Enterprise Sustainability & ESG Frameworks: 
Why Knowledge Graphs are Key

Enterprise Sustainability & ESG Frameworks: Why Knowledge Graphs are Key

We asked experts how knowledge graphs can effectively address issues with Sustainability and Environmental Social Governance (ESG) frameworks. Here’s why knowledge graphs will be essential for the success of the enterprise in the near future.

#ESG #Sustainability #KnowledgeGraphs

Sustainability and ESG Frameworks for Enterprises

Sustainability is a growing focus for many enterprises today. With digital and socio-political transformations underway, organisations are considering how to align with frameworks that promote a circular economy and foster sustainable processes. At the same time, more and more investments are being put into green projects that can make an impact on a societal level. But measuring this impact is where things get tricky.

ESG aims to offer a quantifiable sustainability assessment that allows companies to measure, disclose and manage the impacts they create against verified standards. This should allow for the effective and transparent communication of their contributions. 

Tassilo Pellegrini is the Head of Research Development at the University of Applied Sciences in St. Pölten. He mentions that ESG still remains a “tough nut to crack” because there are so many contexts involved. It is comparably easy to measure environmental impacts of economic behaviour such as carbon footprint but measuring the impact in terms of social and corporate governance becomes quite challenging.

Neither ESG nor Sustainability are well defined concepts and they take many different and sometimes competing factors into account. This is because each is highly context dependent. Complicating things further, every enterprise has a different culture and has a different legacy. 

This leaves ESG and Sustainability frameworks a “fuzzy domain in need of structure”.


No alt text provided for this image


Where Knowledge Graphs Come In

Knowledge graphs can play a pivotal role here. 

Pellegrini explains that “ultimately these frameworks are based on contextual definitions. We then build systems on top of these definitions. Knowledge Graphs and semantic technologies enable the disambiguation of texts and provide context.” From there it is possible to build systems on top of these contextualised definitions, paving the way for clarity. 

Knowledge graphs are true in any domain and applying them wisely can solve the central issues of ESG. Victor de Boer, Associate Professor of User-Centric Data Science at Vrije Universiteit Amsterdam, explains that “put to work in a global context, knowledge graphs can offer interoperability to solve some of our big issues, or at least provide solutions to where solutions need to be directed”. Data integration presents a more holistic picture of all things that might impact final decisions.

In this way, knowledge graphs help to bring knowledge into any organisation in a way that allows them to effectively undergo transformation towards success. Knowledge graphs allow stakeholders to collaborate with each other more effectively through the ways they connect pieces of complex information together.


No alt text provided for this image

Knowledge Graphs are Crucial for the Success of the Enterprise

Here are 3 ways knowledge graphs will be key to the sustainability efforts of the enterprise: 

1. Simplifying the process of information gathering and compilation

Knowledge graphs can significantly reduce the costs of compiling and gathering necessary information for internal and external use. This helps companies keep track of their sustainability efforts and uncover areas for growth. Bruno Wildhaber is a Managing Partner at the Swiss Information Governance Competence Centre, whose research on Rot Data exemplifies this.

Example - Rot Data:

Wildhaber’s research shows that most organizations keep about 60-80% of data they don’t need: This is referred to as Rot Data. While the extent of data energy consumption is easily overlooked, it poses a big sustainability issue for many data based companies. In this case, knowledge graphs offer an effective strategy for approaching metadata and sorting between relevant and irrelevant data. Getting rid of as much redundant data as possible enables companies to reduce their carbon footprint dramatically.


2. Enabling interoperability

Knowledge graphs can connect different parts of the enterprise with external data to get the most rich information possible and make decisions about sustainability. Data integration through a knowledge graph provides an overview of all things that might impact final decisions.

Example - Linking to existing datasets:

De Boer illustrates this interoperability with an example: “If you want to assess a fire hazard, there’s so much data out there that is sometimes not intended to be used for measuring fire hazards but that when linked to existing datasets that are designed for that purpose can actually allow you derive very valuable new facts that might help your business in becoming more sustainable because you can identify where the sustainability risks are."


3. Providing information in the correct form to the correct people

Companies not only collect information for internal use but for external stakeholders with differing levels of knowledge and expertise. Knowledge graphs allow the presentation of information in the correct form allowing it to apply to sustainability efforts. Lyndon Nixon, Assistant Professor of Applied Data Science at Modul University, spoke about an ongoing project which exemplifies this.

Example - SDG-HUB:

SDG-HUB aims to build a knowledge repository to address socio-ecological challenges by analysing climate change and sustainable development communication processes in Austria. Nixon explains that “fundamentally, we are dealing with unstructured data. Knowledge graphs give the opportunity to disambiguate concepts & references that exist within the context.” The SDG-HUB “AI methodology will encompass all the steps of the process from data collection to the development and training of associated neural models, and their outputs.” (Modul). This makes the gathered knowledge available to various audiences. 


No alt text provided for this image

Outlook

A successful shift towards sustainability requires us to ask the right questions, determine suitable definitions and build systems that communicate information in a proper way. ESG offers an effective solution to implementing measures in a defined way. 

While this process is still fuzzy, Knowledge Graphs and Semantic Technology can be leveraged in powerful ways to achieve optimal success.



Thank you to the interviewed experts for their valuable insights!

Victor de Boer, Associate Professor of User-Centric Data Science at Vrije Universiteit Amsterdam

Lyndon Nixon, Assistant Professor of Applied Data Science at Modul University

Tassilo Pellegrini, Head of Research Development at the University of Applied Sciences in St. Pölten

Bruno Wildhaber, Managing Partner at the Swiss Information Governance Competence Centre


Interviewed and written by Yelvilaa Bodomo, Performance and Social Media Marketing Manager at Semantic Web Company (SWC)

To view or add a comment, sign in

Explore topics