1 Pantnagar

Margherita Sini, FAO 1 / 33

http://www.agropedia.net/

Knowledge Management in Agropedia Indica

Pantnagar Workshop

Margherita Sini (FAO)

31 July ‘08 – 2 August ‘08



Outline• Knowledge Management & Knowledge Modeling

• Knowledge Maps

• Representation languages

• Metadata

• AOS

• Agropedia Indica

• What’s next

• Take home messages



Before we start... (1/3)• Data: numbers, words, images symbols as

measurements or observations of a set of variables.• Information: data that are processed to be useful.

Contextualized data. Information includes human participation in the organization of raw data.

• Knowledge: (Oxford Dictionary) “expertise, and skills acquired by a person through experience or education”. Involve expressing, sharing, processing. Intuitions! Confident understanding of a subject with the ability to use it for a specific purpose if appropriate.



INFORMATIONDATA

Before we start... (2/3)

105.7

white Variety Color Size of grain

Botan Rice White 2.5mm length

Jasmine Rice

Brown Rice 6mm length

KNOWLEDGEIf I want to cook an Idli, I need to use a white Short-Grain rice such as Rambhog Rice.



Before we start... (3/3)• Knowledge

– Explicit knowledge: Explicit knowledge is knowledge that has been or can be articulated, codified, and stored in certain media (@Wikipedia)

– Tacit knowledge: resides in one’s mind!

• The AAA paradigm– Anybody and say Anything about Any topic.



Knowledge Management• Create, capture, analyse, apply, and reuse

knowledge;

• The process responsible for gathering, analysing, storing and sharing knowledge and information;

• It involves the design, review and implementation of both social and technological processes;

• Making it available to others;

K from Peoples!K from Peoples!

K for Computers!K for Computers!



Knowledge Modeling• Create knowledge models

is white



Some definitions (1/3)• Concepts / Classes: idea; thought;

• Individuals / Instances: objects of some type;

• Relations / Relationships / Properties / Links: ways that classes and objects can be related to one another;

• Attributes: properties, features, characteristics, or parameters that objects (classes or instances) can have;



Some definitions (2/3)

Concept

Instance

Rambhog Rice

Link / Relationship

Rambhog Rice is a type of Rice

Attributes

• color• size• trade name• hasDaysOfApplicationAfterSowing• hasDaysOfApplicationBeforeSowing



Some definitions (3/3)• Relationships types:

– linking concepts:• Hierarchical: subClassOf (are)

• Associative: objectProperty

– linking concepts to instances:• Is a type of (is a)

– linking concept to values:• dataTypeProperty

Rambhog Rice

Rice

is a (type of)

white

Rice

hasColor (dataTypeProperty)



Thesaurus and other KOS• Knowledge Organization Systems

– Classification schemes– Subject lists– Gazetteers– Glossaries– Thesauri

• Thesaurus: is a structured controlled vocabulary

• Term based

• Maybe multilingual



Knowledge Maps / Concept Maps• Different types

• Should address a specific problem

• In one or multiple languages



Taxonomy Map (are)



Partitivity Map (hasPart or isPartOf )



Attribute Map (hasAttribute or hasValue)



Process Map (usesProcess)



Concept Map



Concept Map



Topic Map• topics - representing any concept (e.g. people,

countries, organizations, software modules, individual files, events)

• associations - which represent the relationships between topics

• occurrences - which represent relationships between topics and information resources relevant to them



Ontologies• More rich KM

• Rules, axioms, ...

• Ontology editors: Protégé, NeOn Toolkit, Swoop



Representation languages• Technologies for Knowledge Management

– machine interpretability (processed by applications)– standardized– bases of semantic web

• Types– RDF and RDFS– OWL: add formal semantics – Topic Map: ISO standard (XML)



Metadata• When you describe a given

object (a book, a person, a product, etc.) with some information, you are actually using metadata: any type of description of an object or resource can be considered metadata.

• A set of elements used to describe an object is called the metadata element set.



Knowledge Modeling in Agriculture



Knowledge Modeling in Agriculture• AOS

• AGROVOC

• AGROVOC Concept Server

• Agropedia KMs

• Agropedia Indica



AOS



AGROVOC Thesaurus



AGROVOC Concept Server WB



Agropedia KMs (1/2)

CMap Editor.

Generic model(one only)

Specific models



Agropedia KMs (2/2)



Agropedia Indica

this is a documentabout rice and its

pests.....

Once the rice ap-pear

in the world .....

Mad Cow Disea-se is the commonly

used name for Bovine

Spongiform Encephalopathy

(BSE) ....

results.....



What’s next• Now it’s up to you...:

– Build more KMs!– Add content! (indexing)

• Agropedia Team:– Translate KMs in Hindi, Telegu, and others– Complete the infrastructure– Enrich services



The original problem...

KNOWLEDGEIf I want to cook an Idli, I need to use a white Short-Grain rice such as Rambhog Rice.

color

rice

recipesize

usedToCook

hasColor

hasSize Jasmine

white brown

Idli

6mm 2.5mm

hasInstance

usedToCook

hasSize

Rambhog

hasColor



Take home messages• Knowledge Maps to express your knowledge• Concepts, Instances, Relationships, Attributes• Relationships: hierarchical, associative

(objectProperties), for values (dataTypeProperty)• Ontology languages for computer consumption• Metadata to describe resources• AOS as pool of services• Agropedia Indica to publish and share your

knowledge and resources



References• KM: http://www.epistemics.co.uk/Notes/90-0-0.htm

• CMap:http://cmap.ihmc.us/Publications/ResearchPapers/TheoryCmaps/TheoryUnderlyingConceptMaps.htm

• RDF / RDFS: http://www.w3.org/TR/rdf-schema/

• OWL: http://www.w3.org/TR/owl-features/

• Metadata:ftp://

ftp.fao.org/gi/gil/gilws/aims/references/flyers/metadata_en.pdf

• AGROVOC and AOS: http://www.fao.org/agrovoc/

• AGROPEDIA: http://www.agropedia.net



Thanks!

[email protected]

Education

1 Pantnagar