EXISTING DATABASE MANAGEMENT SYSTEMS (DBMS'S) CAN EFFICIENTLY HANDLE ONLY FORMATTED ALPHANUMERIC DATA.

EXISTING DATABASE MANAGEMENT SYSTEMS (DBMS'S) CAN EFFICIENTLY HANDLE ONLY FORMATTED ALPHANUMERIC DATA. HOWEVER, MANY APPLICATIONS (E.G., OFFICE AUTOMATION, INDUSTRIAL AUTOMATION, COMPUTER-AIDED DESIGN, MILITARY COMMAND AND CONTROL, AND INTELLIGENCE) ALSO REQUIRE ACCESS TO OTHER TYPES OF INFORMATION SUCH AS TEXT, MAPS, DIAGRAMS, PHOTOGRAPHS, IMAGES AND SIGNALS WHICH CANNOT BE EFFICIENTLY STORED AND ACCESSED EFFECTIVELY BY CURRENT DBMS'S. AS A RESULT, APPLICATIONS SUFFER UNACCEPTABLE ERRORS AND DELAYS WHILE INFORMATION IS MANUALLY COMPILED FROM A VARIETY OF INFORMATION SOURCES. ANOTHER SHORTCOMING OF EXISTING DBMS'SIS THAT THEY CAN STORE ONLY LIMITED KINDS OF SEMANTIC KNOWLEDGE (VIZ. OBJECT TYPES, RELATIONSHIPS, AND SIMPLE CONSTRAINTS) ABOUT DATA IN THE DATABASE. ALL OTHER KNOWLEDGE MUST BE BUILT INTO THE APPLICATION PROGRAMS. HOWEVER, THIS MAKES IT EXTREMELY EXPENSIVE TO DEVELOP AND CHANGE THE PROGRAMS, ESPECIALLY AS KNOWLEDGE EVOLVES. THE OBJECTIVE OF THIS EFFORT IS TO DEVELOP AN ADVANCED DBMS WITHFACILITIES TO INPUT, STORE, RETRIEVE, AND OUTPUT MULTIPLE INFORMATION TYPES; AND FACILITIES FOR DECLARING AND MANIPULATING GENERAL KNOWLEDGE. THE FEASIBILITY OF THIS CHALLENGING OBJECTIVE RESTS ON A KEY TECHNICAL INSIGHT: IT IS NECESSARY TO ENHANCE EXISTING DATA MODELS WITH (A) DIMENSIONAL (SPACE AND TIME) ASPECTS, WHICH ARE THE COMMON CHARACTERISTIC OF NON-RECORD INFORMATION; AND (B) RECURSIVE PREDICATES AND QUERIES WHICH WILL PROVIDE DEDUCTIVE CAPABILITIES EQUIVALENT TO THOSE OF MANY KNOWLEDGE-BASED SYSTEMS. THE GOAL OF PHASE I IS TO SUBSTANTIATE THIS INSIGHT, AND, IF SUCCESSFUL, TO DEVELOP PLANS FOR A NEW KNOWLEDGE-ORIENTED DBMS ARCHITECTURE.