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Final Report
January
1982
DATABASE MANAGEMENT FEASIBILITY
(U)
Prepared
for:
DEFENSE INTELLIGENCE AGENCY
WASHINGTON,
D.C.
20301
Attention:
SGI J
CONTRACT M DA903-8 1 -C-0292
SPECIAL ACCESS PROGRAM FOR GRILL FLAME.
RESTRICT DISSEMINATION TO ONLY INDIVIDUALS WITH VERIFIED ACCESS.
333
Ravenswood Avenue
Menlo
Park,
California
94025
U.S.A.
(415)
326-6200
Cable:
SRI
INTL MPK
TWX:
910-373-2046
^International
fp^bved For Release 2000/08/07 :€©M>Fd£bEA4I)lA4o270001 -9
d For Release 2000/08/07 :€©WFe|GDIfMiMA<l027OOO1-9
Final Report
January
1982
Covering the period October
1980 to September
1981
DATABASE MANAGEMENT FEASIBILITY
(U)
By:
EDWIN
C. MAY
Prepared
for:
DEFENSE INTELLIGENCE AGENCY
Contract
No: MDA903-81 -C-0292
WASHINGTON,
D.C.
20301
Approved For Releaseg^WPID
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CONTENTS
LIST OF TABLES
iii
I
OBJECTIVE
II
INTRODUCTION
III
DISCUSSION
IV
CONCLUSIONS
V
RECOMMENDATIONS
ii
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TABLES
Resource Assessment Summary
Training Target Data
.
.
.
iii
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I
OBJECTIVE
The objective
of
this program is
to develop concepts and materials
to determine
if remote viewing data
can be placed
on
a computerized data-
base-management
system for each access
and manipulation*
#'
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II
INTRODUCTION
The manipulation of textual data was among the earliest applications
of digital computers.
From these earlier uses,
it was immediately apparent
that
two separate requirements should be imposed on data-base management
(DBM)
designers:
.
Develop task specific DBM programs.
•
Develop generalized DBM programs
that allow any
specific application to be designed at
a
later time
by the end-user.
The first requirement was easily met.
An abundance of
data-base management
systems
(DBMS)
for specific tasks exist
that
handle everything from general
accounting
for business to map generation by graphic DBM.
The second
requirement, however,
has not
yet been adequately realized.
Although
many computer vendors offer generalized DBM design programs, they all
appear to be of
limited use when applied to a specific
set
of
design
requirements.
The problem of creating
a DBM design program is
not trivial;
to be useful to the widest possible audience,
it must
be very general.
Yet,
this very generality makes
the final DBM cumbersome
to use.
This report describes
test applications
of
a commercial DBMS
to remote
viewing
(RV)
data and recommends
a threefold approach to the general problem
of RV DBM.
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III
DISCUSSION
*
In the Grill Flame mid-year report,
we demonstrated the use of
a
SGI
commercially available data-base management
(DBM) program applied to two
'~J
problems in RV data management.
The first
of these was
the categorization
and display
of
the results
of
a simulated RV analysis
data
base.
Using
the tentative assessment
form,
which operating RV analysts had suggested,
LUWO
we analyzed
RVs each for
4 remote viewers.
Table
1 shows
a character-
istic output from this data
base, which is repeated here from
The
column headings are the seven categories taken from the assessment
form.
Under each category the remote viewers are listed in ascending
order of assessment averaged over all viewings to date for that
category.
For example, we note
that remote viewer
007 was
least successful at
obtaining information about the geography of
a site.
However, when every-
thing
is
considered, remote viewer
007 had
the best
overall utility.
This
and similar information might have been overlooked with manual inspection.
VAU
The row below the dashed
lines
contains
the averages for each column, which
y
can be considered as
the "facility" assessment for each category.
For
example,
the represented facility does
best on geography elements and
second best when targeted against activity at the remote site.
In a second example, we have used
a DBMS to organize and manage
a
growing
number
of training targets
from the National Geographic
(375 as
of this
report).
Our RV enhancement
effort
currently involves four
remote viewers,
six interviewers,
four target preparers, and numerous
target selection criteria.
With this
level
of
complexity and a growing
gQU
"DoD GRILL FLAME Progress
Report
(U)," presented at Mid-Year
GF Meeting at DIA on 30 April
1981
(April
1981,
SECRET).
