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20 November 1980
A DATA-BASE MANAGEMENT SYSTEM
FOR OPERATIONAL REMOTE VIEWING (S)
Prepared by:
E. C. May, Ph.D.
B. S. Humphrey
Radio Physics Laboratory
CLASSIFIED BY :
Msg, HQDA (DAMI-ISH)
dated 7 July 1978
REVIEW ON: 7 July 1998
SRI 0-4472
This document consists
of 24 pages.
Copy No.
1
SRI
International
333 Ravenswood Ave. . Menlo Park, California 94025
(415) 326-6200 · Cable: SRI INTL MPK . TWX: 910-373-1246
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I
OBJECTIVE
In this document we propose the application of a computer data base
management system (DBMS) (with associated operational RV assessment forms)
to the organization of the client's RV data, including trend analysis through
multi-variable DBMS manipulation of the data.
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INTRODUCTION
A.
Background
As operational remote sensing by psychoenergetic means evolves from
the demonstration phase toward full status as a recognized intelligence
collection technique, it is necessary to develop an overall accurate
assessment of the large amount of data collected to date, and to be able
to recognize significant trends within that data.
In addition, as the
data base continues to expand, a convenient archival technique with rapid
access to the data is mandatory.
It is possible to ascertain interesting trends by casual examination
of the raw data transcripts. However, this type of informal inspection
does not easily provide the detailed, multi-variable analysis by which to
optimize further collection assignments, and it may lead to underutiliza-
tion of RV'er resources. A mission officer could in principle increase
contribution in the operational environment on the basis of correlation
revealed by detailed DBMs analysis of previous results.
A data base management system provides at least three major advan-
tages over manual inspection. DBMS
1. indicates optimal use of multiple RV'ers for specific
operational targets of interest,
2.
efficiently archives and cross-correlates rapidly
increasing volumes of RV data, and
3.
provides means for recognizing and implementing more
subtle targeting strategies for individual RV'ers.
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Appendix A contains the introductory comments of one such DBMS as an
illustration.
B.
Proposal
We propose to select a standard data base management system (DBMS)
which optimally meets the client's requirements, and to construct RV data
assessment sheets to simplify data reduction. We further propose to create
a data base from existing data, and to initiate a multi-variable search
for important trends.
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III
METHOD OF APPROACH
It is important to note here that the technology of data base
management systems (DBMS) is finely developed. The required computer
codes already exist; it is necessary only to select that system which is
most tailored for application to the client's needs.
Once a DBMS has been selected, we will modify and expand the tenta-
tive prototype RV assessment sheet (shown in Appendix B) so that it con-
forms to the constraints of the DBMS and accommodates the specific needs
of the client organization supplying the data. It is presently envisioned
that a number of assessment sheets would be developed and tailored to the
type of facility targeted for the session under consideration. The follow-
ing is a tentative list of possible operational remote sensing target
assessment categories.
SG1A
We propose to work with the client organization to provide instruc-
tions and guidance to reduce the current data for entry into the DBMS.
We would then create the data base using the DBMS itself, working closely
with the client to initiate trend searches.
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IV
PROPOSED PROGRAM
We propose the following:
· Select an appropriate DBMS.
· Construct a series of task-related assessment sheets.
. Build a data base from contractor and client-completed
assessment sheets.
. Initiate trend analysis and produce computer-generated
reports describing the results.
. Provide access to the data base by the client organi-
zation and recommendations for an in-house DBMS
capability.
It is proposed that the above program be completed on a one-man
year level-of-effort basis. We envision a single year's expenditure of
approximately $75K. An itemized cost breakdown will be provided on
request.
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.
Appendix A
INTRODUCTORY CHAPTER OF THE PRIME 400 DBMS
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SECTION 1
INTRODUCTION
INTRODUCTION
PRIME/POWER is a complete data management system combining the features
of Prime's operating system (PRIMOS) with the simplicity of a
high-level, user-oriented query and report language. With PRIME/POWER,
anyone can quickly learn on-line data management at an interactive
terminal. It is not necessary to know anything about programming or
data processing to use PRIME/POWER.
The POWER language is based on simple, easy-to-understand English
commands. Using interactive dialog in all its operations, POWER
prompts (asks) you for the input it needs to perform each function. If
you give it the wrong information, POWER displays an error message
describing the problem.
