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Glossary

books by b a r z i n from the Noun Project

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-based 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.

see: https://psl.linqs.org/

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


Last update: 2021-04-17