A Biological Knowledge Laboratory
{'Code': '08080205', 'Directorate': {'Abbreviation': 'BIO', 'LongName': 'Direct For Biological Sciences'}, 'Division': {'Abbreviation': 'DBI', 'LongName': 'Div Of Biological Infrastructure'}}
{'SignBlockName': 'Peter Arzberger'}
The great volume and depth of scientific knowledge contained in                 the published literature is rapidly becoming available in                       machine-readable (computerized) form.  This research addresses                  the issue of how to give a scientist, a biologist, rapid access                 to this knowledge through a computer system that behaves very                   much like a well-informed colleague, a "Scientist's Assistant".                 The Assistant answers questions by returning appropriate text                   and diagrams, not a list of documents.  Though the approach is                  comprehensive, two topics are emphasized.  Analog Reasoning which               assumes that human knowledge and reasoning is essentially analog                and encyclopedic rather than discrete and formal, and Diagram                   Understanding which treats diagrammatic material as a conveyer of               information which complements language in crucial ways.  The                    research uses and develops tools in artificial intelligence,                    computer vision, natural language understanding, and related                    fields.
{'FirstName': 'Robert', 'LastName': 'Futrelle', 'EmailAddress': 'futrelle@ccs.neu.edu', 'StartDate': '02/01/1989', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
{'Name': 'Northeastern University', 'CityName': 'BOSTON', 'ZipCode': '021155005', 'PhoneNumber': '6173733004', 'StreetAddress': '360 HUNTINGTON AVE', 'CountryName': 'United States', 'StateName': 'Massachusetts', 'StateCode': 'MA'}
{'Code': '1107', 'Text': 'COMPUTATIONAL BIOLOGY ACTIVITI'}
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=1988&All=true', 'xml': '8814522.xml'}