POWER's HELP command provides
a
brief
description of the function and format of any POWER command.
PRIME/POWER and PRIME/POWER+
POWER has two versions:
PRIME/POWER and PRIME/POWER+. PRIME/POWER
runs on all Prime CPUs, from the PRIME 350 on up through the 750.
It
provides the basic query language, report writer, data entry and
maintenance functions required for simple data management.
PRIME/POWER+ expands these capabilities by providing the end user with
the tools for system development. The additional features include
formatted data entry, validation of data entry, text and keyword
processing, table processing, a dictionary file for keywords,
sophisticated report features, procedure files with variables, file
linking, multi-file reporting, concurrent usage safeguards, and a
versatile EDITOR facility. PRIME/POWER+ runs only in V-mode on a 350
CPU and up.
Common Features
PRIME/POWER and PRIME/POWER+ use PRIMOS file utilities to create,
interrogate and update all types of standard data files. These file
types are: MIDAS (index sequential) , binary sequential, binary direct
access and ASCII sequential. Files created outside the POWER system
can be easily overlaid, or mode compatible with POWER. Such files can
then be interrogated and updated like any POWER-created file.
Since PRIME/POWER and PRIME/POWER+ are self-contained,
all data
management operations can be performed entirely within the POWER
system. In addition, all files created or overlaid by POWER are
accessible by applications programs written in COBOL, FORTRAN, PL/1,
RPGII and BASIC. Similarly, files created by such programs can be
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overlaid and interrogated with POWER.
Features of PRIME/POWER and PRIME/POWER+
The common features of PRIME/POWER and PRIME/POWER+ include:
.
. Easy-to-use interactive language.
· Up to 20 user-defined direct access keys.
. Support for complex
£
search
expressions,
including
range
evaluation.
. Automatic data length check during data entry.
. Interface to all standard file types: Index Sequential (MIDAS) ,
ASCII sequential, binary sequential and binary direct access
files.
. Simple creation of all standard file types.
. POWER-created files accessible by applications programs (COBOL,
BASIC, FORTRAN, etc.) .
· Simple data update capabilities.
. Basic report-writing features.
. Extensive computational functions.
. Support for all standard data types, including COBOL COMP-3 and
DECIMAL.
. Procedure files to perform routine or repeated operations.
. Automatic retention of CREATE and ADD dialogues for easy
procedure file creation.
. Password-oriented security system.
Features exclusive to POWER+
. Ability to define and search on keywords.
. Text processing and editing.
. Support for tables in files and reports.
. File-locks to prevent simultaneous file modification.
. Dynamic and static file linking.
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· Range checking for data input.
· Computed fields and linked files in reports.
. Support for different terminal features.
. Screen formatting for simplified data entry.
. An EDITOR facility for text, keywords, and procedure files.
. System-level audit and accounting facilities.
1
INTRODUCTION TO DATA MANAGEMENT
'Data management' is a widely used term which
refers to the
organization and upkeep of large quantities of information. This can
be a difficult task; however, a simple approach often yields the best
results.
£
The POWER system is designed to make data management as
simple and painless as possible.
If you have never used a data
management system or language before, the summary below should help put
some terms and concepts into perspective.
Data Management: The Basic Concepts
Data management involves five basic operations:
1. Organizing and storing information (data).
2.
Retrieving and optionally reporting on specific data items.
3. Updating information in a file.
4. Adding new data to a file.
5.
Deleting data from a file.
These data management operations are based on several general concepts:
. Information, or data, can be stored and accessed most efficiently
using computer facilities. ('Data' refers to two or more 'pieces'
of information, while 'datum' refers to a single piece
of
information.)
. Similar information is grouped into
files;
e.g.,
all data
pertaining to a company's employees may be put into an Employee
file.
. Files are composed of records; for example, each record in an
employee file might contain several pieces of information pertaining
to a single employee. See Figure 1-1.
. Each record in a file is usually divided into one or more fields
each of which contains a singular piece of information. An Employee
file record might contain fields like last name, first name, social
security number, date of hire, etc.
These fields are common to
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FIELDS
FIELD NUMBER
FIELD NAME
FIELD 1
FIELD 2
FIELD 3
FIELD 4
FIELD
LAST NAME
FIRST NAME
SOC. SEC. NO.
