QUERY LANGUAGES - A TAXONOMY Yannks Vassiliou ... - CiteSeerX

QUERY LANGUAGES

-

A TAXONOMY

Yannks V a s s i l i o u and Matthias J a r k e

Center f o r Research on Information Systems Computer A p p l i c a t i o n s and Information Systems Area Graduate School of Business AdministratTon New York U n i v e r s i t y

Workknq Paper Serjces CRIS #34 GBA #82-35

(CR)

T h i s p a p e r was o r i g i n a l l y p r e s e n t e d a t : NYU amposkum -

on User I n t e r f a c e s New York, NY, May, 1982

Center for Digital Economy Research Stem School of Business IVorking Paper IS-82-35

Page 3

1

.

INTRODUCTION A h y p o t h e t i c a l f u t u r i s t i c s c e n a r i o f o r querying a

database

begins w i t h a u s e r s i t t i n g on t h e couch, s i p p i n g some c o f f e e and l o o k i n g a t t h e fancy d i s p l a y of h e r personal computer it h e r t e l e v i s i o n s e t ?

-

understands h e r i n t e n t i o n s , t h e p e r s o n a l her

favorite

format.

To

computer

is

voice

in

presents

an

break t h e monotony, she

-

i s s u e s h e r next r e q u e s t p r a c t i c i n g h e r French simulated

company,

J u s t l i k e h e r b e s t f r i e n d who always

c a t e g o r i z e d by department.

in

is

She s c r a t c h e s her head and i n s t r u c t s t h e

p e r s o n a l computer t o d i s p l a y t h e monthly s a l e s f o r h e r

answer

or,

the

reply

by

t h e same language, a l i t t l e bad i n t h e

accent.

But l e t us d e a l with Architecture with

a

Machine

voice

Group

and

"Put-That-There".

the

This

reality at

gesture real

of

the

present.

MIT [ScHu 821 i s experimenting interactive scenario

system

called

c a l l s f o r t h e database pointing)

u s e r t o i s s u e h e r commands by voice and g e s t u r e ( e . g . and

The

by

positioning her eyes a t t h e d e s i r a b l e o b j e c t i n a large

screen.

The u s e r wears a headset microphone, has a watchband on

her

wrist

for

the

gesture

recognizer,

i s wired a s i f t o be

e l e c t r o c u t e d and s i t s i n a media room.

A t h i r d s c e n a r i o i s r e q u i r e d t o d e s c r i b e t h e most r e a l i s t i c

circumstances

for

i n t e r a c t i v e l y querying a d a t a b a s e .

The u s e r

s i t s i n f r o n t of h e r CRT t e r m i n a l , makes s u r e s h e h a s t h e description

of

the

database

-

right

which f i e l d appears where, what

r e l a t i o n s h i p s e x i s t between t h e d a t a

-

and

starts

typing

the


Page 2

ABSTRACT A taxonomy of database query languages i s p r e s e n t e d based on a n a n a l y s i s of e x i s t i n g languages and c u r r e n t t r e n d s i n r e s e a r c h and p r a c t i c e . The c a t e g o r i z a t i o n of query languages i s hierarchical. A t t h e senses l e v e l , languages a r e d i s t i n g u i s h e d At a a c c o r d i n g t o t h e c l u e s and senses employed by t h e u s e r . more detailed level, the methods l e v e l , languages a r e c a t e g o r i z e d according t o t h e b a s i c concepts, methodologies and conceptual u s e r models which a r e employed. In addition t o t h i s c a t e g o r i z a t i o n , t h e taxonomy i n c l u d e s schemata of e v a l u a t i o n c r i t e r i a t o be used i n language comparisons. Using t h e r e s u l t s of human f a c t o r s s t u d i e s , t h e e v a l u a t i o n schemata a r e a p p l i e d t o t y p i c a l u s e r p r o f i l e s t o d e r i v e u s a b i l i t y recommendations. The u s e r p r o f i l e s a r e p a r t of a comprehensive c l a s s i f i c a t i o n scheme of query language u s e r s a l s o developed i n t h i s paper.

We a r e g r a t e f u l t o our c o l l e a g u e Margrethe Olson f o r h e r comments and s u g g e s t i o n s on t h e f i r s t d r a f t . W e would a l s o l i k e t o thank Martha Hart Deese f o r doing a n e x c e l l e n t job t y p i n g t h e t a b l e s i n t h i s paper.


Page 4

Is i t FIND o r GET I have t o use h e r e , do

q u e r y on t h e keyboard.

I p u t t h e GROUP BY b e f o r e t h e WHERE?

"ILLEGAL

After

COMMAND".

Then a p p e a r s t h e

message:

two more t r f e s she g e t s t h e answer,

b u t i s t h i s what s h e wanted?

What a l l of t h e s e s c e n a r i o s have i n Ldentificatkon

of

our

hypothetical

i n f r e q u e n t u s e r with l i t t l e o r no novice

user

user

as

programming

a

i s

natural

a "novice"; knowledge.

an The

l i k e l y wants t o s t a y away from a p r o g r

most

language, pays l i t t l e a t t e n t f o n

little

common

to

precision

and

logic,

has

s e n s e of a l g o r i t h m i c t h i n k i n g , and e x p e c t s t h e system t o

respond t o h i s

or

her

personal

style.

Our

preference

for

f o c u s i n g on t h e novice u s e r f n our s c e n a r i o s s h o u l d n o t b e t a k e n a s an i n t e n t i o n t o i g n o r e a l l o t h e r t y p e s of u s e r s . should

be

Rather,

t a k e n a s a r e a l i z a t i o n t h a t t h e p o p u l a t i o n of novice

u s e r s i s i n c r e a s i n g a t l e a s t p r o p o r t i o n a l l y with t h e computer

and knformation systems.

equipment

t y p e s of system database

it

users

can

interacthn

benefit

languages

human f a c t o r s p r i n c i p l e s

of

a

if

the

takes

knto

language

growth

of

Regardless, o t h e r des2gn

of

thekr

conskderatkon t h e

system

designed

for

where

some

novices.

The t h r e e hypothesize

we

scenarios are

give

goLng,

an

what

indkcation

of

d k r e c t i o n we a r e t a k i n g , and

where we a r e today with d a t a b a s e q u e r y languages.

The number and v a r i e t y under

development

bas

of

query

languages

available

or

become s o confuskng t h a t a framework 2 s

needed f o r c l a s s i f y i n g and e v a l u a t k n g q u e r y languages

in

terms


Page 5

of t h e i r u s a b i l 2 t y by d i f f e r e n t t y p e of u s e r s .

3s

paper

to

establish

such

from it.

recolnmendatfons

a

Our g o a l i n t h i s

framework

and

to

I n t h i s r e s p e c t , our work goes beyond

p r e v i o u s surveys and c a t e g o r i z a t i o n s t h a t have appeared

[LOTS 811, EMcMc 8 2 1 ,

Our taxonomy i s observation

the

of

two

[S~RQ 771 ) .

a

two-level

language

engineering*

hierarchy

grounded

in

the

converging t r e n d s which seem t o govern t h e

r e c e n t development of query

necessary

in

I [BCS 81 1 , [LaPi 76,77,801 , [LeBl 791 , [LeSa 741 ,

literature

formal

derive

theory

languages;

and

the

one

other

orfginating

from

S e c t i o n 2 expands on t h k s 2dea

human

after

from

factors

giving

the

d e f i n i t i o n s and narrowing t h e scope of t h e p a p e r t o a

manageable t a s k .

In Section 3 ,

describing

the

senses

level,

languages

a r e c l a s s i f k e d by t h e s e n s e s employed f o r i n t e r a c t i o n

with

database.

the

reviewed

to

at

level.

this

Some

recent

experimental

systems

are

i l l u s t r a t e t h e t y p e of developments t o be expected These

convent&onal query

systems

language

are

contrasted

with

more

systems

2n

a uniform evaluatkon

S e c t i o n 4 d e s c r i b e s t h e low l e v e l

of

the

scheme.

methods l e v e l .

hierarchy,

the

Languages a r e c l a s s i f i e d by t h e methods of query

formulation.

Each

cost-benefit

scheme

method

is

evaluated

based

on

t h e e f f o r t f o r u s i n g t h e system

in

a

(qualitative)

( c o s t ) and t h e f u n c t k o n a l power of t h e language ( b e n e f i t ) .


Page 6

I n S e c t i o n 5, a language

users

is

evidence from human recommendations

unified

approach

for

developed.

The

results

experkments

factors

classifying

query

of S e c t i o n 4 and

are

used

to

derive

concerning t h e u s a b i l i t y of language methods by

S e c t i o n 6 o f f e r s o u r c o n c l u s i o n s and d i r e c t i o n s

u s e r type.

for

f u t u r e research.

2.

BASIC CONCEPTS AND METHODOLOGY

I n r e c e n t y e a r s , t h e f o c u s of computer systems has

shifted

from nuntber-crunching and mass d a t a p r o c e s s i n g t o t h e management of d a t a a s a s t r a t e g i c r e s o u r c e i n t h e management

systems

provide

o r g a n i z a t i o n , g i v e a v a r i e t y of

a

organization.

conskstent

users

Database

view

appropriate

and

of

the

secure

t o t h e d a t a , and o f f e r e f f i c i e n t f i l e management s u p p o r t

access

f o r a p p l i c a t f o n programs.

A

categorization

of

languages

d a t a b a s e i n t e r a c t i o n s i s p r e s e n t e d i n t h e appendix ( T a b l e 1 ) . c e n t r a l i n t e r a c t B o n mode of u s e r s

with

a

database

system

for A

is

through a query language.

A Query

Roughly,

IQL) cannot

be

defined

preciskon.

it i s a h i g h - l e v e l computer language f o r t h e r e t r f e v a l

of d a t a h e l d i n d a t a b a s e s and f i l e s [BCS 811. focus

with

In t h i s paper

we

on languages f o r q u e r y i n g d a t a b a s e s r a t h e r t h a n a r b i t r a r y

c o l l e c t i o n s of f i l e s .