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V
%
V
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Table
RESOURCE ASSESSMENT SUMMARY
(23 Apr
1981)
Geography
Elements
LS
Elements
SS
Ambience
Activity
Personnel
Utility
ID
Ave
. ID
Ave
. ID
Ave
ID
Ave
ID
Ave
, ID
Ave
ID
Ave
007
1.39
712
1.15
007
0.71
712
0.95
712
1.14
007
0.53
712
0.55
126
1.44
126
1.33
712
0.73
126
1.50
126
1.62
531
1.21
531
1.38
531
1.59
531
1.57
531
1.31
531
1.75
531
1.75
712
1.56
126
1.55
712
2.63
007
2.09
126
1.56
007
S
1.81
007
1.86
126
2.00
007
2.63
*
*
*
*
*
*
*
1.76
1.53
1.08
1.50
1.59
1.32
1.53
*
Average of each column.
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number
of targets,
a DBMS was mandatory to avoid duplication and to provide
target statistics.
As
an example
of
the DBMS output,
Table
shows
a small portion of
the existing data.
The targets were selected solely on the basis
of their
use
as
calibrations
for operational RV sessions.
They are displayed
chronologically as
a demonstration of
a sorting procedure.
Both of
the above DBM applications were
done on
a
large-scale
PRIME 750
computer using the PRIME Corporation's
POWER+ packaged DBMS,
In spite
of
the
computing power
of
the PRIME 750 and generality
of POWER+,
four
specific problems were identified:
This
DBMS:
(1)
Did not allow
for the formation of specific data
records
that
contained parts
of separate records
from the remaining data base,
(2)
Did not easily allow
a change of
data base.
(3)
Did not allow
for tree structures.
(4)
Can be installed on the
SRI
International's
PRIME
400 at
a
cost
of $75,000 to $125,000.
Table
is
an example
of the first problem described above.
The
simulated
data base was entered and stored by grouping together all the parameters
I
from the analysis
of
a single remote viewer
for
a single operational
f
’
,
session.
Yet,
to provide the summary information in Table
1, we must
uO
collect scores
and
IDs
from across many sessions.
In fact,
Table
1 was
manually constructed to demonstrate
a
concept
and was beyond the
capability
of
P0WER+,
The second problem applies
to both DBM examples.
In developing the
designs
of
the respective
data
bases,
it was necessary to modify them in
n
progress
to assure an optimum configuration.
P0WER+ requires
that all the
data
be reentered into the new design.
Although P0WER+
has
a file
conver-
sion capability that
makes possible reentry of
data from
a disc,
it was
cumbersome;
therefore,
we decided to reenter the data manually.
w
ft
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Table
TRAINING TARGET DATA
(23 April
1981)
Date
Time
Latitude
Longitude
Target Location
Monitor
Class
Preparer
15 Feb 1980
1021
42° 34
’
08° 44
' E
Calvi,
Corsica
Puthof
C
Unknown
3 Mar 1980
0910
11° 26
' S
53° 04
f W
Campo de Diauarum,
Brazil
Puthoff
B
Unknown
3 Mar 1980
0917
14° 00
r N
121° 00’
Lake Taal-Luzon,
Phillipines
Puthoff
B
Unknown
3 Mar 1980
1000
12°30
' N
7 0° 00
1 W
Aruba
Island, Lesser Antilles
Puthoff
C
Unknown
Jul
1980
0900
21°38 *N
157° 04
T W
Oahu,
Hawaii
0^4
C
Unknown
Jul
1980
0952
31°30
f N
35° 30* E
Dead Sea,
Israel/Jordon
0\jTJ
c
Unknown
2 Oct
1980
0820
18° 29
T N
66° 08*W
San Juan,
Puerto Rico
Puthoff
c
Puthoff
2 Oct
1980
0900
58° 12
'
06° 23 'W
Stornoway Lewis
Is.,
Scotland
Puthoff
c
Unknown
2 Apr 1981
0905
34° 40
* S
58? 30
f W
Buenos Aires, Argentina
Puthoff
c
Harary
2 Apr
1981
0945
45° 3 0
' S
1 65° 3 0 * E
Dusky Sound,
New Zealand
Puthoff
B
Harary
3 Apr 1981
0807
22°30* N
88° 2 O’ E
Calcutta, West Bengal- India
c
Harary
3 Apr
1981
0815
51° 13 *N
04° 25
1 E
Antwerp,
Belgium
C
Harary
3 Apr
1981
0840
4 1° 02
' N
28° 57
* E
Istanbul,
Turkey
SG1J
c
Harary
3 Apr
1981
0920
39° 44 * N
44° 23
1 E
Mt. Ararat, Turkey
B
Harary
3 Apr 1981
1010
35° 09
1 N
32° 47 ’E
