“Remember that every science is based upon an abstraction. An abstraction is taking a point of view or looking at things under a certain aspect or from a particular angle. All sciences are differentiated by their abstraction.” (Fulton Sheen) Graph and document databases (aka document stores), also demonstrate this principle. A few years, graph databases […]
Generally Accepted Data Modeling Principles
What can data modelers learn from accountants? Accounting is a solidly established practice that the world cannot live without. One of the established guidelines for accountants is called GAAP (Generally Accepted Accounting Principles in the US), and there are similar international setups. You might guess these standards are about rules, but actually, accounting is much […]
Rethinking Master Data Management
Click to learn more about author Jeff Kinard. Master Data Management (MDM) is seen as a necessary evil by many organizations. However, most haven’t found an effective method or service to handle it. In the case of asset-heavy industries, the strategies currently deployed are archaic, magnifying the problems. Many organizations overlook and underestimate MDM, and […]
Data Ontology is the Future, and I Can’t Wait
Click to learn more about author Mike Brody. When the inventor of the World Wide Web says a new technology is gonna be big, I’m inclined to listen. In this now decade-old TED Talk, W3C Director Sir Tim Berners-Lee makes a convincing case for the critical importance of what he calls “data linking,” a technology that […]
Solving Knowledge Graph Data Prep with Standards
Click to learn more about author Dr. Jans Aasman. There’s a general consensus throughout the data ecosystem that Data Preparation is the most substantial barrier to capitalizing on data-driven processes. Whether organizations are embarking on Data Science initiatives or simply feeding any assortment of enterprise applications, the cleansing, classifying, mapping, modeling, transforming, and integrating of data […]
Data Lakes: Cleaning Up Data’s Junk Drawer
Click to learn more about author Paul Brunet. We all have that place where we end up stashing those things we think we’ll need or want someday. Some of us throw the stuff in a junk drawer in the kitchen. Others squirrel it away to the attic or into a closet in the spare bedroom. […]
Taxonomy vs Ontology: Machine Learning Breakthroughs
The difference between Taxonomy vs Ontology is a topic that often perplexes even the most seasoned data professionals, Data Scientists, Data Analysts, and many a technology writer. Yet, taxonomies and ontologies form the underpinnings of how machines learn and understand, a group of technologies that are quickly improving in perception and cognition. Cognitive Computing technologies […]
What Is Ontology?
Ontology is often considered a subset of taxonomy. An ontology: Is a domain; contains more information about the behavior of entities and the relationships between them; includes formal names, definitions and attributes of entities; and, may be constructed using OWL, the Ontology Web Language from the W3C. Other Definitions of Ontology Include: “A data model […]
What Is Taxonomy?
Taxonomy represents the formal structure of classes or types of objects within a domain. It organizes knowledge by using a controlled vocabulary to make it easier to find related information. A taxonomy must: Follow a hierarchic format and provides names for each object in relation to other objects. May also capture the membership properties of […]
Introduction to: SKOS
SKOS, which stands for Simple Knowledge Organization System, is a W3C standard, based on other Semantic Web standards (RDF and OWL), that provides a way to represent controlled vocabularies, taxonomies and thesauri. Specifically, SKOS itselfis an OWL ontology and it can be written out in any RDF syntax. Before we dive into SKOS, what is […]