A q u e r y language i s u s u a l l y assumed t o be

interactive,

and

on-line

ad-hoc { n o t p r e d e f i n e d ) .

able

to

support

q u e r i e s which a r e

I n t e r a c t i o n v i a a QL t e n d s

to

be

of


Page 7

low complexity and t h e displayed answer t e n d s t o be 1im2ted t o a I t i s o f t e n assumed t h a t t h e p r i n c i p a l u s e r s of

few l i n e s . are

the

ones'

kmportant

do

performance

contrasted languages

that

with are

usually

usage

usability,

are

tools

is

technical query

efficiency. lkmited

of

expert2se.

development

By

time

construction,

efficiency

in

The as

query

run

time.

t h o s e t h a t s e t pragmatic g o a l s kn terms of

QLs

all-purpose

have

factor

system

Successful and

not

QLs

rather

for

all

production of 10000 m a i l i n g

than

those

t y p e s of u s e r s . labels

in

clakm

that

to

be

For i n s t a n c e , t h e

special

formats

would

r a r e l y be attempted i n a QL.

The taxonomy i s based on our observation t h a t c u r r e n t query languages

have

developers,

developed

originating

from

from

two

the

sources. the

One

areas

of

group

of

programming

languages and database t h e o r y c o n c e n t r a t e s on t h e s y n t a c t i c form and semantic mean2ng of database formal, has

mathematically

moved

restricted

to

oriented

"Engl2sh-lfkes'

natural

interactions.

towards more " u s e r - f r i e n d l i n e s s s ' . developers

started

from

simple

function

The

languages overall

trend

The second group of

with

keys

or

computer

systems.

line-by-line

trend

with

toward

t h e database. more

finally has

been

language

Beginning

prompting,

complex systems i n v o l v e t h e use of menu s e l e c t i o n interaction

and

t h e ergonomic a n a l y s i s o f i n t e r a c t i o n

technology of novice u s e r s with

from

language concepts, t h i s group

keyword

languages.

Starting

or

more

graphical

These developments r e p r e s e n t a

"functionality"

while

remaining

novice-oriented.


Page 8

I n c o n v e n t i o n a l query languages ( " f i r s t these

two

areas

have

developed

fairly

generation

QLs"),

independently;

s e r v i n g t h e more, t h e o t h e r t h e l e s s s o p h i s t i c a t e d u s e r .

one Recent

developments,

however, l e a d t o an o v e r l a p of t h e usage a r e a f o r

b o t h language

groups.

approaches

to

The

is

challenge

functionally

powerful

r e l a t i v e l y unsophisticated users.

to

integrate

query

languages

both for

We c a l l t h e s e systems "second

generatkon QLsl'.

The upper l e v e l of o u r taxonomy e x p l o r e s i n more d e t a i l t h e differences called

between

senses

QLs.

level

is

interaction

first

and

because

second the

use

It i s

g e n e r a t i o n QLs. of

more

senses

in

one of t h e main advantages i n second g e n e r a t i o n

The lower l e v e l taxonomy f o c u s e s on t h e methods that -

have

been used i n e x i s t f n g , mostly f i r s t g e n e r a t i o n QLs.

Each strengths

of and

the

categories

weaknesses

p r o c e s s of choosing a evaluation

Finally,

which

both

taxonomy

First,

language.

are

established.

determined

t h e multi-dMensional

levels

have

must b e t r a d e d o f f d u r i n g t h e

query

parameters

t h e s e parameters a r e

on

for

the

Next,

each

fmportant

t h e v a l u e s of

language

category.

e v a l u a t i o n c a n be r e l a t e d t o t h e

u s e r and t a s k p r o f k l e of t h e a p p l i c a t i o n t o d e t e r m i n e

the

most

s u i t a b l e query language.

Our e v a l u a t i o n of query languages tables.

For

generating

and

Delphi-like method s e r v i n g a l s o findings.

filling as

a

centers these valTdity

around

several

t a b l e s we used a check

of

our

F i r s t w e made t h e taxonomies of q u e r y languages.

The


Page 9

e v a l u a t i o n parameters i n surveying

the

the

literature,

definitions.

agreed

and

reconciling

our

filled-in

the

We

i n d e p e n d e n t l y and had agreement entries.

were

extracting

i m p o r t a n t c o n t r i b u t i o n s , and precise

tables

in

upon

after

generalizing

the

differences

for

table

approximately

entries

90% of

The only c a s e where we had t h e e x a c t o p p o s i t e e n t r i e s

i n a column was caused by a n ambiguous d e f i n i t i o n of t h e heading;

particular

in

language

this

is

paper

i s the 'best'

not

to

important

question

is:

language f o r a c e r t a i n c l a s s survey

what of

psychologically

suggest

that

R a t h e r , we b e l i e v e

f a c t o r s make a QL a b e t t e r

users

and

oriented

applications. studies

of

We query

languages and r e l a t e t h e i r major r e s u l t s and c o n c l u s i o n s t o taxonomy.

our

Although t h e s e r e s u l t s s h o u l d be t a k e n w i t h c a u t i o n ,

we a r e a d v o c a t e s with

a

i n t e r n s of u s e r performance

[LOCBO 76, LOTS 771 o r coverage of f e a t u r e s .

therefore

column

t h e column was s u b s e q u e n t l y dropped.

Our purpose

the

the

of

query languages.

psychologically

oriented

experimentation

Quoting from fSHNEI 781, '...each

result

i s l i k e a s m a l l t i l e c o n t r i b u t i n g t o a n emerging mosaic of behavior...'.

user

One purpose of a taxonomy f o r q u e r y languages i s

t o i d e n t i f y a r e a s where f u r t h e r human

factors

experiments

are

most u r g e n t l y needed.

In t h e n e x t s e c t i o n we begkn o u r h i e r a r c h i c a l presenting

the

highest

level;

languages

are

taxonomy

by

categorized

a c c o r d i n g t o t h e d i f f e r e n t c l u e s and u s e r s e n s e s employed d u r i n g t h e i n t e r a c t i o n of t h e u s e r w i t h t h e system.


Page 10

THE SENSES LEVEL

3.

The

first

restricted hardware

generation

interaction interface

artificial

query

languages

environment.

[terminal,

The

provide user

keyboard),

and

a

has a l i m i t e d a

relatively

conceptual model of t h e d a t a and t h e i r o r g a n i z a t i o n .

The u s e r a l s o has a formal query language syntax ( t h e the

rules

of

game), and uses h i s experience and mastery of t h e system t o

accomplish h i s t a s k (how t o p l a y and win t h e game). visual

ability

The

they

are

Rather,

Furthermore, t h e u s e r

r e p r e s e n t e d by f o r m a t t e d t e x t .

does n o t employ f u l l y h i s s e n s e s and c o g n i t i o n .

For

instance,

formulation he i s n o t u s i n g v o i c e , touch, h e a r i n g , o r

query

gesture.

user's

while i n t e r a c t i n g with t h e database i s l i m i t e d ;

t h e o b j e c t s of i n t e r e s t a r e r a r e l y d i s p l a y e d d i r e c t l y .

in

very

Additionally,

his

knowledge

of

spatiality

is

not

The u s e r may s t i l l perform h i s t a s k b u t with ljlmited

utilfzed.

p r o d u c t i v i t y and a t t h e expense of more s t r e s s ,

less

interest,

and less p l e a s u r e .

Considerations such a s t h e s e have l e d t o second QL

systems

which

a t t e m p t t o i n c r e m e n t a l l y u t i l i z e t h e human's

i n s t i n c t s and senses. systems basic

Shneidennan [SHNEI 821

a s " d i r e c t manipulation systemsi'. features

reversible

are:

actions,

object

of

of

these

QL

refers

to

these

He states that their

interest

visibility,

rapid

and replacement of command language s y n t a x

by d i r e c t manipulation of o b j e c t s . some

generation

systems

and

In t h i s present

section a

we

review

categorization I n

r e l a t i o n t o f i r s t g e n e r a t i o n QLs.


Page 11

The emergence of t h e second g e n e r a t i o n query not

coincidental.

-

Hardware New

is

R a t h e r , it has followed and has been g r e a t l y

a s s i s t e d by developments i n many r e l a t e d a r e a s .

(a)

languages

Notably:

Developments

devices

such

as

videodiscs,

content

addressible

memories, h o l o g r a p h i c memories, and o p t i c a l s t o r a g e d e v i c e s allow f o r increased c a p a b i l i t i e s i n s t o r i n g d a t a i n s e v e r a l forms.

use

emergence

of

of

accessing

A d d i t i o n a l l y , v o i c e r e c o g n i z e r s and

s y n t h e s i z e r s , e y e - t r a c k i n g and increased

and

pointing

devices

multi-media i n t e r a c t i o n s .

microprocessor

technology

lead

to

Finally, the

assists

in

the

p r o l i f e r a t i o n of telecommunication networks and d i s t r i b u t e d processing.

( b ) - Developments

2

Graphics ~d

Artificial Intelligence

The a b i l i t y t o d i s p l a y i n f o r m a t i o n i n t h e most n a t u r a l dense

form, t h a t of an image, coupled with h i g h - r e s o l u t i o n

d i s p l a y d e v i c e s and t h e u s e of c o l o r , to

imediate

the

direct

comprehension

representation

interest

[NeSp 79,

processing,

and

-

of

greatly

of

MOORH 761.

objects

of

Research

in

particularly i n natural

e x p e r t systems and r o b o t i c s

f o r m u l a t i o n and u s e r feedback [GaPa 8 Q l . generation

contributes

query o u t p u t and t h e

manipulation

FoVD 8 2 ,

a r t i f i c i a l intelligence

second

and

-

language

a s s i s t s i n query In

general,

the

QL systems a p p e a r more " i n t e l l i g e n t " t o

t h e user.


Page 12

Ic )

-

&

Developments

Psychology

Related Sciences

I t seems t h e r e i s a new i n t e r e s t i n b r i d g i n g

between

the

gap

t h e r e s e a r c h e r s and p r a c t i t i o n e r s mostly concerned

w i t h t h e human f a c t o r s

aspects

their

are

colleagues

technology

of

tremendous

who

query

query

primarily

language

possibilities

of

concerned

design.

for

languages,

Because

interaction

with

and

with the of

the

second

g e n e r a t i o n query languages, t h e need f o r s c i e n t i f i c methods to

deal

w i t h t h e complex c o n d i d e r a t i o n s of 'convenfence',

'friendLiness\ apparent.

and

Several

"efectiveness'

of

QLs

becomes

p s y c h o l o g i c a l s t u d i e s of QLs have been

r e c e n t l y r e p o r t e d [BrSh 78, REISN 75,81, SHNEI 78, WeSt 811 and

considerable

interest

has

been

generated

i n human

f a c t o r s of query languages a s evidenced by new p r o f e s s i o n a l meetings

and

special

i s s u e s of academic computer s c i e n c e

and p r o f e s s i o n a l p u b l i c a t i o n s f o c u s i n g on human f a c t o r s .

