Puffin Semantics aims to provide high quality, accessible data management tooling that supports making data Findable, Available, Interoperable and Reusable: FAIR. Puffin Semantics started out of a frustration with the quality of tooling that is aimed at facilitating conformity to information standards, be it internal to an organization or international.

We started in the utility sector, a domain rife with information standards, like the W3 recommendations in the linked data space or utility specific standards like IEC-CIM. However, in practice, those data models do not get used, because typically, the knowledge required to properly implement them correctly in different technologies, is rare to come by. So instead of reusing standardized data definitions, each data engineer, business intelligence analyst or data scientist comes up with their own definitions. This typically results in software that does not integrate: that doesn’t speak each others language. Whereas Newton could ‘stand on the shoulders of giants’ most of our data scientist have to reinvent the wheel for every new application.

We believe data is worth nothing if it’s meaning isn’t clear to those who need to work with it, whether it is developers, business analysts or domain experts. That is why we put semantics front and center in the products we make.

Recent Posts

Acting Locally Introduction

In the universe of agile organizations and decentralized governance, those who built and maintain the individual parts of our IT landscape, have the most influence on how these parts are realized, and thus how they will interact with other parts. This is closely related to the concept of do-ocracy where those who do the work have or get the mandate make the decisions. Whether an organization explicitly adopts do-ocracy or not, more often than not it effectively it is the case: it is the best model to describe what happens or gets done.
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Identity and Persistence

In this part we’ll have a closer look at the identity of the things we keep data of. One could argue that this is mostly a ‘pattern of miscommunication’ however, this one requires a little more background to understand so we treat it separately. The question about identity is about wondering about what one is thing and it being the same. This becomes relevant when dealing with aboutness and master data management: when we are wondering whether we have two records about the same thing in multiple information systems.
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Two approaches to modelling meaning

In this piece I want to introduce two approaches to model meaning that are relevant to data architecture. They evolve around the Triangle of Reference that was introduced in a ‘The Meaning of Meaning’ by Ogden and Richards in 1923. In a nutshell the, the triangle relates the thoughts or concepts we have (top of the triangle) to the things in the worlds that we have thoughts about (the Referents) and the symbols we use to symbolize our thoughts (like words, pictograms, data etcetera).
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What is information

Before we talk about data management, and how people and machines interact with data, it is important to take a moment to explore why we have data in the first place. And for that we need to take a step back and explore the nature of information. This will allow us to better understand the strengths and limitations of data and also put its expressiveness in context. I’d like to make an important scope not here.
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Patterns of Miscommunication and Misrepresentation

How do we know what we know in data modelling

How to help us render IEC-CIM in your (native) language

Welcome

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