How do we describe something n What something

How do we describe something? n What something is about? – What the content of an object is “about”? n Different methods (Wilson, 1968) – counting terms (objective method) – complete description/summarization – unifying thought(s) – What stands out (main points) n Challenges – Non-text 1

Languages for aboutness n Indexing languages: – Terminological tools • Thesauri (CV – controlled vocabulary) • Subject headings lists (CV) • Authority files for named entities (people, places, structures, organizations) – Classification – Keyword lists – Natural language systems (broad interpretation) 2

Aboutness: How to do it! n Read the document [Intellectual reading] – look for key features – many indexers mark up the items – rarely have time to read the whole document n n Determine aboutness [Conceptual analysis] Translate aboutness into the vocabulary or scheme you are using – In general: Subject headings: 1 -3 headings – Descriptors, 5 -8 descriptors – Classification: 1 notation (should it only be one!? ). 3

Features of indexing languages: n With the exception of a few general domain tools, they are generally domain specific. – Me. SH – NASA Thesaurus – Astronomy Thesaurus – ERIC thesaurus http: //www. darmstadt. gmd. de/~lutes/thesoecd. html n Concepts (or concept representations) are arranged in a discernable order 4

Language schema designs n Classified--grouping – Hierarchies and facets Me. SH Browser http: //www. nlm. nih. gov/mesh/MBrowser. html Art and Architecture (Getty AAT) http: //www. getty. edu/research/conducting_research/vocabularies/aat/ n Alphabetical -- horizontal – Verbal/Alphabetical (ordering/filing challenges) 5

Controlled Vocabulary n n n Why do we have a controlled vocabulary? Three of you independently identify a new human gene, and each separately name it different things. How do we handle references/resolving/utilizing this concept which has different names. Let alone, across languages? ! 6

Controlled Vocabulary n A list or a database of subject terms in which each concept has a preferred terms or phrase that will be used to represent it in the retrieval tool; the terms not used have references (syndetic structure), and often scope notes. Their can be aliases for preferred terms (so the all three of your gene names get recorded and are matchable to the preferred term). 7

Example n n For gene names, there is an authority, HUGO Gene Nomenclature Committee that designates an official curated name for gene. During the research process however, there may have been multiple initial names. 8

More Examples n n Most processs however, do NOT have standardized naming. For instance genetic conditions are not named in one standard way. Doctors treating patients often propose the first name, but often expert working groups later revise to more appropriate name. 9

Cont’d n n n The basic genetic or biochemical defect that causes the condition (for example, alpha-1 antitrypsin deficiency); One or more major signs or symptoms of the disorder (for example, hypermanganesemia with dystonia, polycythemia, and cirrhosis); The parts of the body affected by the condition (for example, craniofacial-deafness-hand syndrome); The name of a physician or researcher, often the first person to describe the disorder (for example, Marfan syndrome, which was named after Dr. Antoine Bernard-Jean Marfan); A geographic area (for example, familial Mediterranean fever, which occurs mainly in populations bordering the Mediterranean Sea); or The name of a patient or family with the condition (for example, amyotrophic lateral sclerosis, which is also called Lou Gehrig disease after the famous baseball player who had the condition). 10

Thesaurus (structured thesaurus) n n Lexical semantic relationships Composed of indexing terms/descriptors Descriptors = representations of concepts Concepts = Units of meaning (Svenonius) 11

Thesaurus n n n Preferred terms Non-preferred terms Semantic relations between terms How to apply terms (guidelines, rules) Scope notes Adding terms (How to produce terms that are not listed explicitly in thesaurus) 12

Preferred Terms n Control form of the term • Spelling, grammatical form • Theatre / Theater • MLA / Modern language association n Choose preferred term between synonyms • Brain cancer or Brain Neoplasms? 13

Common thesaural identifiers n SN Scope Note – Instruction, e. g. don’t invert phrases n USE Use (another term in preference to this one) n n UF Used For BT Broader Term NT Narrower Term RT Related Term 14

Semantic Relationships n n n Hierarchy Equivalence Association 15

Hierarchies of Meaning ‘Beer Glass’ ‘White wine glass’ ‘Glass’ ‘Wine Glass’ ‘Red wine glass’ From: Controlled Vocabularies/ Paul Miller Interoperability Focus UKOLN 16

Hierarchy n n Level of generality – both preferred terms BT (broader term) – Robins BT Birds n NT (narrower term) – Birds NT Robins – Inheritance, very specific rules 17

Equivalence n n n When two or more terms represent the same concept One is the preferred term (descriptor), where all the information is collected The other is the non-preferred and helps the user to find the appropriate term 18

Equivalence n Non-preferred term USE Preferred term – Nuclear Power USE Nuclear Energy – Periodicals USE Serials n Preferred term UF (used for) Non-preferred term – Nuclear Energy UF Nuclear Power – Serials UF Periodicals 19

Association n n One preferred term is related to another preferred term Non-hierarchical “See also” function In any large thesaurus, a significant umber of terms will mean similar things or cover related areas, without necessarily being synonyms or fitting into a defined hierarchy 20

Association n Related Terms (RT) can be used to show these links within thesaurus – Bed RT Bedding – Paint Brushes RT Painting – Vandalism RT Hostility – Programming RT Software 21