Semantic Metadata

What is Metadata

Metadata is information about data
Metadata is typically
- Manually provided
- Often missing
Metadata can be automatically captured
- By a sensor or instrument
- By a workflow system

Data characteristics: Size, statistical properties
Descriptive metadata: Location, collection, frequency
Provenance metadata: What workflow was used, what its components were, what the input data was

A metadata vocabulary is the set of the terms used to describe metadata
A metadata standard is a vocabulary that is agreed upon by a community and are adopted for metadata
- Based on its broad applicability and how well it supports uses of the metadata

Metadata captures knowledge about objects in the domain of interest
It is important to learn computational concepts for knowledge representation
These representations are key to communicate important expertise to collaborating data scientists and computer scientists

Knowledge is a set of beliefs held by an agent that determine its behavior
Knowledge representation is a field of artificial intelligence devoted to developing and implementing computer languages to capture knowledge

- Note: Properties is about relationship

Knowledge systems use a knowledge base of beliefs to generate their behavior
Behavior changes when new beliefs are added
- If they exhibit wrong behaviors/answer, beliefs can be changed to fix them
They reason: use logical inference over their beliefs to answer queries/deduce new beliefs
- uses a logic system to reason over the beliefs/data in the knowledge base
Knowledge system uses knowledge base that contains the beliefs, and then uses a logic system (such as knowledge representation system, like a frame system) to reason over beliefs

Reasoning is done over symbols that make up the beliefs much like calculations are done over numbers
Reasoning uses a logic system to do inference: a system of general logic rules to deduce new beliefs from initial beliefs in a knowledge base
Natural deduction is an example of a logic system

Symbol are labels that can be used to refer to entities in the world
Several symbols may exists for the same object
A knowledge representation language specifies
- Symbols and a notation ofr how to combine the symbols to represent beliefs
A knowledge base is a set of beliefs and can be used by a knowledge system to generate its behavior

A knowledge representation system is a logic system that has three components:
- Knowledge representation language: what symbols can be used an how to combine them
- Logic rules: how can the system infer new beliefs given initial beliefs
- Reasoning algorithm: how teh system uses the language and the logic rules

A frame system is a kind of knowledge representation system for descriptive knowledge
Each class is represented as a frame that captures is main characteristics

An ontology contains descriptive knowledge about entities of interest in a domain
- A shared conceptualization of the world
An ontology is typically a collection of generic frames
Vs. a vocabulary, which is just a set of terms but not organizing them within a hierarchy
Ontology is a “generic frame only” knowledge representation system
Ontologies thus have the 3 components and not associated instances/data

A standard language for the web (like HTML), specifically for authoring ontologies
Knowledge representation language used to author ontologies - ‘generic frame only’ knowledge representation system - for the web
- Represents descriptive knowledge on the web
- Can result in a more elaborate version of a frame system
Provides for:
- Language
- Rules
- Reasoning algorithm

OWL as description logics:
- Knowledge representation language
- Descriptive knowledge
Description logics - language designed for knowledge representation and reasoning for descriptive knowledge