Id)- Success

Computer Games

Computer games have r e v o l u t i o n i z e d t h e way p e o p l e interfaces

to

computer

systems.

The p l e a s a n t and s i m p l e

i n t e r a c t i o n h a s helped remove many that

humans

Naturally,

have

the

while

success

faced of

perceive

psychological

with

computer

a

barriers

computer system. games

influences

d e s i g n e r s of QLs [MALON 821.


Page 13

It i s hard t o a c c u r a t e l y i d e n t i f y t h e p e r s o n l s ) r e s p o n s i b l e

for

the

emergence

of

second

g e n e r a t i o n query languages.

seems though, t h a t Negroponte and F i e l d s

deserve

major

It

credit

w i t h t h e p r e s e n t a t i o n a t t h e Conference on Very Large Data Bases [FiNe 761.

They

emphasized

clues predefined According

like

data

that,

attribute

traditional

names,

relationships

in

QLs

attribute

order

to

and

iconic

(how

the

d a t a look l i k e ) .

n a v i g a t i n g through t h e d a t a b a s e t a k e s different

values

and data.

EFiNe 761, t h e next s t e p i s t o go beyond symbolic

to

is)

only

retrieve

c l u e s t o o t h e r , more n a t u r a l c l u e s , such as s p a t i a l data

use

a

(where

Browsing o r

dLmension;

new

the

very

from t h e one d e s c r i b e d by Bacbman i n h i s T u r i n g Award

l e c t u r e where t h e programmer i s p o r t r a y e d a s a n a v i g a t o r f i n d i n g his

way

through

a

network

structured

s p a t i a l knowledge seems e s p e c i a l l y

organization

research and

significant

The u s e of

among

all

the

There i s ample documentation i n

i n t e r e s t i n g i d e a s i n tFiNe 761. psychological

database.

substantiating

the

power

of

spatial

t h e a b i l i t y of humans t o remember by l o c a t i o n

and appearance EFiNe 761.

A prototype

database

management,

jmplemented currently

by

Chris

include

based

called Herot

on

the

SDMS, at

CCA

principle

has

been

arrangement.

spatial

developed

[Nerot 81, 8 2 1 .

systems the

ECCA

ability

771. to

The

advantages

It

and

is

SDMS

of

the

l o c a t e o b j e c t s of i n t e r e s t by

browsing and zooming, and t h e u s e of i c o n s , c o l o r , and

of

on INGRES [STONE 7 51 w i t h p l a n n e d e x t e n s i o n s

running

t o o t h e r database system

system

highlighting

s u p p o r t s a m u l t i p l i c i t y of d a t a t y p e s :


Page 14

v i d e o and v i d e o d i s c Lmages, i l l u s t r a t i o n s , t e x t , and i c o n s which are

direct

functLons.

representations An

of

t h e u n d e r l y i n g computer system

example of t h e l a t t e r [HEROT 821 i s a n i c o n of

a

c l o c k w i t h t h e c o r r e c t time from t h e computer system.

Another system based multi-media

user

query

the

interface

capability

to

same

principles

databases

of

data

for

of

a

a d a t a b a s e by making u s e of v i d e o d i s c

are

presented

to

the

Motion and

still

u s e r , t o g e t h e r with

browsing c a p a b i l i t i e s and s p a t i a l i n f o r m a t i o n . option

on

i s t h a t of McDonald

technology and i n t e r a c t i v e computer g r a p h i c s . pictures

and

The purpose of t h i s p r o j e c t i s t o develop

[McDON 81, 82a, 82bl. a

on

The u s e r has t h e

u s i n g t h e keyboard, a joystick, o r a touch-panel.

v e r y i n t e r e s t i n g f e a t u r e of t h e system i s

the

flexibility

A

the

u s e r has i n p e r s o n a l i z i n g t h e method of q u e r y i n g t h e d a t a b a s e .

McDonald's system r e q u i r e s t h e u s e r t o machine v i a t h r e e s c r e e n s .

interact

with

the

T h i s s i m u l t a n e o u s viewing c a p a b i l i t y

may have some d i s a d v a n t a g e s c o n s i d e r i n g i n e v i t a b l e head movement and

possible

user

u s i n g t h e system difficulties

in

confusion. a

laboratory

order

a r e not very

setting,

McDonald

reports

p r o v i d i n g i n p u t f o r multi-media i n t e r a c t i o n s .

a l s o r e p o r t s t h a t touch-panels, this

In s e v e r a l e a r l y e x p e r i e n c e s i n

keyboard,

i n user preference. convenient

to

use

and

joystFck

She

follow

The o b s e r v a t i o n t h a t j o y s t i c k s contradicts

the

experiences

r e p o r t e d i n [NEROT 821 and t h e f i n d i n g s o f [EnGr 751.


SECOND GEWRATION QUERY M G U A G E S

BY

LE VIDEO GRAPHIC QUERY FACILITY

keyboard f u n c t i o n keys picking d e v i c e s touch-sensitive screens voice-recognizers gesture-tracking eye-positioning tracking

keyword c o m n d s menus gesture eye-positioning zooming voice browsing by-example form-f i l l i n g touch

screen v o i c e synthesizer c o l o r graphics video-display printer

Lists Tables Forms Templates Icons Color n i g h l i g h t ing Images Sounds o r v o i c e Arrangement Text

keyboard f u n c t i o n keys picking devices

by-example form-filling

screen printer

Templates Tables

keyboard f u n c t i o n keys touch-sensitive screens picking devices

menus browsing pointing touch

screens (multiple) printer video-display color graphics

Tables Icons Color Arrangement

I

I

v o l c e synthe-

Table 2(a):

Taxonomy of Query Languages a t t h e S e n s e s L e v e l

Center for Digital Economy Research Stem School of Business \Vorking Paper IS-82-35

Low-Medium

Low-Med ium

Table 2 ( b ) :

Taxonomy of Query Languages a t t h e S e n s e s Level

Page 17 The only commercially available Query-By-Example model o f data. and

771,

EZLOOF

second

generation

QL

is

which i s based on t h e relational

Relations are represented d i r e c t l y on t h e screen

t h e user moves the cursor f r e e l y along the rows and columns Query formulation i s done

of the tables. examples;

a

natural

education

major contributions and t h e

through

process.

success

the

use

of

We b e l i e v e t h a t t h e

secrets

of

QBE

are

the

"by-example" principle, t h e two-dimensional data representation, and t h e stepwise l e a r n a b i l i t y feature. fact

that

The l a t t e r r e f e r s t o the

a novice can perform something interest2ng i n a very

short t i m e , yet the system provides a l o t expert user.

more

power

for

the

Several psychological studies focusing on QBE w i l l

be discussed i n Sectkon 5 . In Table 2 we

present

an

evaluation

and

comparison

of

second generation QLs with f i r s t generation query languages.

In

addktion, we present t h e evaluation o f example second generation QL SySternS.

The f i r s t part o f Table 2 examines languages the

query

parameters.

formulatiog For

and t h e output

query

d i f f e r e n t media

that

instance, the user

of

formulation

in

terms

interaction we

first

consider

are available t o t h e language user. a

second

of

generation

QL

may

have

the For in

addition t o t h e regular keyboard some pkcking devkces i j o y s t i c k , mouse), a touch s e n s i t i v e screen, a voice more

important

distinction

though

recognizer,

etc.

A

between t h e two generation

languages with respect t o query formulation i s t h e

I


Page 18 the

clues

and

senses

which

2nformation from t h e database. greater

use

of

senses

the

user

employs

user

reply.

of

The

and cogn2tion.

much

Output p r e s e n t a t i o n i s system

informs

t h e a c t i o n r e s u l t , and t h e format of t h e system's latter

appearance,

extract

Second generation QLs make

f u r t h e r subdivided i n t o t h e medkum on which t h e the

to

and

refers their

to

the

types

arrangement

of

objects,

that

may

their

facilitate

comprehension of t h e i n t e r a c t i o n .

The second p a r t of Table 2 i s more s u b j e c t i v e d e a l i n g the

d p a m % c s of

languages. user

user

interaction

for

Interaction c h o k e refers

has

in

choos2ng

medium

appropriate

for

the

task

interesting

and

the

challenge

results,

we

be

say

t h e e v a l u a t i o n of t h e

to

the

flexibility

s t y l e of i n t e r a c t i o n ;

interactLon

important

can

the

switched at

to

that

one

the

whether t h e

is

which

more

When t h e k n t e r a c t i o n i s

hand. of

with

interaction the

has

visBbly

QL system provkdes high

gamesmanshkp.

Most f i r s t g e n e r a t i o n QLs h i g h l y depend on database model.

underlying

It B s e s s e n t i a l t h a t t h e u s e r knows whether t h e

underlying d a t a b a s e system and model network [CODAS 7 1I operate.

the

, or

is

relational

[CODD 711,

h i e r a r c h i c a l [ I B N 751 f o r t h e language t o

The u n d e r l y i n g database model 2 s g e n e r a l l y t r a n s p a r e n t

t o t h e second g e n e r a t i o n language u s e r .

The u s e r can make c l e r i c a l , s y n t a c t i c during

the

5nteraction

or

semantic

errors

and t h e p r o b a b i l m o f something going

wrong i s not s u b s t a n t i a l l y d i f f e r e n t f o r t h e two g e n e r a t i o n QLs.


Page 19

F&ner d i s t k n c t i o n s of e r r o r s a r e d i s c u s s e d i n t h e n e x t s e c t i o n . O n t h e o t h e r hand, t h e

amount

of

traininq

required

for

the

a c q u i s 2 t k o n of t h e a b i l f t y t o complete an i n t e r e s t i n g t a s k seems t o b e lower with second g e n e r a t i o n QLs.

