Knowledge Base

About this tool

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.

Knowledge base data visualization

knowledge base data graph

Explore the knowledge base data graph.

Explore


Improve the Knowledge Base

Are you aware of an asset that can help enrich the BPC KB? Share it with us and be named contributors to our work.

Fill in the questionnaire


Displaying 21 - 25 of 25

Solver specialises in providing world-class financial reporting, budgeting and analysis with push-button access to all data sources that drive company-wide profitability. Solver provides BI360, a Corporate Performance Management (CPM) software suite for companies of all sizes, which is available for cloud and on-premise deployment, focusing on four key analytics areas.

In: Assets

DataMelt or DMelt is a software for numeric computation, statistics, analysis of large data volumes ("big data") and scientific visualisation. The program can serve many areas, such as natural sciences, engineering, modelling and analysis of financial markets and (as it is a computational platform) it can be used with different programming languages on different operating systems

In: Assets

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

Open data - Download the Knowledge base

You are free to download the data of this Knowledge base.

To do this you must be an authenticated user: log in or sign in now.

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