Glossary¶
DRAFT: Work in progress¶
This material is a work in progress, at "rough draft" stage.
– A –¶
abstraction layer¶
A technology implementing a separation of concerns
a way of hiding the working details of a subsystem, allowing the separation of concerns to facilitate interoperability and platform independence
see: https://en.wikipedia.org/wiki/Abstraction_layer
Apache Spark¶
One of the most popular open source projects for "Big Data" infrastructure, based on [zahariacfss10]. Spark provides a classic example of applicative systems used for data analytics.
See: https://spark.apache.org/
applicative systems¶
– C –¶
cloud computing¶
see: https://derwen.ai/d/cloud_computing
computable content¶
– D –¶
data context¶
data engineering¶
data governance¶
see: https://derwen.ai/d/data_governance
data science¶
see: https://derwen.ai/d/data_science
data strategy¶
distributed systems¶
– G –¶
graph algorithms¶
graph database¶
graph data science¶
– K –¶
KG¶
abbr. knowledge graph
KGC¶
abbr. Knowledge Graph Conference
knowledge graph¶
One of the more concise, contemporary definitions is given in [hogan2020knowledge]:
We refer to a knowledge graph as a data graph potentially enhanced with representations of schema, identity, context, ontologies and/or rules.
see: https://derwen.ai/d/knowledge_graph
Knowledge Graph Conference¶
The annual Knowledge Graph Conference and its community https://www.knowledgegraph.tech/
knowledge graph embedding¶
– M –¶
machine learning¶
see: https://derwen.ai/d/machine_learning
– N –¶
natural language¶
see: https://derwen.ai/d/natural_language
– O –¶
OSFA¶
abbr. "One size fits all", a common antipattern in technology
a description for a product that would fit in all instances
see: https://en.wikipedia.org/wiki/One_size_fits_all
– P –¶
probabilistic graph inference¶
probabilistic soft logic¶
A computationally efficient form of statistical relational learning described in [bachbhg17]
We unite three approaches from the randomized algorithms, probabilistic graphical models, and fuzzy logic communities, showing that all three lead to the same inference objective.
property graph¶
– R –¶
RDF¶
abbr. Resource Description Framework https://www.w3.org/RDF/
a standard model for data interchange on the Web
reinforcement learning¶
see: https://derwen.ai/d/reinforcement_learning
– S –¶
semantic technologies¶
Semantic Web¶
A proposed evolution of the World Wide Web, discussed in retrospect by [shadbolt06semantic], and coordinated through the W3C. The intent was to move from documents for humans to read, to a Web that included data and information for computers to manipulate.
see: https://en.wikipedia.org/wiki/Semantic_Web https://www.w3.org/standards/semanticweb/
separation of concerns¶
statistical relational learning¶
see: https://www.cs.umd.edu/srl-book/
– W –¶
W3C¶
abbr. World Wide Web Consortium https://www.w3.org/
an international community where Member organizations, a full-time staff, and the public work together to develop Web standards