first on Enterprise Knowledge.

Enterprise Knowledge is pleased to introduce a new webinar series, The Semantic Exchange. This session is number two of a five part series where we invite fellow practitioners to tune in and hear more about work we’ve published from the authors themselves. In these moderated sessions, we invite you to ask the authors questions in a short, accessible format. Think of the series as a chance for a little semantic snack!

This session is designed for a variety of audiences, ranging from those working in the semantic space as taxonomists or ontologists – to folks who are just starting to learn about structured data and content, and how they may fit into broader initiatives around artificial intelligence or knowledge graphs. 

This 30-minute session invites you to engage with Ben Kass’s white paper, What is Semantics and Why Does it Matter?. Come ready to hear and ask about:

• Why should you model the semantics of your data?
• What does it mean to define semantics?
• How do we capture semantics for use by machines?

This webinar will take place on Wednesday July 2nd, from 1:00 – 1:30PM EDT. Can’t make it? The session will also be recorded and published to registered attendees. View the recording here!

The post The Semantic Exchange: What is Semantics and Why Does it Matter? appeared first on Enterprise Knowledge.

Enterprise Knowledge is pleased to introduce a new webinar series, The Semantic Exchange. We’re kicking off a five part series where we invite fellow practitioners to tune in and hear more about work we’ve published from the authors themselves. In these moderated sessions, we invite you to ask the authors questions in a short, accessible format. Think of the series as a chance for a little semantic snack! 

This session is designed for a variety of audiences, ranging from those working in the semantic space as taxonomists or ontologists – to folks who are just starting to learn about structured data and content, and how they may fit into broader initiatives around artificial intelligence or knowledge graphs. 

This 30-minute session invites you to engage with Bonnie Griffin’s infographic, Why Your Taxonomy Needs SKOS. Come ready to hear and ask about: 

• Why SKOS is the W3C-recommended format for taxonomies 
• How SKOS unlocks more value than a simple term list 
• What your organization misses out on with non-SKOS taxonomies

This webinar will take place on Wednesday June 25th, from 1:00 – 1:30PM EDT. Can’t make it? The session will also be recorded and published to our knowledge base following the session. View the recording of the first session here!

The post The Semantic Exchange: Why Your Taxonomy Needs SKOS Webinar appeared first on Enterprise Knowledge.

An experienced instructor of taxonomy workshops and taxonomy/ontology consultant, Hedden was invited to present this special session comprising of two 45-minute parts, after which she will be joined by Taxonomy Boot Camp chair Helen Lippell for a 45-minute live “Ask Us Anything” session in the Zoom meeting event. In the first part, Hedden addresses what taxonomies are and why they are useful, and in the second part she discusses various components of taxonomy projects. 

Taxonomy Basics takes place Wednesday, May 1, 9:00 – 11:45 am EDT, 14:00 – 16:45 BST. See the full session outline and register here.

Hedden will also be giving a short presentation “Tips for Taxonomy Hierarchies” in the fall edition of Bite-Sized Taxonomy Boot Camp London, joining several other expert speakers for the half-day event on Wednesday, October 9, 2024. Tickets are for the series of three half-day events on March 20, June 19, and October 9. See the full program and register here.

The post EK’s Heather Hedden to Present Taxonomy Basics at the Virtual Taxonomy Boot Camp London appeared first on Enterprise Knowledge.

Benefits of Taxonomies and Ontologies

Taxonomies (hierarchical or faceted structured controlled vocabularies of concepts) primarily enhance search and retrieval of content, but they have related benefits. Taxonomy uses and benefits include: 

• Tagging: to index content consistently so that retrieval is comprehensive and accurate
• Normalization: to bring together different names, localizations, and languages for concepts
• Standard search: to enable users to find content about something (whereby the user’s search string matches taxonomy concepts)
• Topic browse: to enable users to explore subjects arranged in a hierarchy and then get content on the selected subject
• Faceted (filtering/refining) search: to enable users to find content that matches a combination of basic criteria
• Discovery: to enable users find additional, related content tagged with the same concepts; to explore broader, narrower, and (sometimes) related taxonomy topics
• Content curation: to create feeds or alerts based on pre-set search terms
• Metadata management: to support identification, comparison, analysis, etc., in addition to content retrieval

Ontologies (semantic models comprising the types/classes, semantic relationships, and attributes of entities) were originally for describing a domain while also supporting inference for learning more about the domain. However, when entities from a taxonomy are combined with an ontology, benefits and capabilities include:

• Modeling complex interrelationships (e.g. in product approval or supply chain processes) while also connecting to content
• Executing complex multi-part search queries
• Exploring explicit relationships between concepts, not just broader, narrower, or related
• Searching across datasets, not just searching for content
• Searching on more specific criteria that vary based on category (class)
• Visualizing concepts and semantic relationships
• Reasoning based on inferences
• Creating knowledge graphs (incorporating instance data), upon which additional knowledge applications can be built

“Content” refers to files, documents, images, intranet pages, spreadsheets, etc. “Data” refers to such things as the information within database records and the cells within tables or spreadsheets. Sometimes people are looking for content, sometimes they are looking for data, and sometimes they are looking for both. Taxonomies focus on connecting users to content, and ontologies focus on data, so a combination of taxonomies and ontologies can connect users to both content and data, in addition to connecting the content and data together. 

Taxonomies and Ontologies Combined

Taxonomies and ontologies have different origins (library/information science vs. computer/data science), and thus usually different experts, but these two knowledge organization systems have converged greatly in the past decade. There are two primary reasons for this convergence:

• The adoption of shared Semantic Web (World Wide Web Consortium) standards, whereby both taxonomies and ontologies are built on the same data model, RDF (Resource Description Framework), and other models and standards based on RDF. Thus they can be built in the same tools and connect to each other seamlessly.
• The increased business needs to manage and extract knowledge from growing volumes of content and data together in sophisticated ways  as well as the growing demand for data and information, not just for documents and pages

As mentioned above, there are different definitions for ontologies, and a leading difference concerns whether individual entities are included within the scope of “ontology.” An ontology is either:

1. 1) A model of a knowledge domain, comprising classes, semantic relationships, and attributes (along with prescribed rules or constraints on each of these components, etc.), or

• 2) A model of a knowledge domain, comprising classes, semantic relationships, and attributes, plus all the individual members of the classes, which are described in controlled vocabularies, including taxonomies

The following pair of diagrams listing different controlled vocabulary and knowledge organization systems illustrate the views of these two different definitions of ontologies. 

• 1) Ontology as a model of a knowledge domain that serves as a semantic layer connected to various controlled vocabularies:
  
  

1. 2) Ontology as the most semantically rich type of knowledge organization system, which includes all the features/components of taxonomies, thesauri, and named entity controlled vocabularies plus more semantics:

Depending on how you define ontology, above, a taxonomy can then either

1. be enhanced to include an ontology as an additional semantic layer (definition #1), or
2. be used as an important component of an ontology (definition #2

Ontologies alone may have taxonomic features of deep hierarchies of classes and subclasses, but without a taxonomy or thesaurus built on the SKOS (Simple Knowledge Organization System) data model, the full range of functionality of alternative labels, labels in other languages, multiple definitions and types of notes, etc. are not supported. Taxonomies provide a linguistic aspect that ontologies alone lack. 

Ontologies alone would support modeling, exploring, and visualizing entities and their relationships, which may be based on their properties. Ontologies may also support inference reasoning. However, functions involving semantic search, which brings together synonyms and disambiguating homonyms, etc. require taxonomies, thesauri, or other controlled vocabularies. 

Creating an Ontology Based on Taxonomies

Regardless of which of the two definitions of ontology you prefer, if you already have a taxonomy, which is often the case, you can extend it to become or or add an ontology and then reap the additional benefits of the combined knowledge organization system. If you have multiple taxonomies and other controlled vocabularies, an ontology can link them together. 

Whether you are building a taxonomy, ontology, knowledge graph, or a broader digital transformation for knowledge management, there should be a combination of top down and bottom up approaches to the process. The top-down methods focus on obtaining input from stakeholders, whereas the bottom-up methods focus on analysis of content and data. 

The basic approach to building an ontology, especially a business or enterprise ontology, is to identify groups of things (or “business objects”), which become classes in an ontology, identify relationships between pairs of classes, and identify important characteristics (or attributes) of members of a class. The top-down approach to this task involves interviewing stakeholders and conducting brainstorming sessions and focus group sessions to identify these classes, relationships, and attributes. The bottom-up approach to ontology creation often involves looking at spreadsheets and tables of critical data pertaining to different business objects. 