With

the

direct

manipulation

of

objects

in

second

g e n e r a t i o n query languages, t h e amount of u s e r feedback from t h e system i s v e r y high; Most

users

find

the

it

actkon

is

here

instantly

visible.

i m p o r t a n t t o have t h e f e e l i n g of b e i n g i n

c o n t r o l d u r i n g t h e i n t e r a c t i o n with

the

system;

we

find

no

s u b s t a n t i a l d i f f e r e n c e h e r e between t h e two g e n e r a t i o n QLs.

Where second g e n e r a t i o n QLs, status,

have

less

at

least

capabkl&tLes i s

on

g e n e r a t i o n QLs seem t o have an advantage

in

their

current

funct&onality. here

since

First

they

can

cover a b r o a d e r and more d i v e r s e s e t of f u n c t i o n s .

Different requirements.

requests

may

have

different

output

format

The amount of u s e r f l e x i b i l i t y i n c o n t r o l l i n g t h e

format of t h e o u t p u t i s c a p t u r e d

by

the

user

output

control

parameter.

In summary, second g e n e r a t i o n QLs have over

several

t r a d k t f o n a l f k r s t g e n e r a t i o n query languages:

advantages t h e methods

t h a t t h e u s e r employs i n query f o r m u l a t i o n and comprehension

of

t h e r e p l y , t h e amount of t r a i n i n g r e q u i r e d , t h e system feedback, and t h e gb%esmanship of t h e i n t e r a c t 3 o n .

A d i s a d v a n t a g e may

be

t h e l i m i t e d language coverage.


Page 20

A word of c a u t i o n i s needed.

a

new

burden

Second generation QLs prov2de

of r e s p o n s i b i l i t y f o r t h e applicat2on developer.

For i n s t a n c e , t h e a p p r o p r i a t e i c o n s t o

represent

use of c o l o r and h i g h l r g h t i n g , and t h e ' n a t u r a l '

objects,

the

arrangements of

t h e o b j e c t s i n t h e database g r e a t l y i n f l u e n c e t h e success of t h e system.

Additional

designers.

These

skills

new

may

skills

be

are

needed not

for

found

application

today

in

the

t r a d k t i o n a l systems analysks and deskgn education.

Furthermore, t h e f a c t t h a t t h e query part,

although

a

language

is

only

c e n t r a l one, of t h e " t o t a l " i n t e r f a c e should

n o t be overlooked.

In a l a y e r of s e v e r a l computer

systems

t h e second generation QL i s t h e outmost l a y e r .

languages

a

and

Apart

from t h e obvious overhead, t h e r e i s t h e g r e a t r i s k of f a l l i n g t o a

lower l e v e l system during t h e i n t e r a c t i o n .

It i s very l i k e l y

t h a t t h e i n t e r a c t i o n with such a lower l e v e l system w i l l n o t consistent

with

protection

mechanisms

interaction

the

level

second

to

for

a

another

generation smooth

QL.

be

We b e l i e v e t h a t

transition

from

one

i s a s t r o n g requirement f o r t h e

s u c c e s s of second generation query language systems.

4.

THE METHODS LEVEL

The languages

previous

section

accordkng

to

generatkon

query

a

taxonomy

of

query

t h e c l u e s and t h e u s e r s e n s e s t h a t a r e

employed f o r t h e i n t e r a c t i o n . first

presented

In t h i s

section,

we

categorize

languages a c c o r d i n g t o method t y p e and


Page 21

e v a l u a t e them with r e s p e c t t o i n t e r a c t i o n and

user

parameters.

The t a b l e e n t r i e s

Table 3 summarizes our f i n d i n g s .

performance

and h i g h l i g t s of our comparison a r e now explained.

W e c l a s s i f y t h e f i r s t generation query languages

groups:

functkon-key,

graphic

or

keyword,

pictorial,

positional

a d d i t i o n , we r e l a t e findings

line-by-line

in

restricted

keyword, the

results

eight

prompting, menu s e l e c t & o n , natural

and

in

language,

mathematical

from

this

linear

keyword.

taxonomy

to

In our

t h e s e n s e s l e v e l by grouping t h e second g e n e r a t i o n

QLs ( l a s t row of Table 3 ) .

The use of f u n c t i o n method

i s a ILmited

but

very

of i n t e r a c t i o n f o r inexperienced u s e r s .

effective

By t h e p r e s s of

a s p e c i a l key on t h e keyboard, a p r e v i o u s l y prepared t r a n s a c t i o n or

Is

report

parameterized system-driven

processed.

Line-by-line

ineraction

[LeBl 791,

dialogue.

built-up

a

t h e name

of

the

user's

dialogue

is

responses. menu

A

sjlsnple

the

more

selection.

r e q u i r e d t o p o i n t t o h i s c h o i c e from a menu of by t h e system.

very

f i e l d name, a comparison v a l u e , e t c .

from

system-driven

a

called

I n t h e t y p i c a l c a s e , t h e u s e r w i l l be

prompted t o e n t e r ( l i n e - a t - a - t k n e ) interest,

is

, also

object

of

The query i s sophisticated

Here, t h e u s e r i s options

Menus a r e s t r u c t u r e d h i e r a r c h i c a l l y ;

offered

t h e choice

of a n o p t i o n may cause t h e a v a i l a b i l i t y of a new menu [ElNu 801. These

three

language methodologi!es a r e u s u a l l y custom-made f o r

specific applications.

They may b e based on a lower l e v e l query

language.


Page 22


Page 23

In graphic manipulate

or

visual

pictorial symbols

query

EMCDON

the

t o formulate q u e r i e s .

and r e l a t i o n s h i p s i n t h e d a t a b a s e a r e geometric shapes

languages

user

can

The e n t i t i e s

represented

by

specffic

75, TSICH 76, SENKO 78, ChFu 791.

The r e s t r i c t e d n a t u r a l language mode has a t t r a c t e d i n t e r e s t in

r e c e n t years.

The i n t e n t i o n i s t h a t t h e u s e r can employ h i s

n a t i v e n a t u r a l language l e . g . interaction

with

English, German, French) f o r

A t l e a s t one such QL system i s

t h e database.

c o m e r c f a l l y a v a i l a b l e LAIC 82, HARRI 771 and s e v e r a l o t h e r s the

research

laboratory

at

ELEHMA 77, 78, PLATH 76, CODD 74, 78,

Some n a t u r a l language systems w i l l

WALTZ 78, WILKS 771.

the

engage

i n a d i a l o g u e with t h e u s e r t o r e s o l v e any ambiguity i n r e q u e s t s [CODD 781.

We

communication far

from

should in

out

to the

person-person prefix

the

natural

language

a r t QL systems i s s t i l l cornnunfeation;

"restricted".

s i g n i f i c a n t f o r some s e m a n t i c a l l y for

that

a l l such s t a t e - o f - t h e

close

~ u s t i f i c a t i o n of

point

This

restricted

may n o t b e

applications

some t y p e s o f u s e r s [TURNE 82, STOHR 821.

t h a t n a t u r a l language i s a second g e n e r a t i o n

the

and

It may b e argued

QL.

Even

though

n a t u r a l language may become a dominant QL i n t h e f u t u r e , it does n o t meet our c r i t e r i a f o r second g e n e r a t i o n QLs; has

limited

use

of

the user still

methods, i n s t i n c t s and s e n s e s t o i n t e r a c t

with t h e database.

The m a j o r i t y of q u e r y languages f a l l i n t o t h e l i n e a r keyword.

category

of

These languages u t i l i z e s t a t e m e n t s s i m i l a r t o a

p r o g r m i n g language such a s

FORTRAN,

but

more

English-like.


Page 24 The

commands

have

a

definite

syntax

s p e c i f i c reserved l i s t can be used. linear

keyword

languages

and QUEL [ S T O N E 7 51

are:

and

Some

only words from a

typical

operands

to

of

[ I B M 751 ,

SQL [ D E N N Y 771 , DL/1

to

the

convey

position

replace

ESCHMI 77,TODD 761.

wordy

The succinctness

of

the

command

meaning [BOYCE 753.

keyword languages use t h e precise notation o f formalism

examples

.

Some keyword languages use operators

and

Other

the

mathematical

English-like

expressions

of

mathematlcal

symbols

allow f o r short expression o f powerful operations.

We have included i n t h e

Appendix

a

list

of

example

QL

language systems as well as the methodologies they employ, t h e i r procedurality type and the underlying database model and system. Representative

QLs are

also

presented

i n t h e l a s t column o f

Table 3 .

The query language t y p e s , as defined above, in

terms

of

three

basic

interaction

, and

f o r m u l a g n , language

are

evaluated

parameters:

output presentation.

Query formulation describes the overall e f f o r t o f t h e to

work

with

the

system.

I t

is

further

the

amount

of

n u t

expressing

the

for t h e query expression (e.g.

number o f k e y s t r o k e s ) , t h e type o f errors i n and

user

divided i n t o the

thinking e f f o r t required before the user s t a r t s request,

query

query

formulation

t h e i r handling, and f i n a l l y , t h e t r a i n i n g e f f o r t needed for

t h e interaction.


Page 2 5

Most query languages impose a s t r i c t p r o t o c o l the

user

[REISN 841

of

keyword-oriented

introduces

languages.

This r e f e r s t o the

u s e r adopts t o e x p r e s s t h e r e q u e s t .

is

higher

languages

which

model

for are

Reisner

t h e n o t i o n of a "model of t h e p r o c e s s of

query w r i t i n g " t h a t u s e r s develop. the

require

This i s e s p e c i a l l y

t o remember s y n t a c t i c c o n s t r u c t s .

characteristic

and

keyword

The

oriented

systm-driven

strategy of t h i s

languages

dialogues

than

for

(,e,g,

menu

selection).

I n p u t r e f e r s t o t h e amount of c l e r i c a l e f f o r t i n e x p r e s s i n g When t h e i n t e r a c t L o n i s v i a a keyboard t h i s may b e

the request.

measured with t h e number

of

keystrokes.

Alternatively,

with

p o i n t i n g d e v i c e s a good measure i s t h e number of p o i n t e d o b j e c t s [LOTS 811.

The c l e a r winners i n t h i s c a t e g o r y a r e f u n c t i o n keys

and menu s e l e c t i o n .