BIRTH DATE
RECORD 1
Jones
Steve
323-40-5940
2 DEC 53
RECORD 2
Harris
Mike
100-07-4091
23 MAY 49
RECORD 3
Umlasky
Becky
231-57-5921
25 MAY 52
RECORD &
Figure 1-1. Employee File Records
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every record in the file.
. Each field within a record is given a name which accurately
describes the information it contains. Such field-names are
referred to as descriptors or keys. Ordinarily, one retrieves
certain pieces of information from a file by specifying the search
conditions, fields or keys must meet in order to be retrieved. Only
those field values which satisfy the stated search conditions are
retrieved from the file during a search.
Data Management: The Basic Operations
What can be done with information once it is organized in files?
Some
of the possibilities are:
(
. Retrieve certain information from the file.
· Examine data.
. Perform arithmetic operations on the data.
· Change or update the data.
· Delete specific data items.
. Obtain a paper copy of the data (i.e., print it out) .
. Format the data, and print it out in a 'report' format.
. Add new data to the file.
POWER TERMS AND CONCEPTS
Most of the terms used in POWER are very similar to those just
discussed. There are a few modifications:
. In POWER, fields are named by descriptors.
. There are two types of descriptors:
search and display.
Search descriptors name fields which will be used as keys and
will be frequently searched on. Display descriptors usually
describe fields which are less frequently searched on.
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Terms
)
In addition to those defined above, the POWER vocabulary includes the
following terms:
.
File
A collection of related information divided into common records.
Each file has a unique set of descriptors or fields associated
with it. For example, a file containing payroll information might
contain one record per company employee. Each record is composed
of several fields or descriptors, e.g., NAME, SALARY, AGE, etc.
· Data Base
A group of interrelated files.
· Record
A block of related data composed of one or more fields named by
descriptors. A file is made up of one or more records.
· Descriptor
A field that is common to all records in a file. Descriptors are
defined when the file is created. For example, in a Personnel
file, there may be several descriptors such as NAME, ADDRESS,
PHONE, etc.
. Search Descriptor
A descriptor that is used to retrieve a selected record or
records. This descriptor can be used with the FIND, GET, PRINT or
DISPLAY commands. Search descriptors can be up to 32 characters
in length. (In a MIDAS file, each search descriptor is an index
and is part of the index subfile.)
. Display Descriptor
A descriptor that is used in a selected display or print of a
record. These descriptors are used to sequentially search a file
for information. Display descriptors can be a maximum of 80
characters in length. (In a MIDAS file they are not physically
part of the index subfile, they are non-indexed fields.)
· Text (POWER+)
A free-form portion of a record that may contain up to 50 lines of
data. Each line can be up to 80 characters in length.
.
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·
Set
A group of records fulfilling any stated search requirement.
A
set is created as a result of a successful FIND, GET, or EXPAND
command. For example, a FIND command may search using NAME IS
'MITH' as the criteria. All records within the selected file
whose NAME field contained 'SMITH' would form a set. Up to 49
sets can be active at one time per user.
.
· Current Set
The last set created by a successful
search operation, such as
FIND, GET, or EXPAND.
· Keyword (POWER+)
A word or phrase that is contained within a record or which
appropriately describes a concept within a record; can be used as
a search criterion. Keywords can be up to 20 characters in
length.
(Keywords are stored in indices 15-17 in a MIDAS file) .
. Internal Keyword (POWER+)
A keyword actually contained in the TEXT portion of a file.
Keywords are defined by bracketing them, <like so>, as text is
added to each record.
. External Keyword (POWER+)
A keyword that is not contained within the text of a record.
External keywords are logical search keys that describe or relate
to the information contained in a particular record.
External
keywords are added to a record after the text has been entered.
Data Management in POWER
POWER offers all the basic tools needed for data organization and
management. With POWER you can:
. Create a file with up to 20 keys (search descriptors)
retrieving information.
for
. Take an already existing file and define it according to POWER
terms; called 'overlay'.
. Retrieve and display information
from
the
file,
using
previously defined descriptors as search keys.
· Compute and update numeric data.
. Change fields in selected records or change file globally.
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. Write simple command sequences (procedures)
per formed repeatedly.
that
can
be
· Write reports to format data output.
· Delete data from a file.
. Add new records to a file.
-
Files Created by POWER
Most users of POWER will not need to worry about file types and
structures;
POWER takes care of file-related details for you.
However, some users will need to know about the files POWER creates.
