Knowledge Base

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The Big Policy Canvas Knowledge Base is a state-of-the-art, online and dynamic repository that functions as an accumulator uniting all the knowledge produced during the project. It is structured along the three dimensions of needs, trends and assets and furthermore offers a mapping among them by defining how they are interconnected and how they influence each other.

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Weka, an open source software, is a collection of machine learning algorithms for data mining tasks. The algorithms can either be applied directly to a data set or called from the user's own JAVA code (as Weka itself has been fully implemented in the JAVA programming language). Weka features include machine learning, data mining, pre-processing, classification, regression, clustering, association rules, attribute selection, experiments, workflow and visualisation

In: Assets

The OpenText Sentiment Analysis module is a specialised classification engine used to identify and evaluate subjective patterns and expressions of sentiment within textual content. The analysis is performed at the topic, sentence, and document level and is configured to recognise whether portions of text are factual or subjective and, in the latter case, if the opinion expressed within these pieces of content are positive, negative, mixed, or neutral

In: Assets

Trackur’s automated sentiment analysis looks at the specific keyword one is monitoring and then determines if the sentiment towards that keyword is positive, negative or neutral with the document. That’s weighted the most in Trackur algorithm. It can be used to monitor all social media and mainstream news, to gain executive insights through trends, keyword discovery, automated sentiment analysis and influence scoring

In: Assets

Nowcasting is a forecasting methodology that is becoming increasingly popular in economics. The use case considers the potential use of Νowcasting in the context of economic policy setting and sets the potential value of an extended use of Νowcasting against different contexts.

In: Assets

This use case covers the methods that can assist policymakers throughout all stages of the policy cycle. It explains the sources for these data and how the outputs can be used to gain. understanding of stakeholders’ and citizen’s opinions on policies and strategies

In: Assets

The Smart Fire Department could be one aspect of a Smart Government scenario. Intelligently networked objects such as smoke detectors, smartphones, surveillance cameras and drones can support the work of the fire department thus leading to tracking behaviour, enhanced situational awareness, sensor-driven decision analytics, process optimisation, optimised resource consumption, complex autonomous systems.

In: Assets

Sensors perfect the transport infrastructures by reporting automatically about its utilisation and current condition. Sensor-generated information about the stress on roads, tracks, canals, bridges and tunnels helps civil engineering authorities to better estimate the condition of the infrastructure. They recognise and repair damages in the transport infrastructure in order to ensure an optimal traffic flow. This is supplemented by indications from citizens via apps.

In: Assets

The aim of the project is to construct a computer-based simulation model as a decision-support tool for policy-making in the early life course. This entails building a model with micro-level data derived from existing longitudinal studies to quantify, for policy purposes, the underlying drivers and determinants of progress in the early life course.

In: Assets

Expressing and visualising opinions on policies.

In: Assets

Information to the citizens and companies of the State of Bavaria in Germany in the domain of energy sources, including renewable energy.

In: Assets

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All the data are licensed as Creative Common CC-BY 4.0.