Global Foresight for Environment Protection

Global foresight for environment protection focuses on geopolitical and business aspects of ESG, including climate  action, responsible production and consumption patterns, clean water and sanitation, and clean and affordable energy. The foresight comprehends insights on future trends and scenarios to guide decision-making in developing better  policies. A contextual graph built through data from the Common Crawl, Linked Open Data Cloud, and global media news provides unique insights into mass media’s convergence of the three societal systems (economy, politics, science).

The Global Foresight for Environment Protection Use Case in detail

Global foresight for environmental protection focuses on the geopolitical and business aspects of ESG, which includes climate action, responsible production and consumption patterns, clean water, and affordable energy.

This approach involves analyzing news articles and extracting information about events happening in the world, particularly those concerning companies mentioned in the articles. With the help of Graph-Massivizer, past events will be used to compute potential future events to detect trends and anomalies.

Use case overview

The main objective of this use case is to identify individual relations related to global companies in online media mentions. These relations are related to various topics concerning environmental protection and business operations. Based on these extracted relations, predictions about potential future events can be made. These predictions will be based on identified generalized sequences of events.

Using Graph Massivizer, we can identify shared sequences of events across multiple companies and use those patterns to predict new events based on a sequence of recent events about a company. Besides predicting future events, the aim is also to identify specific trends and anomalies in the data by observing data in individual industries, sectors, and geographies.

The outcome of this project is the ability to identify common sub-graphs related to individual companies in large graphs of data. These patterns can be used to predict, as accurately as possible, likely future events.

This Use Case relies on cutting-edge technology to help organizations predict future events based on past data patterns. Our workflow is based on the initial provision of data as JSON objects, which are then converted to a graph structure using an established ontology. The Graph Scrutinizer is our main component for computing patterns and trends, and it operates on data imported into Graph Massivizer. By leveraging its powerful capabilities, the Graph Scrutinizer can predict potential future events for a new subgraph based on common patterns.  The Use Case relies primarily on Graph-Inceptor for ingesting new data and Graph-Scrutinizer for extracting common patterns and trends from the graph.

Expected Outcomes of the Use Case

The results of our use case are reported in the form of a list of potential events predicted for a given input sequence of past events. Each predicted event has an associated probability, giving a clear sense of the likelihood of it occurring based on the frequency of the pattern in past data.

Our prediction component is the perfect addition to your existing product, seamlessly integrating with it to offer you an additional service for an extra charge.

We are committed to offering this service to organizations in the geopolitical segment, hedge funds and investment companies, and general companies interested in monitoring their supply chain. As the primary stakeholders in this use case, analysts will benefit from our technology as it enables them to understand what is happening globally and the potential consequences of these events. By leveraging our cutting-edge tools and technology, you can be confident in your ability to predict future events and make informed decisions that will keep you ahead of the curve.

Detail of the User Interface