The most commonly encountered files in the POWER system are called
MIDAS, (Multiple Index Data Access Systems) files.
MIDAS files: MIDAS files are special data files structured for quick
data retrieval.
POWER can access these files using a 'direct'
retrieval method.
Each MIDAS file has an associated index subfile, which serves as a
quick
look-up file (much like a phone book). All the search
descriptors you've defined for the file are listed in the subfile along
with their 'address' locations in the file. When you specify a
descriptor to be searched on during a file query, POWER goes to the
index subfile, looks up the descriptor and its address, goes to the
data file and retrieves the proper records. This kind of search can be
called the index access method.
Other files:
Files of other types, such as ASCII sequential, may be
created or overlaid in POWER.
Sequential files are set up quite
differently from MIDAS files. There is no index subfile for sequential
files;
therefore, all descriptor values must be searched
for
sequentially in the file instead of directly.
Sequential searching involves stepping through every record in the
file, one after the other, in the order in which they are physically
located in the file, until the desired one is found. When a descriptor
is specified in a search expression, POWER goes directly to the file
and searches every record until the proper descriptor (key) value is
located. The sequential access method can take a lot more time than
the index access method, especially if the file contains many records.
Display Descriptors vs. Search Descriptors
-
In MIDAS files, a descriptor defined as a display descriptor does not
appear in the index subfile. When you search on a display descriptor,
POWER must do a sequential search through the actual MIDAS file until
the desired field value for the descriptor is found. In other words,
for MIDAS files, search descriptors are accessed by the index access
method; display descriptors, by the sequential access method.
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In sequential files, display descriptors are accessed sequentially,
just as search descriptors are; however, they are usually reserved for
fields not often searched on. The reasons for having both search and
display descriptors are simple:
. You can define only 20 search descriptors per file (only 14 if
you select the TEXT and KEYWORD option in POWER+); if you want
more keys to search on, they must be defined as display
descriptors.
. Search descriptors have a maximum length of 32 characters;
Display descriptors have a maximum length of 80 characters.
. Display descriptors are usually the fields you won't search on
frequently.
-
. In both POWER and POWER+, having display descriptors enables
you to define up to 512 fields per record, instead of just 20.
CONVENTIONS
Throughout this manual, many symbols and conventions are used in
describing command formats and syntax. There are also some special
rules for defining descriptor names and file names in POWER.
These
conventions are listed below.
Command Syntax Rules
All POWER command formats are governed by the following syntax rules:
. WORDS-IN-UPPER-CASE
Capital letters identify command words or keywords. They are to be
entered literally. If a portion of an upper-case word is underlined,
the underlined letters indicate the minimum legal abbreviation.
. Words-in-lower-case
Lower case letters identify parameters. The user substitutes an
appropriate numerical or text value.
· Braces { }
Braces indicate a choice of parameters and/or keywords. At least one
choice must be selected.
· Brackets [ ]
(
Brackets indicate that the word or parameter enclosed is optional.
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· Hyphen -
A hyphen identifies a command line option, as in: SPOOL -LIST
· Parentheses ( )
When parentheses appear in a command format, they must be included
literally.
· Ellipsis ...
The preceding parameter may be repeated.
· option
The word option indicates one or more keywords or parameters can be
given, and that a list of options for the particular command follows.
Command Format
The general format of many POWER commands is given below. Commands are
im uppercase:
lowercase words are 'arguments', or 'parameters'.
Arguments are usually optional on a command line and can be any one of
several values, depending on the context in which the command is being
used.
(variable
COMMAND [Snn] { descriptor-name
-
KW
-
'value'
variable j
Snn
Set number where nn is a number from 1 to 49.
descriptor-name
A specific descriptor name used in
search and display commands.
various
KW
Indicates that a keyword value is to be searched
on or displayed.
'value'
Actual record
value
corresponding
to
the
descriptor,
variable or
keyword
named
previously. Must be enclosed in single quotes.
variable
A numeric or character variable used in search
or computation expressions.
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INTRODUCTION
:
Some POWER commands accept one or more options from a list. These are
represented as follows :
COMMAND
option-1
option-2
option-n
If more than one option is specified on a command line, they are
separated by commas or spaces, as indicated in each individual command
format.
