The Academy offers a unique range of online eLearning resources spanning and integrating Data Science, Sustainability and Risk Management
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This course is a CrashProgram (short course) introducing the GeoJSON specification for the encoding of geospatial features. The course is at an introductory technical level. It requires some familiarity with data specifications such as JSON and basic knowledge of Python. The update expanded several sections, added examples with geopandas and fixed some broken links.
Enjoy!
In this course we want to study an identification framework for Open Source Business Model Risks.
The scope of the analysis covers both for-profit and non-profit projects.
The structure of the course is as follows:
The result is a FOSS Risk Canvas, a concise tool that helps with a comprehensive self-assessment of business model risks that can hinder FOSS projects reach financial sustainability.
In a blog post we discuss variability drivers of reported financed emissions of portfolios. Using a conceptual deed-dive into calculation procedures we isolate the fundamental factors and how they can be explained using waterfall diagrams.
The Open Risk Manual was developed for a long time, with out-most conviction, as an open and free resource. An open online repository of information about Risk Management in all its forms, that was the core idea, part of our vision for widely available open source tools for risk management and sustainable finance.
Alas, as of late the open part of the mission has become very problematic. A large number of AI bots are now roaming the internet and hitting servers (like the one on which the Manual runs) indiscriminately, without regard to breaking it. It has become very difficult to defend against such (effectively) DDoS attacks. Filtering the thousands of hostile bot requests using random address from human users is not what we want to spend our resources on. After trying all possible measures, it became clear that nothing will do. We need to ask users of the Manual to login before browsing and/or searching.
The login mechanism is the same as the Academy. Users of the Academy can already use the Manual using their existing credentials. Other users will need to setup and have an account approved at the Academy.
Our objective in this post is to express standard financial statements concisely using symbolic mathematical notation that substantially captures their numerical information content and the constraints being satisfied.
We use the incidence matrix of an accounting graph to describe an abstract underlying accounting system that follows double-entry bookkeeping principles and we derive from it the classification, aggregation and stock-flow machinery that reproduces the well-known balance sheet, income and cash flow statements.
In a new paper we develop the concept of an accounting graph as an intuitive and flexible tool that can faithfully represent widely used accounting concepts.
More specifically, a weighted directed multigraph representation is applied to model standard double-entry bookkeeping (DEB) of individual accounting entities but extended to also provide a consistent accounting graph for larger economic networks that feature multiple transacting entities (so-called quadruple-entry accounting). We illustrate the concepts with stylized accounting examples. Such accounting graphs are promising both as educational tools and towards the application of computational tools on accounting data.