Course Content: This CrashCourse is an introduction to semantic data using Python. It covers the following topics: We learn to work with RDF graphs using rdflib We explore the owlready package and OWL ontologies We look into json-ld serialization of RDF/OWL data We try data validation using pySHACL We use throughout a realistic data set based on the Credit Ratings Ontology Who Is This Course For: The course is useful to:
Making Open Risk Data easier: In an earlier blog post we discussed the promise of Open Risk Data and how the widespread availability of good information that is relevant for risk management can substantially help mitigate diverse risks. The list of Open Risk Data providers, particularly from public sector, keeps increasing and we are aiming to document all available datasets in the dedicated page of the Open Risk Manual.
The challenge with historical credit data: Historical credit data are vital for a host of credit portfolio management activities: Starting with assessment of the performance of different types of credits and all the way to the construction of sophisticated credit risk models. Such is the importance of data inputs that for risk models impacting significant decision making / external reporting there are even prescribed minimum requirements for the type and quality of necessary historical credit data.
StatsNews: Aggregating Economic Open Data news: StatsNews Version 1.3 of the RegNews Aggregator includes a separate stream of economic opendata news releases. Regnews is a web app developed by Open Risk to assist with keeping abreast with diverse financial regulatory news releases and publications. The app data are directly derived from the published regulatory RSS sheets (NB some are not conforming to RSS standards). If in doubt please refer to the original feeds (links provided).
From Big Data, to Linked Data and Linked Models: The big data problem: As certainly as the sun will set today, the big data explosion will lead to a big clean-up mess How do we know? It is simply a case of history repeating. We only have to study the still smouldering last chapter of banking industry history. Currently banks are portrayed as something akin to the village idiot as far as technology adoption is concerned (and there is certainly a nugget of truth to this).
What Inka quipus teach us about data management: Chances are that your knowledge of ancient Peruvian culture is a bit rusty. Maybe you have some vague high-school memories of an extensive but backward empire that was conquered and then asset-stripped by a handful of Spanish conquistadores. Or maybe your best preserved memory is the excitement of reading von Daniken’s speculations that the Nazca lines are extraterrestrial spaceports. But unless you happened at some point later in life to hear about the work of Prof.
Open Source Risk Data with MongoDB and Python: Open source software is all the rage those days in IT and the concept is making rapid inroads in all parts of the enterprise. An earlier comprehensive survey by Gartner, Inc. found that by 2011 more than half of organizations surveyed had adopted open-source software (OSS) solutions as part of their IT strategy. This percentage may have currently exceeded the 75% mark according to open source advisory firms.