Special Characters
Several characters reserved for special uses by POWER cannot be
included in descriptor names or file names. These special characters
are:
· period
, Comma
( left parenthesis
) right parenthesis
/ slash
* asterisk
+ plus
- minus
= equal
< greater than
< less than
' single quote
The only characters listed above which can be used in defining file
names are: period (.) and minus (-).
.
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Appendix B
A TENTATIVE RV ASSESSMENT SHEET
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(S
INSTRUCTIONS TO ANALYSTS (U)
(U) The information provided as enclosure to this report was obtained in
response to a collection requirement provided by
This information was acquired from a new and potentially valuable source of
intelligence. Work is currently being pursued to determine the accuracy,
reliability, and improvement potential of this source. Your remarks and
attention to the evaluation sheet will be the basis for our assessment of this
new collection technique. Therefore, the effort you expend will greatly assist
us and will ultimately result in you receiving more data of increasing accuracy
and reliability.
(U)
While formulating your judgements concerning the data, the following
comments concerning this new source of intelligence may be helpful.
(U) Foremost, the data is likely to consist of a mixture of correct and
incorrect elements. Specifically:
(1) (S) The descriptive elements are generally of higher
reliability than judgements or labels as to what is
being described (recreational swimming pool may be
mistaken for water purification pools, an aircraft
hull may be mistaken for a submarine hull, etc.).
Therefore, seemingly appropriate descriptive elements
should not be rejected because of mislabeling.
(2)
(S) The data often contain gaps (in a 3-building complex,
for example, perhaps only two of the buildings may be
described, and an airfield may be added that isn't there).
Such gaps or additions should not be taken to mean that the
rest of the data is necessarily inaccurate.
(S) Therefore, a recommended approach is to first examine the entire
information packet to obtain an overall "flavor" of the response, reserving
final judgement even in the face of certain errors, and then go back through
for detailed analysis.
(U) If you have questions regarding the data you have received or on its
evaluation please feel free to contact me at any time. Thank you.
SG1J
SRI 0-4410
This document consists
of 5 pages.
Copy No.
3
Classified by: DIA-DT
Review on: 3 Nov 2000
C/O L. Lavelle - Bldg. 44
SRI International
Menlo Park, CA 94025
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PSYCHOENERGETICS PROGRAM
OPERATIONAL TARGET FILE
(SRI Internal Use Only)
(U) Project Name
(S) Viewer
(S)
Monitor
(S) Date
Time of Start
Time of Finish
(S) Client
(S) Priority
Urgent
Routine
(U) Target Key
( ) Variance from Standard Protocol
(U) Target ID No.
( ) Information Provided by Requestor
( )
Information Provided to the Monitor
( )
Information Provided to the Source
( )
Information Requested by Analyst
(S) Date Information Delivered to Client
(S) Additional Data Request by Client
Yes
No
(S) Dates Additional Data Requests Met
( )
Remarks
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(U)
(S)
SUMMARY EVALUATION SHEET (U)
For the summary evaluation, please check the following boxes as to the accuracy of the submitted material.
ACCURACY
Little
Correspondence
Site Contact,
with
Mixed Results
Good
Excellent
Unknown
Not
Applicable
0
1
2
3
(S) Geographical locale descrip-
tion (terrain, water, etc.)
(S) Large-scale manmade elements
(cities, buildings, silos,
docks, railroad lines,
airfields, etc.)
(S) Small-scale manmade elements
(antennas, computers, tanks,
missiles, offices, etc.)
(S) General target ambience (re-
search, production, adminis-
tration, storage, troop move-
ments, naval activity, air
activity, weapons testing, etc.)
(S) Relevant specific activities
(nuclear testing, missile
firing, CBW storage, ELINT
monitoring, etc.)
(S) Personality information
(physical descriptions,
actions, responsibilities,
plans, etc.)
(S) Overall utility
None
Marginal
Useful
Very Useful
Cannot be de-
termined at this time
*
(U) Definitions for the accuracy scale:
0 - Little correspondence
Self explanatory.
1 - Site contact with
mixed results
Mixture of correct and incorrect elements, but enough of the former to
indicate source has probably accessed the target site.
2 - Good
Good correspondence with several elements matching, but some incorrect information
3 - Excellent
Good correspondence with unambiguous unique matchable elements and relatively
little incorrect information.
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( ) DETAILED EVALUATION SHEET (U)
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Evaluation
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SECRET
Approved For Release 2000/08/07 : CIA-RDP96-00788R001300220001-4