Three

main

formulation:

types

clerical

of

error

(e.9,

may

occur

a

semantic

lfomulation

s y n t a c t i c a l l y c o r r e c t query which does n o t s o l v e t h e t a s k

a t hand).

will

occur

We c o n s i d e r h e r e t h e for

probability

d i f f e r e n t language t y p e s .

that

such

it

has been d e t e c t e d .

occurs,

function key).

the

correction

an

error

Our f i n d i n g s i n d i c a t e t h a t u s e of

f u c t i o n keys r a r e l y r e s u l t s i n any t y p e of error

errors

Furthermore, we a r e

i n t e r e s t e d i n t h e amount of e f f o r t r e q u i r e d t o h a n d l e after

query

t y p o s ) , s y n t a c t i c ( n o t following

t h e c o r r e c t s y n t a x of t h e l a n g u a g e ) , and of

during

effort

errors,

and

if

an

i s small ( p r e s s another

On t h e o t h e r hand, t h e c h a l l e n g f n g i n t e r f a c e

of


Page 26 a

second

generatkon

QL

may

result

f o l l o w t h e wrong p a t h while browsing)

i n semantic e r r o r s le.g. for

which

the

handlhg

This i s n o t t h e e a s e w i t h c l e r i c a l o r s y n t a c t i c

e f f o r t i s high.

e r r o r s i n second genaration QLs;

these errors

are

immediately

d e t e c t e d and t h e r e i s a r a p i d r e v e r s k b l e a c t i o n t o c o r r e c t them.

The amount of t r a i n i n g necessary f o r t h e u s e r level

where

he

consideration training

can

for

2nto

perform

language

to

reach

a

u s e f u l t a s k s i s a very fmportant acceptance.

three categories:

We

have

subdivided

u s e r t y p e l e v e l , composition,

and comprehension.

The u s e r type l e v e l r e f e r s t o t h e degree of user

must

have

before

he

can

use

corresponds t o novice u s e r , medium l e v e l high

expertise

t h e language. to

skilled

Low l e v e l user

and

l e v e l corresponds t o p r o f e s s i o n a l u s e r ( s e e a l s o Sectkon 5

f o r detailed have

an

definitions).

edge

here;

since

System-driven the

user

is

dialogue

languages

guided

durfng t h e

i n t e r a c t i o n , t e c h n i c a l e x p e r t i s e i s n o t necessary. that

the

the

W e a l s o note

u s e r s of r e s t r i c t e d n a t u r a l language must be s k i l l e d ,

a t l e a s t with r e g a r d t o t h e a p p l i c a t i o n domain.

Composition i s t h e t a s k of f o r m u l a t i n g a query.

is

that

A facility

easy t o l e a r n f a c i l i t y i s n o t n e c e s s a r i l y easy t o use.

The analogue i s with t h e p r o g r m i n g language BASIC; almost

takes

no tlime t o l e a r n , b u t w r i t i n g a complex program i n BASIC

i s n o t an easy t a s k .

very

it

little

trainfng

experience ETURNE

Second g e n e r a t i o n query languages

require

f o r using t h e available f a c i l i t i e s .

Our

821 i s t h a t t h e " r e s t r i c t i o n s " p a r t i n n a t u r a l


Page 27 language

n e c e s s i t a t e s t r a i n i n g f o r query composition.

must be t a u g h t t o use o n l y

the

allowable

unambiguous

The u s e r English

constructs.

Comprehension r e f e r s t o t h e amount of t r a i n i n g r e q u i r e d understand

a query formulated by another user.

t o understand an unambiguous also

It i s very easy

language

statement.

We

c o n j e c t u r e t h a t a u s e r understands e a s i l y a l i n e a r keyword t h i s i s explained from t h e simple syntax and a p p r o p r i a t e

query; keyword with

natural

to

s e l e c t i o n i n such languages.

little

mathematical

On t h e o t h e r hand, a u s e r

background

find

will

it

hard

to

comprehend a query i n a mathematical keyword language.

The second major parameter f o r query language e v a l u a t i o n i s language

-

power

what f a c t o r s t h i s function

keys

how much a u s e r can do with t h e Language and depends

and

menu

on.

selection

s i m p l i c i t y i n query formulation. designed

to

be

powerful,

the

number

has

where to

the

user

of

pay t h e p r i c e f o r

Although such languages can be

t h e y can never reach t h e e x p r e s s i v e After a l l , there are

power of a keyword-type QL. on

is

This

upper

bounds

of f u n c t i o n keys a v a i l a b l e and on t h e number of

a l t e r n a t i v e s t h a t may be s e l e c t e d b e f o r e t h e menu p a t h becomes a labyrinth.

System-driven application general

domain

purpose.

application

query while In

languages keyword

addition,

Ivocabulary)

must

depend

on

the

orLented languages a r e more the

be

heavily

terminology

of

the

defined before a r e s t r i c t e d

n a t u r a l language i s u t i l i z e d .


Page 28

discussed

As

generation

in

Section 4,

depends

QLs

on

the

usage

of

most

t h e underlying database system and

t h i s i s e s p e c i a l l y t r u e with keyword o r i e n t e d languages.

model;

S e l e c t i v i t y i s t h e a b i l i t y of t h e language u s e r t o as

first

precisely

as

possible

what

data

he

wishes

t o retrieve

The d e s i r a b l e high s e l e c t i v i t y i s u s u a l l y

[LOTS 811.

specify

found

in

keyword t y p e languages and second genaration QLs.

F u n c t i o n a l i t y r e f e r s t o t h e number of d i f f e r e n t language

can be used f o r .

seems t o be generation

the QLs

major

the

A s we p o i n t e d o u t i n s e c t i o n 4 , t h i s

user

(except

tasks

performance

advantage

of

first

f u n c t i o n keys and menu s e l e c t i o n ) over

second generation query languages.

Our t h i r d major presentation.

This

criterion

variation

[the

which

responsiveness

the

flexibility

p r e s e n t a t i o n format and/or devices),

comparison

QL

in

redirecting (how

rapid

output

presented),

is

selecting output

and

to

suited

output

mostly depend on t h e Regardless,

for

the

system

than

output

is

the

have

the

consistent

application). rather

an

alternative

system's r e s p o n s e ) , and customization ( t h e a b i l i t y t o best

output

is

i s subdivided i n t o c o n t r o l l a b i l i t y of t h e

u s e r t o c o n t r o l t h e pace a t format

for

These parameters

the

language

type.

t h e philosophy behind c e r t a i n language groups l e a d s

t o a more n a t u r a l a d a p t a t i o n of a d e s i r a b l e o u t p u t f e a t u r e i n system. than

a

For i n s t a n c e , customization i s e a s i e r i n menu s e l e c t i o n with

a

positional

keyword

language

and

system

responsiveness i s h i g h l y v i s i b l e i n second g e n e r a t i o n QLs.


Page 29

The c o n t r i b u t i o n of t h i s s e c t i o n i s t h e and

the

presentation

of

usability

and

taxonomy

of

QLs,

interaction features

a c c o r d i n g t o which query language designs can be evaluated.

The

reader

The

may

look

at

Table 3

c o n s t a n t c o s t i s t h e amount of language

can

be used.

a s a cost-benefit training

necessary

from

the

before

the

V a r i a b l e c o s t s a r e t h e e f f o r t s involved

i n f o r m u l a t i n g q u e r i e s and handling e r r o r s . derives

analysis.

language

power

The

user

benefit

and t h e o u t p u t p r e s e n t a t i o n

features.

Not a l l e n t r i e s i n Table 3 a r e s u b j e c t i v e .

For

instance,

t h e f a c t t h a t t h e f u n c t i o n a l i t y of keyword-oriented languages i s high i n comparison t o t h e use of f u n c t i o n keys prompting i s v e r y h a r d t o argue a g a i n s t .

or

line-by-line

On t h e o t h e r hand, f o r

t h e few s u b j e c t i v e e n t r i e s i n Table 3 , such a s u s e r

type

level

and u s e r model of query w r i t i n g complexity, w e remind t h e r e a d e r t h a t t h e methodology we followed ( d e s c r i b e d i n not

have

strong

scientific

validity.

approach may be misleading a s p o i n t e d o u t conjectures approach.

can

be

The in

s e c t i o n 2) "common

does

sense"

[MORAN 811.

Our

t e s t e d u s i n g what Moran c a l l s t h e f e a t u r e s

T h i s r e f e r s t o experiments t o measure t h e

impact

of

language f e a t u r e s on u s e r performance.


Page 30

5.

U S E R TYPES A N D ---

QUERY LANGUAGES

In t h i s section, we r e l a t e our taxonomy o f query to

the

d i f f e r e n t types

c l a s s i f i c a t i o n scheme o f which

methods

types.

of

users.

query

We

language

languages

develop

users

a

and

unified

recommend

would be most appropriate f o r t h e d i f f e r e n t user

Where possible, we substantiate our position by e x i s t i n g

human

factors

studies or point out areas where further studies

are needed.

Many c r i t e r i a f o r

classifying

users

781 but t h e i r relationships have hardly uses

a

proposed

expand

it

to

elsewhere. can

An

be

diaensions, frequency

been

studied.

[SHNEI

two-dimensional scheme c l a s s i f i e d by syntactic and

semantic knowledge.

them

been

7 4 , C U F F 80, LeBl 7 9 , MORAN 8 1 , S H N E I 8 0 , YORMA 77, ZLOOF

[CODD

801

have

We base our analysis on

include

other

his

approach

c r i t e r i a t h a t have been proposed

analysis o f these c r i t e r i a reveals t h a t derived

from

namely, of

a

system

familiarity

query

but

language

with

with

of

the four ( b i n a r y )

programming

usage,

most

knowledge

concepts, about

the

application, and range o f d i f f e r e n t operations required.

Familiarity

with

programming

concepts

seems

a

better

wording than the often-cited d i s t i n c t i o n between programmers and non-programmers, which inconsistent

may

interpretations

lead

to

different

and

is

not

afraid

of

times

[ C U F F 80, GrWa 7 8 , MORAN 811.

assign "high" f a m i l i a r i t y with programming concepts who

at

computers

to

a

We user

and has acquired logical or

algorithmic problem-solving a b i l i t i e s .