A quicker bottom-up approach to creating ontologies is to look at the taxonomies and controlled vocabularies you already have. Each taxonomy hierarchy, controlled vocabulary, term set, facet, or what is designated as a “concept scheme” in the SKOS model can be considered to be a class in an ontology. Additional classes or subclasses might get added, and some term lists might not be needed in an ontology, but often concept schemes can serve as the basis of classes, one-to-one.

Facets in a faceted taxonomy enable browsing or limiting searches for content items by certain aspects. However, content needs to be limited to that of a similar kind that shares the same facets, such as all product pages, all reports, all employee profiles, or all media files. If we can convert the facets to ontology classes, create new semantic relationships between them, and tag all content, a search application is no longer limited to a certain kind of content or asset. Rather, conditional queries in the same application/user interface can be targeted at any kind of content. 

Example: Converting Facets to Classes to Build an Ontology

Consider an example for an organization’s internal knowledge base. There may exist multiple repositories of content and data, each with its own faceted taxonomy and its own user interface.  

• Reports could be searched using a Reports faceted taxonomy, which has the facets Report Type, Subject, Author Name, and Division.
• Employees as experts could be searched using a People faceted taxonomy, which has the facets Name, Job Title, Location, Division, Skills, and Subject Expertise.
• Media files could be searched using a Digital Asset Management faceted taxonomy, which has the facets Subject, Location, Event, Person Depicted, and Creator

We could create classes to reflect the aggregation of all of these facets.

• Division
• Employee name (which also includes report authors and media asset creators)
• Event
• File type (with subclasses for Document type and Asset type)
• Job role (including titles)
• Location
• Skill
• Subject (including expertise areas

Then we could consider the relationships or links between the classes, and create verb-based semantic relationships. Any class that is a target/object of a relationship can be a target of a search query. The following are just some examples, but not a complete list with all reciprocal relationships.

Employee knows Subject
Employee created File Type
Employee possesses Skill
Employee basedIn Location
Employee belongsTo Division

File Type hasTopic Subject
File Type createdBy Employee
File Type belongsTo Division

Subject knownBy Employee
Subject topicOf Division
Subject topicOf File Type
Subject topicOf Event

Event basedIn Location
Event belongsTo Division
Event hasTopic Subject

Finally, you should consider what additional data is of importance for the entities in each class, such as contact information for Employees and dates of publication for files and for the occurrence of Events. These would normally not exist in a taxonomy, but should be added to the ontology to support the exploration of more kinds of data.

Conclusions

Combining a taxonomy with an ontology provides many benefits and capabilities which a taxonomy alone or an ontology alone (as merely a semantic model) cannot provide. 

Building an ontology based on one or more existing taxonomies is an efficient and very suitable method of bottom-up development. The existing taxonomies and controlled vocabularies provide a basis for knowledge modeling. Furthermore, by leveraging an existing taxonomy that has already been tagged to content, certain benefits of the ontology will already be in place. 

Managing the taxonomy plus the ontology as a semantic layer also has benefits. A taxonomy plus ontology is more flexible and adaptable than a single large ontology, since the taxonomy changes more frequently than does the ontology. Also, more taxonomies and controlled vocabularies can easily be added in the future. There are also several software options for combined taxonomy-ontology creation and management. These applications are based on RDF, including SKOS for taxonomies and RDF-S and OWL for ontologies. This facilitates the technical aspects of extending a taxonomy to become an ontology. 

Although extending taxonomies to become ontologies is easier than creating ontologies from scratch, it still requires ontology design expertise. For assistance in extending your taxonomies into an ontology, contact us to get started.

The post Extending Taxonomies to Ontologies appeared first on Enterprise Knowledge.

An experienced instructor of taxonomy workshops and taxonomy/ontology consultant, Heather will take advantage of the first in-person World IA Day event in Boston since 2020 by leading a brief interactive workshop on techniques for taxonomy creation. Taxonomies are an important component of information architecture that provide the guiding terms and labels for users to find the information they need on a website, intranet, or search application. 

Addressing the World IA Day 2024 theme of “Context,” Heather will demonstrate methods of taxonomy creation that address the context of specific content and users, including content analysis and user interviews. The workshop is aimed at all levels. World IA 2024 Boston will take place at the Boston Public Library, 700 Boylston St, Boston, MA, 1:00 – 3:00 pm on Saturday, March 2. Heather follows the keynote speaker Dawn Russell, and there will be networking time at the end of the session. Registration is free (although $5 donations are suggested), and space is limited. Register at: https://ti.to/worldiaday/wiad24-boston

The post Heather Hedden to Speak at World IA Day 2024 Boston appeared first on Enterprise Knowledge.

