Multi-Model Search using Semantics and Optic API

Researchers have a large corpus of content at their fingertips. When searching, they expect underlying concepts, classifications, and occasional variations to be found. This is a natural way of thinking; as humans, we understand the world is governed by a complex set of relationships and concepts. Yet to computers, it is quite binary. The term or phrase is present in the record, or not.

So, how do we get our applications to recall information like us? This is actually a more complex problem to solve than it might appear on the surface. The MarkLogic Optic API makes your searches smarter by incorporating semantic information about the world around you.

As a developer, when we delve into a project, we usually look at the problem with a certain lens. We often have data in tabular form, unstructured text, and classification systems. Sometimes, we get blinded by looking at a single data structure to solve all our problems. This is due to the limitations of the underlying technology. But, this may not be the best, or most natural, approach for managing the data.

Large bodies of text can benefit from structure. It can be expressed as XML or JSON, which includes metadata and markup. Facts can be expressed in taxonomies and ontologies as semantic graphs of knowledge. When integrating with BI and analytic tools, data in tabular formats are needed. So where do we start? If we look at the market, we see multiple point solutions for managing the data in a more native form. With point solutions, complex architectures are used to compose queries and aggregate results.

In MarkLogic, you can manage your varying shapes of data within a single server and reduce architectural complexity. Even better, with the Optic API, you can query and join datasets of any shape and size in a single API. No need to manually stitch the results together.

Ready to see it in action? In the Search Multi-Model Data with Optic API tutorial, I walk you through how to set-up a MarkLogic Data Hub to ingest and harmonize data, then we use the Optic API to discover the valuable information.