Page

Table 4 (a):

(novice u s e r )

(skilled user)

(skilled user)

(professional user)

User t y p e s

31

-

~ n t e r a c t i o nc a p a b i l i t y ( s y n t a c t i c knowledge) a s a f u n c t i o n of f a m i l i a r i t y w i t h p r o g r a m i n g c o n c e p t s a n d f r e q u e n c y o f system usage.

casual user

c l e r i c a l user

s p e c i a l i s t user

Table 4 ( b ) :

User t y p e s

-

T a s k s t r u c t u r e ( s e m a n t i c knowledge) a s a f u n c t i o n o f a p p l i c a t i o n knowledge a n d r a n g e of o p e r a t i o n s .


Page 32

The

dimension

of

frequency

system

usage

was

first

We demonstrate t h a t t h i s i s one of t h e

i n t r o d u c e d by [LeBl 791.

most Lmportant dimensions by d e r i v i n g from it many of t h e dimensions

appearing

in

the

literature.

Frequency

d e t e r m i n e s d i r e c t l y t h e a c c e p t a b l e amount of t r a i n i n g ; one

wants

justified.

other of

use

t h e more

t o u s e t h e system, t h e g r e a t e r i n i t i a l i n v e s t m e n t i s The

amount

of

training

in

turn

t y p i c a l s k i l l l e v e l a f t e r t h e t r a i n i n g period.

determines

the

We f e e l t h a t t h e

t r a n s i e n t s k i l l l e v e l s d u r i n g t h e t r a i n i n g phase a r e of i n t e r e s t for

q u e r y language s e l e c t i o n o n l y i f t h e frequency of u s e i s s o

low t h a t each u s e of t h e system r e q u i r e s r e l e a r n i n g turnover

of

users

is

extremely

high.

d i s t i n c t i o n between "novice" u s e r ( t a s k : (task:

In

or

this

if

the

way,

the

l e a r n i n g ) and " e x p e r t "

r o u t i n e s k i l l ) made i n EMORAN 811 c a n be reduced t o t h e

frequency

of

'*novicen n o t

usage only

dimension.

We

therefore

use

the

term

f o r new u s e r s b u t a l s o f o r o t h e r i n f r e q u e n t

u s e r s with l i t t l e programming knowledge.

In

combination,

determine system; 4!a)

the

user"

the

two

dimensions

discussed

so

far

a b i l i t y t o t e c h n i c a l l y i n t e r a c t with t h e

h i s o r her "syntactic

knowledge"

Table

[SHNEI 801.

shows t h e r e l a t i o n s h i p between t h e two b a s i c disnensions and

t h e l e v e l of i n t e r a c t i o n s k i l l .

The semantic knowledge

dhensions

are

concerned

and r a n g e of o p e r a t i o n s o f t h e u s e r .

c o n t e x t , a p p l i c a t i o n knowledqe measures conceptual

with

model

the

application

In t h e database

precision

of

the

t h e u s e r h a s a b o u t t h e s t r u c t u r e and c o n t e n t s


Page 33

of t h e d a t a b a s e . very

T h i s c o n c e p t u a l model

d e t a i l e d t o a general idea.

can

be

wants

to

ask

in

the

from

The o t h e r dimension, r a n g e of

o p e r a t i o n s , d e s c r i b e s how many d i f f e r e n t t y p e s user

anything

language.

dLmensFons g i v e a good p i c t u r e of

the

of

queries

the

these

two

Together, task

structure

of

the

u s e r , a n o t h e r semantic c r i t e r i o n ( T a b l e 4 ( b ) ) .

We now proceed t o r e l a t e t h e twelve u s e r t y p e s

defined

by

combinations of s y n t a c t i c and semantic knowledge t o t h e language methods d i s c u s s e d i n t h e p r e v i o u s s e c t i o n .

Developed u s i n g

the

t e c h n i q u e d e s c r i b e d i n t h e Zntroduction and t h e r e s u l t s of human f a c t o r s s t u d i e s , Table 5 language

gives

an

methods f o r each u s e r t y p e .

ordered

list

of

suitable

Before d i s c u s s % n g T a b l e 5

i n d e t a i l , however, we g i v e a g e n e r a l overview of human

factors

r e s e a r c h on t h e methods l e v e l ,

S i n c e t h e now c l a s s i c experkments of [REISN 751 751,

a

number

of

we

can

[ThGo

l a b o r a t o r y s t u d i e s and f i e l d experiments of

human f a c t o r s i n query languages have been purposes,

and

reported.

For

our

c l a s s i f y t h e s e s t u d i e s a s e i t h e r comparisons

between languages t h a t u s e d i f f e r e n t methods,

or

as

usability

s t u d i e s of c e r t a i n f e a t u r e s w i t h i n a language t y p e .

The f i r s t group of experkments c o n s i s t s of keyword

vs.

keyword vs.

second

generation

comparisons

languages [ThGo 75, GrWa 781,

p o s i t i o n a l languages [REISN 751,

and

keyword

r e s t r i c t e d n a t u r a l languages [SHNEI 78, SmWe 77, TURNE 821. r e a d e r i s c a u t i o n e d , however, t h a t n o t a l l of t h e s e intended

a

general

comparison

of

vs. The

experiments

of methods b u t r a t h e r s p e c i f i c


Page 34

comparisons of languages.

Nevertheless, t h e y

give

some

hints

and d i r e c t i o n s f o r f u t u r e r e s e a r c h .

The

second

usability

of

given method. been

the

group

certain

of

experiments

languages

One f o c a l p o i n t

keyword

language

concentrates

on

the

o r language f e a t u r e s w i t h i n a

of

laboratory

experiments

has

[REISN77, West 8 1 , WELTY 79,

SQL

THOMA 761, a n o t h e r t h e i n f l u e n c e of conceptual d a t a models [BrSh 78,

LOTS 781.

I n a d d i t i o n , t h e r e have been a number of f i e l d

s t u d i e s concerned languages

in

with

the

various

usability

settings

of

restrPcted

natural

[RAMER79, HARRI 77, KRAUS 79,

LEHMA 78, TURNE 82, WOODS 721.

A s f o r u s e r t y p e s , most s t u d i e s i n t h e s y n t a c t i c

dimension

focus

toward

laboratory

experiments

Therefore,

as

In

chose

subjects

often

contrasting

overall

learn2ng

addition,

with

user. and

Virtually

retention

all

tests.

most

experimenters

explfcitly

l i t t l e knowledge of programming c o n c e p t s ,

them

background.

better

are

novfce

mentioned above, t h e r e s u l t s a p p l y mainly t o t h e

infrequent user.

programming

the

knowledge

with

another

havPng

group

more

A l l experiments of t h k s d e s i g n show a n

performance

for

users

with

programming

background.

The semantic c l a s s i f i c a t i o n of e x p e r i m e n t a l u s e r s clear.

While

the

laboratory

experiments

mostly

is

less

work

with

s t u d e n t s whose semantic knowledge i s d i f f i c u l t t o e s t a b l T s h , t h e thrust

of

the

field

experiments

is

toward

the application

s p e c i a l i s t , l e s s o f t e n toward t h e managerkaf u s e r .


P a g e 35

line-by-line

menu se 1e c t i o n restricted

line-by-1 i n e

menu s e l e c t i o n

line-by-line

menu s e l e c t i o n

second g e n e r a t i o n

Professions

second g e n e r a t i o n

T a b l e 5:

R e l a t i n g l a n g u a g e methods t o u s e r t y p e s


Page 36

n-programmers

Table 6:

Human p a c t o r s E x p e r i m e n t s w i t h Query Languages and F e a t u r e s


Page 37

The major r e s u l t s of s t u d 3 e s r e f e r r e d t o i n t h i s paper displayed

in

Table

For

6.

a

more

detailed

are

overview

of

l a b o r a t o r y experiments, s e e [REISN 811 o r [SHNEI 8 0 1 .

We now t u r n given

in

to

discussing

the

specifkc

recommendations

Table 5 f o r asskgning language methods t o u s e r t y p e s .

Our procedure w i l l be t o f o l l o w t h e columns

of

the

table

and

t h e n summarize t h e r e s u l t s by language type.

The c a s u a l u s e r i s c h a r a c t e r 2 z e d a s having o n l y

a

general

i d e a about s t r u c t u r e and c o n t e n t of t h e database b u t whose range of needed operatlions 2 s a l s o l j m i t e d s o t h a t he may n o t use f u l l power of a query language [REISN 771. t h e u s e r s of e x t e r n a l electronFc

funds

databases

like

t r a n s f e r systems.

the

Typhcal examples a r e [LOTS 821

videotex

or

Casual u s e r s would o n l y by

chance be f a m i l i a r with programnhg concepts ( t h a t i s t h e reason why

the

lower

f f e l d of Table 5 i s n e a r l y empty) b u t may

left

v a r y kn t h e i r frequency of system usage. the

infrequent

casual

user

c h o i c e s o r line-by-line (skilled)

may

wish

The system must

I n o v r c e ) , by o f f e r f n g skmple menu

prompts, whlile t h e to

adopt

a

more

more

frequent

active

(second

of

actions

.

The managerial u s e r i s probably type.

Unw2lling

user

role

g e n e r a t i o n languages) o r a t l e a s t a f a s t e r sequence ( u s e of f u n c t i o n keys)

guAde

the

most

demanding

user

t o "waste" t h e t o a c q u i r e d e t a i l e d knowledge

of t h e database, he s t i l l wants t o perform q u i t e complicated and varied

t a s k s , e.g.,

types.

Today, menu systems can be used

g e n e r a t i n g summary information of d i f f e r e n t for

s2mple

tasks

and


Page 38

kntermediaries

must

handle

complex

ones

happens t o have programming background

unless

and

r o u t i n e l y ( p r o f e s s i o n a l manager5al u s e r ) .

uses

t h e manager the

database

A more d i r e c t p a t h t o

t h e database i s t h e g r e a t promise of advanced language such

as

second

concepts

generatkon QLs o r r e s t r i c t e d n a t u r a l language.

S t u d f e s of usage of n a t u r a l language show, however, t h a t users

may

novice

have problems with t h e s y n t a c t i c r e s t r i c t i o n s of t h e

language [TURNE 821 o r t h e semantic r e s t r i c t i o n s of the d a t a b a s e For t h i s reason, r e s t r i c t e d n a t u r a l language i s o n l y

[BrSh 781.

positioned i n t h i r d place f o r

novkce

managerial

users.