Vouni
,
Cyprus
B
Harary
3 Apr
1981
1015
41° 50'
71° 28* W
Providence,
Rhode
Island
c
Harary
6 Apr 1981
0817
00? 1 4
* S
78°30'W
Quito, Ecuador
Puthoff
c
Harary
6 Apr
1981
0824
39° 18
’
7€?38’W
Baltimore, Maryland
Puthoff
B
Harary
6 Apr
1981
0827
36? 36' N
83° 40 ’W
Cumberland Gap, Kentucky-Tennessee-Virginia
Puthoff
B
Harary
6 Apr
1981
0835
00° 19
’ N
32° 35
’ E
Ka mpa la ,
Uga nda
Puthoff
B
Harary
6 Apr
1981
0845
37° 37
'
79° 33
f W
Natural
Bridge, Virginia
Puthoff
B
Harary
6 Apr 1981
0930
13° 32
'
710 57’W
Cuzco,
Peru
Puthoff
B
Swann
6 Apr
1981
0936
28° 59
1 N
13° 40 'W
Montana del Fuego, Lanzarote Canary
Island
Puthoff
B
Swann
6 Apr
1981
0945
51°29
' N
00?38'W
Windsor Castle, Windsor England
Puthoff
B
Swann
7 Apr
1981
0940
29° 25
' N
98° 30 'W
San Antonio,
Texas
Puthoff
B
Harary
8 Apr 1981
0836
20? 19
r N
103° 10*
Chapala Lake, Mexico
Puthoff
B
Swann
8 Apr
1981
0956
33° 39
r S
78° 58 *W
Robinson Crusoe
Is.,
Juan Fernandez
Island
Puthoff
B
Unknown
8 Apr 1981
1116
51°51
f N
01° 21
f W
Blenheim Palace, Oxon England
Puthoff
B
Swann
8 Apr
1981
1119
60?00’N
152° 00 'W
Cook
Inlet
, Alaska
Puthoff
B
Swann
9 Apr 1981
0845
03° 02
’ S
37° 20
f E
Mt.
Kilimanjaro, Tanzania
Puthoff
c
^Humphrey
9 Apr
1981
0923
38° 22
1 N
1 1 0° 2
f W
Canyonlands
Park,
Utah
Puthoff
B
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The third problem arises
in a training evaluation environment.
The
target management
data shown in Table
2 displays only a small portion of
the data that
is available for each of
the targets.
Each target
is
classified as
to the principal type of target with regard
to large-scale
geographical features
(e.g.;
a body of water, an island,
or a mountain).
For purposes
of evaluation,
it
is necessary to know details
of each of
these major features.
For example,
one may want
to determine how many
targets had "muddy streams"
as
the particular form of
"water."
POWER+
was
incapable of providing this
capability.
Thus,
only a coarse target
classification was
possible.
A "tree-structured" data base
is one of the
easiest solutions
for this
problem.
A properly designed tree structure
allows
for easy modification and simple implementation of
complex searches
such as
the one described above.
It
is
not
that tree-structured data-base systems
do not exist.
Rather,
they tend to
be
large
(require
large main-frame memories)
and
require
fast processors.
Typically,
these
data bases include a
large
number of features
that are not
required in our application and unneces-
sarily burden the speed/memory requirement
of the system.
The deficiencies
described here are not unique
to POWER+ .
Each
commercially available DBMS will have similar problems with regard to
our application.
However,
there are portions
of our application that may
have reduced requirements
and can be solved with simple data-base manage-
ment
systems.
SO
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IV
CONCLUSIONS
Depending upon the exact data-base design criteria,
commercially
available DBMS may possibly be applied to RV data and target management
on a
limited basis.
Such systems are available for
a
combined hardware/
software
cost
of approximately $5,000.
These systems have the added
advantage of being "desk-top" size and are
single user so that
the entire
system may be maintained within a secure environment.
If we consider the security requirement
of the general GRILL FLAME
program and budget
constraints ,, we conclude that:
5MOTE
•
Full
data-base management
of RV data
is possible,
<-
but
must
be developed in house.
•
A complete DBMS must
be self-contained,
flexible,
and operate
as
a single-user on a micro-mini-computer.
U>4W
PfV/
ft
@ much $ pera/ hr.
TO DO
THIS
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