The Solution

To support the creation of a taxonomy for the healthcare organization’s call center, EK facilitated a taxonomy design workshop with key stakeholders from the call center, consisting of several succinct sessions with dozens of participants from across the organization. In order to gain a better understanding of the healthcare organization’s current user needs, EK facilitated five different activities: a Personas Activity, a User Stories Activity, a Content Types Activity, a Metadata Fields Activity, and a Taxonomy Governance Activity, using the online whiteboard tools Mural and RetroTool. EK also facilitated guided discussions on Taxonomy, Core Workflows, and Content Governance. EK compiled these findings into a Taxonomy Workshop Report which contained our recommendations surrounding baseline taxonomy design, content types, and information architecture, as well as suggestions for content management and taxonomy governance, including a proposed taxonomy governance model. 

Following the delivery of the Taxonomy Workshop Report, EK held additional sessions with the company stakeholders to better understand their current content management and governance processes. To summarize these findings and analyses, EK delivered a Content Governance Plan which provided detailed recommendations on how the healthcare organization could effectively store and manage their content in the short- and long-term. More specifically, the Content Governance Report included a Content Governance Model with associated roles and responsibilities that aligned to governance and KM best practices; governance processes and workflows for adding, updating, and archiving content; a structure for content governance team meetings; preliminary content management best practices for formatting and tagging content; and recommended next steps for the healthcare company to ensure optimal value was being derived from their call center content.

The EK Difference

To garner buy-in from users, EK facilitated multiple sessions following the delivery of the Taxonomy Workshop Report to answer both technical and non-technical questions about the report itself, as well as how the taxonomy would actually function within the knowledge management platform. By engaging in conversation with call center stakeholders, EK was able to answer pointed questions about specific aspects of the taxonomy report that otherwise would not have been addressed, further streamlining acceptance and adoption and allowing us to communicate the value of the taxonomy in business terms to a wide and diverse user group. EK also incorporated this direct stakeholder feedback into the Content Governance Report, highlighting and providing strong evidence for the most important and meaningful components based on what was learned during the additional sessions. 

Additionally, EK leveraged our years of experience and subject matter expertise in taxonomies and content management consulting to tailor our workshop agenda and materials to the specific challenges being faced by the call center, ultimately delivering more applicable and actionable plans that align with both industry best practices and the strategic goals of the overarching organization.

The Results

During this 2-month effort, EK identified and defined the high-level, prioritized metadata fields for the taxonomy design, as well as the foundational structure for the information architecture and governance model necessary to support the KM platform implementation. Following the taxonomy work, EK also defined high-level content governance roles and responsibilities, as well as policies and procedures, to help the multinational healthcare organization maintain its content going forward. EK delivered all of this in a Taxonomy Workshop Report and Content Governance Report, and maintains a positive relationship with both the knowledge management platform and the healthcare organization to date. 

The post Taxonomy Workshop and Content Governance for a Multinational Healthcare Company appeared first on Enterprise Knowledge.

The Solution

EK facilitated a series of workshops, interviews, and focus groups with subject matter experts, content creators, and technical partners to define the current and target state of the retailer’s Content Management maturity using EK’s proprietary 50-factor Content Management Benchmark. EK then partnered with the learning team to define a fully customized, iterative, task-based content management strategy, implementation roadmap, and KM Platform design to help the learning team improve their Content Management maturity over a multi-year period using a phased approach. The KM Platform design featured recommendations to leverage new and existing technologies, including a metadata management hub, taxonomy management system, knowledge graph, and search engine. These technical recommendations have resulted in the creation of a digital library that is currently helping the retailer to more effectively and efficiently manage the sheer scale of content in their learning ecosystem, increase the organization’s speed in creating learning content, and decrease the time it takes associates to find and discover lessons.

The EK Difference

EK leveraged its unique, 50-factor benchmark to develop a comprehensive analysis of the retailer’s Content Management maturity and define a future state for the retailer to work towards. EK also utilized its thorough understanding of the client’s culture and processes to produce a Content Management Strategy and Roadmap for implementation using an iterative, Agile approach, and leveraged in-house technical expertise to recommend a unique set of technological solutions aimed at alleviating the inefficiencies the client was experiencing. 