Some

f i e l d s t u d i e s i n d i c a t e t h a t more f r e q u e n t u s e r s of t h i s t y p e can adapt t o t h e l i m i t a t i o n s [KRAUS 791.

Similar

to

the

casual

user,

the

clerical

user

(or

parametric u s e r [ZLOOF 781 ) h a s t o perform only a liLmEted number of o p e r a t i o n s on organization data.

the

gives

database, him

improves

computer-oriented languages

or

day-to-day more

integration

in

the

or

menus

with

productivity.

frequent

clerical

system

little

For

the

user,

more

keyword

o r even t h e more c o n c i s e mathematical languages a l l o w

f o r powerful o p e r a t i o n s . in

his

d e t a k l e d knowledge about t h e a v a i l a b l e

The use of f u n c t i o n keys

guidance

but

general ( s e e , e.g.,

Many s t u d i e s e x i s t f o r t h i s u s e r

type

[EmNa 8 1 , HUMAN 8 2 1 ) b u t l i t t l e h a s been

published on t a i l o r i n g query languages t o c l e r i c a l u s e r s .

A s t h e range of operatkons becomes

user

turns

into

an

broader,

the

clerical

applicatlion s p e c i a l i s t u s e r ( w e a v o i d t h e

synonymous " p r o f e s s i o n a l u s e r " because we

assigned

this

tktle


already

to

a

syntactic

category).

This type of u s e r can be

expected t o have d e t a i l e d knowledge of t h e database and wants t o do

many

d i f f e r e n t operations ( d a t a analysis, decision support)

but often

lacks

programming

programming

background.

conventional

While

and query languages mainly support t h e p r o f e s s i o n a l

( f r e q u e n t and programming) a p p l i c a t i o n s p e c i a l i s t , most recent

research

focuses

on

novice

For

example,

human

factors

the

and s k i l l e d u s e r s who a r e

expected t o be a dominant group of computer u s e r s future.

of

studies

in

the

near

indicate

that

novices :

*

have d i f f i c u l t i e s with e x p l i c i t q u a n t i f i c a t i o n [THOMA 761;

*

perform b e t t e r with a r e l a t k o n a l model of d a t a t h a n with a network o r h i e r a r c h y when u s i n g a keyword language embedded i n APL [LOTS 781 ;

*

l e a r n a second g e n e r a t i o n language (QBE) f a s t e r t h a n a keyword language (SQL) of s u i l a r power EThGo 75, GrWA 781;

*

perform b e t t e r on hard q u e r i e s with a more p r o c e d u r a l approach (TABLET vs. SQL) f o r problem-solving i n a keyword language [West 811;

*

can be o f f e r e d a ( c l o s e d ) s u b s e t i n a l a y e r e d language [REISN 771.


Page 40

S t u d i e s of t h e use of n a t u r a l language i n t e r f a c e s far

have

so

been i n c o n c l u s i v e , probably due t o d i f f e r e n t u s e r t y p e s and

scope of a p p l i c a t i o n . competitive

if

We hypothesize t h a t n a t u r a l

restricted

to

r e l a t i v e l y sLqple o r t a i l o r e d

a

narrow

database

language

domain

structures

is

[WOODS

721,

EHARRI

77,

DAMER 791, o r f r e q u e n t u s e r s who adapt t o t h e l i m i t a t i o n s [LEHMA

78, KRAUS 791.

More novice u s e r s a p p a r e n t l y g e t i n t o t r o u b l e i f

t h e i r knowledge of t h e d a t a b a s e i s l i m i t e d and i f t h e q u a l i t y of t h e o v e r a l l i n t e r f a c e (compare sectLon 2 ) does n o t match t h a t of t h e query language i t s e l f [TURNE 821.

With -proved

somewhat o p t i m i s t i c p r e f e r e n c e f o r r e s t r i c t e d

Systems o u r

natural

language

o v e r keyword Languages i n t h e upper r i g h t f i e l d w i l l become more realistic. formulation

For s k i l l e d u s e r s , n a t u r a l language of

some

queries,

bud

in

offers

general

a

keyword o r

mathematical language with i t s more powerful o p e r a t o r s preferable.

concise

will

be

The i n c l u s i o n of second g e n e r a t i o n languages i n t h e

lower r i g h t box i s due t o t h e i r r a p i d

reversable

actions

that

s u p p o r t e x p l o r a t o r y u s e of t h e d a t a b a s e [SHNEI 821.

W e have reviewed i n some d e t a i l t h e u s a b i l i t y

methods

for

summarizing

each the

user

results

type.

We

conclude

by

language

type.

this An

of

language s e c t i o n by

interesting

p a t t e r n can be observed h e r e .


Page 41

The p a t t e r n Section 2

of

query

language

development

around

the

lower

right

of

and

positional)

5, t h a t i s , around

Table

s k i l l e d o r p r o f e s s i o n a l u s e r s with d e t a i l e d d a t a b a s e Keyword

languages

have

more

general

languages which i n t u r n may be more task

in

can be observed i n t h e usage d i s t r i b u t i o n of methods.

Formal query languages (keyword, mathematical, center

outlined

structures

such

as

knowledge.

scope t h a n mathematical

efficient

for

specialized

a p p l i c a t i o n programming.

What t h e s e

languages have i n common i s t h e i d e a of f u l l s p e c i f i c a t i o n of an command o r a sequence of commands i n a command

operation

by

language.

N a t u r a l language can be t h o u g h t of a s a n e x t e n s i o n of

this

kind

a

of

(first

language t o be used by less

generation)

sophisticated users.

The o t h e r choosing

from

(technical) a

line

of

development

starts

with

v e r y l i m i t e d s e t of f u n c t i o n s prompted by t h e

system and t h e n g r a d u a l l y e n r i c h i n g

the

set

accomodate more s k i l l e d o r a m b i t i o u s u s e r s .

of

functions

to

I n a s c e n d i n g degree

of s o p h i s t i c a t i o n , t h i s group of methods Fncludes f u n c t i o n keys, line-by-line

prompting,

menus,

and

f i n a l l y second g e n e r a t i o n

languages.

From Table 5, it c a n be seen t h a t t h e h i g h e r l e v e l s of b o t h developments, language,

and,

sophisticated

second to menu

generation a

lesser

languages, r e s t r i c t e d n a t u r a l

degree,

selection,

keyword

overlap

in

languages their

and

usage.

Currently, t h e r e i s competition r a t h e r than cooperation, b u t t h e long-term t r e n d should b e towards i n t e g r a t i o n .


Page 4 2

CONCLUSIONS

6.

is

The taxonomy developed i n t h i s paper

based

on

a

new

i n t e r p r e t a t i o n of t h e development of d a t a b a s e query languages a s beLng i n f l u e n c e d by t h e a r e a s of programming languages, d a t a b a s e management,

and

human

factors

engineering.

This observation

l e a d s t o a two-level c l a s s i f i c a t i o n of query languages: user

senses

employed,

and

by

the

by

language methods.

the

It was

d e q o n s t r a t e d t h a t t h i s c l a s s i f i c a t i o n can s e r v e a s

a

e v a l u a t i n g query languages i n a s t r u c t u r e d manner.

In addition,

we developed a

comprehensive

classification

scheme

tool

of

for

query

language u s e r s from which most e x i s t i n g u s e r c a t e g o r i z a t i o n s c a n be derived.

The language and u s e r taxonomies t a k e n us

to

make

specific

recomendations

permitted

together

for

relating

language

methods t o u s e r t y p e s and a p p l i c a t i o n s .

Much remains t o be done. experiments

in

We

have

pointed

out

that

t h e f i e l d have been d i r e c t e d towards comparison

a t t h e g e n e r a l methods l e v e l , and t h a t experiments with language systems have n o t been c o n c l u s i v e .

be

natural

P s y c h o l o g i c a l models

of query f o r m u l a t i o n a r e o n l y i n t h e i n i t i a l s t a g e . to

few

There seems

l i t t l e r e s e a r c h on d a t a b a s e usage f o r c l e r i c a l u s e r s and

on t h e long-tern performance of s k i l l e d u s e r s . generation

languages

are

d i f f e r e n t i a t i o n of methods

in

within

too

early

this

Finally, a

group

stage to

be

second for

the

clearly

understandable.


Page 4 3

Each s i n g l e language t y p e w i l l have problems the

accoisunodating

v a r i e t y of u s e r t y p e s d i s c u s s e d i n t h i s paper.

We e n v i s i o n

f u t u r e query languages t o employ m u l t i p l e i n t e r a c t i o n o r d e r t o have a broader coverage and u s a b i l i t y . b e l f e v e t h a t new users

to

languages

customize

the

will

provide

interaction

to

in

I n a d d i t i o n , we

facilities their

modes

allowing

own needs and

preferences.


Page 44

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Austkn,

Texas,

[MYLOP 761 Mylopoulos, J., e t a l , "TORUS: A S t e p Towards B r i d g i n g t h e Gap Between Data Bases and t h e Casual User", I n f o r m a t i o n Systems, 2, (19761, 49-64. [NeSp 791 Neman, W.S., S p r o u l l , R.F., Computer Graphics", McGraw-Hill,

"Principles

of

Interactive

N e w York, ( 1 9 7 9 ) .

[NICKE 811 R.S.Nickerson, "Why I n t e r a c t k v e Computer Systems a r e Sometisnes not Used by People who mght Benefkt from Them", 1nt.J.Man-Machine S t u d i e s 15 119811, 469-483 [PLATH 761 Plath, W.J., "REQUEST: A N a t u r a l Language Question Answering System", IBM J. Res. Development, v o l . 20, ( 1 9 7 6 ) . [REISN 751 Reisner, P., Languages: 11975).

"Human F a c t o r s E v a l u a t i o n of Two Data Base Query 44, SQUARE and SEQUEL", Proceedings of NCC, Vol.

[REISN 771 R e i s n e r , P., " U s e of Psycholog3.eal E x p e r b e n t a t 2 o n as a n a i d t o Development of Query Language", IEEE T r a n s a c t i o n s of Software Engineerkng, SE-3, 3, ( 1 9 7 7 ) , 218-229 [REISN 811 P.Reksner, A Survey 13-32

"Human F a c t o r s S t u d i e s of Database Query Languages: and Assessment", ACM Computing Surveys 13 ( 1 9 8 1 ) ,

[SCHAU 761 Schauer,U., "Ein System unfagreicher Messdaten", S p r i n g e r , Berlkn, 11976).

zur

PnteraktWen Bearbektung and S p r u t h , (eds.),

Hesselmeir


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[SCHMI771 Schmidt, J . W . , "Some High-level Language C o n s t r u c t s f o r Data of Type R e l a t i o n " , Transacions on Database Systems, 2, 119771, pp.247-261. [SCHU821 Schmandt,C., Hulteen,E.A., "The I n t e l l i g e n t V o i c e - I n t e r a c t k v e Interface", p r o c e e d i n g s of Human f a c t o r s i n Computer Systems, G a i t h e r s b u r g , Md, ( 1 9 8 2 ) . [SENKO781 Senko, M.E., w i t h Lkght (1977).

"DIAM I1 w i t h FORAL LP: Making P o i n t e d Q u e r i e s Pen", Information Process2ng 77, North-Holland,

[SHIPM 81 ] Shipman, "The F u n c t i o n a l Data Model and t h e Data language DAPLEX"', ACM Transact2ons on Database Systems, 6 , 1 , ( 1 9 8 1 ) . [SHNEI 781 Shnekderman, B * , "Improving t h e Human F a c t o r Aspect o f Database I n t e r a c t k o n s " , ACM T r a n s a c t i o n s on Database Systems, 3, ( 1 9 7 8 ) . [SHNEI 801 B.Shneiderman,

"Software Psyckology8', Cambridge/Mass.,

(1980).

[SHNEI 821 B.Shnefderman, "The F u t u r e of I n t e r a c t k v e Systems and t h e Emergence of D i r e c t Manipulation", Proceedings of t h e NYU Symposium on U s e r I n t e r f a c e s " , New York, May, ( 1 9 8 2 ) . [SmWe 771 Small,D.W., and Weldon,L.J., "The E f f i c i e n c y of R e t r i e v i n g Information From Computers Using N a t u r a l and S t r u c t u r e d Query ~ a n g u a g e s " , Rep. SAI-78-6 55dWA, Science Applicat2ons, September, ( 1 9 7 7 ) . [STOHR821 E.A.Stohr, J.A.Turner, Y.Vassiliou, N.H.whLte, "Research kn N a t u r a l Language R e t r h e v a l Systems", 1 5 t h Ann.Hawai.2 I n t .Conf on System S c i e n c e s , Hawaki 1982

.

[STONE751 "The Deshgn and Implementation Stonebraker, M e I e t a l , 1, no. INGRES", ACM T r a n s a c t i o n on Database Systems, v o l . September, ( 1 9 7 6 ) .

of 3,

[StRo 771 Stonebraker, M.R., Rowe, L.A., "Observations on Data Manipulation Languages and T h e i r Embedding i n General Purpose Programming Languages", Proc. ACM I n t l . con£ Very Large Data Bases, ( 1 9 7 7 ) , 128-143.

.


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Research Yorktown

Base Management", on Very L a r g e Data

[TODD761 Todd, S.J.P., '*The P e t e r l e e R e l a t i o n a l T e s t V e h i c l e 0verv2eww, IBM Systems J o u r n a l , 1 5 , ( 1 9 7 6 ) . [TSICH 761 Tsichritzis, D.C. , "LSL: A Link and P r o c e e d i n g s o f t h e ACM SIGMOD, Washington,

Query

Selector 11976).

-

A

System

Language",

[TURNE821 Turner,J., Jarke,M., Stohr,T, Vassiliou,Y., and White,N., "Using R e s t r i c t e d N a t u r a l Language f o r Data R e t r i e v a l A Fzeld E v a l u a t 2 o n W , P r o c e e d i n g s on NYU Symposkum on U s e r I n t e r f a c e s , New York, May, ( 1 9 8 2 ) . +

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Page 52

[WOODS771 "Lunar Rocks i n N a t u r a l E n g l i s h : Explorations i n Woods, W.A., N a t u r a l Language Q u e s t i o n Answering1*, L i n g u i s t i c S t r u c t u r e s ProcessLng, Zampolli ( e d . ) , North-Holland, ( 1 9 7 7 ) . [WOODS 721 Woods, W.A., Kaplan, R.M., and Nash-Webber, B., "The Lunar S c i e n c e s N a t u r a l Language Informaion System", B o l t Beranek and Newman, Cambridge, Mass, J u n e , 11972). [YORMA 771 Yomark, Be, "The ANSI/X~/SPARC/SGDBMS A r c h i t e c t u r e " , The Ansi/Sparc DBMS Model, Jardine, (ed. ) , North-Holland, Amsterdam, (19771, 521. [ZLOOF 771 Zloof , M., "Query By Example: Systems J o u r n a l , 4, ( 1 9 7 7 ) .

A

Data

Base

Language",

IBM

[ZLOOF 781 Z l o o f , M., "Design A s p e c t s of t h e Query-by-Example Data Base Management Language", i n Databases: Improving U s a b i l i t y and Responshveness, Ben S h n e i d e m a n , ( e d . ) , ( 1 9 7 8 ) .


APPENDIX

grouping/sort ing report generation

u s u a l l y provided by h o s t language

PASCAL-R

T a b l e 1:

Examples f o r some t y p e s of d a t a b a s e l a n g u a g e s

EX PLANAT ION

A s e l f - c o n t a i n e d language p r o v i d e s a l l t h e n e c e s s a r y c a p a b i l i t i e s f o r performing d a t a b a s e i n t e r a c t i o n s . On t h e o t h e r hand, t h e s y n t a c t i c forms of a q u e r y language can b e enbedded i n a p r o g r a m i n g language l i k e , PC/I, COBOL, o r PASCAL. There a r e f o u r t e c h n i q u e s f o r embedding (LaPi 8 0 ) : s u b r o u t i n e c a l l s ( D L / I , TOTAL-IQ), s i m p l e e x t e n s i o n (COBOL/DML), nonp r o c e d u r a l o p e r a t o r s (C/QUEL, APL/EDBS) , and i n t e g r a t e d (PASCAL-R) Same q u e r y languages a r e r e t r i e v a l - o n l y ; t h i s i s t y p i c a l o f r e s t r i c t e d n a t u r a l language systems. More commonly, u p d a t e c a p a b i l i t i e s a r e p r o v i d e d . Data a d m i n i s t r a t i o n i n c l u d e s t h e a b i l i t y t o c r e a t e and modify d a t a b a s e d e s c r i p t i o n s , d e f i n e i n t e g r i t y c o n s t r a i n t s and impose a c c e s s c o n t r o l . More language examples a r e g i v e n i n T a b l e 7 .

.


QUERY LANGUAGES

...................................................... LANGUAGE

DB MODEL

DB SYSTEM

METHOD

d-------------

TYPE

REFERENCE

--------------

--d----------------------------------------------------------

ADACOM ADASCRIPT ALPHA ASI/INQUIRY CONDOR CUPID DAPLEX DATA DISPLAY DEDUCE DRUID EQBE EUF I D FOKAL5P GENIE G IS GPLAN HAMEST IDSQ ILL IMMEDIATE INTELLECT I SBL I(ZF LADDER L INUS LSL LUNAR MODEL 204 NATURAL

h y b r kd hybrid relational hierarch2cal natural relational hybrid network relational network relational network hybrid network hierarchical network network hybrid relational hierarchical natural relational hierarchical natural relational network natural network hybrrd

NOMAD

NUL PLANES/JETS PASCAL-R QBE QBPE QLp QUEL QUERY RAMIS RENDEZVOUS REQUEST SWRDLU SQL SQUARE TQA/REQUEST TORUS TOTAL-IQ UDL USL

network natural relational relational relational network relational hybrid natural network natural relational relational natural natural network hybrid natural

ADABAS ADABAS

-

INS

INGRES INGKES IDMS

-

IDMS IDAMS special DLAWII IDMS IMS special SEED IDS

-

SYS-2000 ADABAS PRTV 1MS IDA/FAM

MRDS LSL special MODEL 204 ADABAS NOMAD

.

ALPHA/

PASCAL-R QBE

-

DMS/I 100 INGRES INRGE special TOTAL special SYSTEN R

-

speckal MINIZ TOTAL

-

SYSTEM R

keyword keyword keyword keyword natural pictorial keyword keyword keyword keyword f ill- i n natural pictorkal keyword keyword keyword keyword keyword keyword keyword natural mathm. keyword natural keyword keyword natural keyword keyword keyword keyword natural mathem. fill-in p2ctorkdl keyword keyword keyword keyword natural keyword keyword keyword posit. natural natural keyword keyword natural

navigation navi g a t i o n calculus non-proc. linguistic

-

.

non-proc navigation calculus navi g a ti o n non-proc

.

A1

-

[GMD 753 [GMD 751 [CODD 71,727 [ IBM 7 51 EBANER 771 [McDON 751 [SHIPM 811 [IDMS 771 [CHANG 761 [IDMS 771 [SCHAU 761 [KAMEN 781 [SENKO 781 [IDMS 771 f IBM 751 [HASEM 775 [IDBS 791 [VONGO 741 [ L a P i 751 [MRI 731 [AIC 821 [TODD 761

navigation navigation navigation navigation navigation non-proc. non-proc. linguistic algebra non-proc

~ I B M xx]

A1

[HENDR 781

.

calculus navigation A1

navigation navigati.on non-proc navigation 41 calculus calculus

.

-

non-prqccalculus non-proe non-proc.

.

A1

navigatkon A1

mappkng mapping lingukstkc A1

.

non-proc non-proc. linguisth

[TSICH [WOODS [CCA [GMD

761 72,771 773 751

[DeHe

761 781 771 771 791

[WALTZ [SCHMI [ZLOOF [ChFu [BENNE [STONE

xxj

751

[CODD 74,781 [CINCO 781 [WINOG 711 [ASTRA 761 [BOYCE 751 [PLATH 761 [MYLOP 761 [CINCO 781 [DATE 801 [LEHMA 77,781