The EK team was uniquely positioned to deliver expertise in learning solutions because of our extensive experience delivering KM training sessions, workshops, and materials to a variety of clients as well as our in-house team of instructional designers and learning technology experts. We have conducted dozens of similar efforts with organizations like this one, and the EK team was equipped to deliver both hands-on training and in-depth technical support. This enabled us to holistically understand this organization’s needs and develop a strategy to help the learning team find the learning content and training materials they needed to support the organization’s employees. The EK team also demonstrated effective knowledge transfer techniques that the learning team could then utilize within their own training efforts. 

EK is also skilled in bridging the gaps between strategy, design, and implementation, as this effort fused personal interaction with stakeholders to develop a content management strategy with targeted, technical recommendations to plan and implement a KM Platform design. Rather than evaluating just the current state of the organization and developing a strategy to address current challenges, the EK team worked with stakeholders to determine the organization’s long-term goals and recommended various technologies that would help the organization update and maintain its learning content in the future.   

The Results

The retailer and EK’s long-standing partnership allowed them to successfully design, develop, and deploy three major releases for the digital library into the retailer’s production environment, resulting in increased time savings and reduced costs related to developing learning content, as well as a workforce with the necessary skills and expertise to do their jobs effectively and adapt to a rapidly changing environment. The retailer was able to gain an improved visibility into each associate’s capabilities and an enhanced ability to identify gaps in their learning content, resulting in more targeted learning experiences to upskill employees and guide their professional development. Additionally, the renewed consistency, reuse, and findability of learning materials allowed the retailer to mitigate any repercussions associated with on-site store safety, diversity and inclusion, and employee and customer health and wellbeing.

The post Content Management Strategy for an International Retailer appeared first on Enterprise Knowledge.

The Solution

EK performed initial user and system research and analysis to identify issues and recommend solutions to improve overall UX. As part of this research, EK facilitated cross-departmental focus groups and workshops with stakeholders and SMEs, in addition to conducting a current and target state analysis. During these activities, EK identified strengths and challenges in multiple aspects of the content lifecycle, from authoring and publishing to end-user content engagement. The challenges identified in the analysis provided an opportunity to identify and prioritize relevant use cases, which helped shape the Agile product roadmap and EK’s tool recommendations. Additionally, the analysis enabled EK to identify user goals and evaluation criteria that could be measured to test solution effectiveness. The EK team also collaborated with taxonomy SMEs to review and improve the existing content metadata, providing the foundations for more granular content tagging. EK then developed an Agile product roadmap that incorporated our UX and system recommendations with iterative milestones and collaborated with the client company on implementing the multi-workstream roadmap to ensure the client company met its goals and improved solution effectiveness.

EK’s user and system research found a cycle of challenges that reduced user confidence in the client’s documentation hub.

The EK Difference

The EK team leveraged our experience with taxonomy design, ontology design, UX best practices, and enterprise search to design an Agile roadmap to achieve expanded search capabilities, governance workflows, and more personalized content experiences. Our certified taxonomists and ontologists collaborated with client company SMEs to capture and translate existing metadata and authoring processes into an expanded taxonomy that the CCMS could leverage for granular content tagging. EK’s expert taxonomy and ontology designers discerned metadata pain points to design and deliver data models that would support the client company’s current and future advanced user-driven use cases. EK also leveraged our knowledge graph experience to implement and query the data models created by the ontology designers to support the prioritized use cases surfaced from our initial research and analysis. The EK team leveraged our advanced content management, search, and knowledge management solution architecture experience to design a new system architecture that enables dynamic content assembly, improves search experience, provides personalized content to system users, and decreases manual authoring time spent creating the content.

The Results

EK delivered a state-of-the-art solution architecture that enables increased granular tagging of componentized content for improved content and metadata management, content reuse across multiple end-user content experiences, and a streamlined content authoring process. The focus groups that EK conducted enabled the EK team to include and inform multiple departments across the organization, facilitating future cross-department collaboration. After applying the content changes, EK worked with the client to reevaluate user feedback on the site and found that

• Users were more satisfied with the content experience,
• Users were much more accurate with their answers, and
• Users were able to find answers in almost half the time.

The bench-marked structured Agile roadmap will enable the team to socialize the architecture and governance changes within the organization, communicating and promoting momentum and buy-in for the architecture and governance implementation.

The post User-Centric Content Engineering to Improve Customer Experience appeared first on Enterprise Knowledge.