SIPP Access:  Facility for the Analysis of Large-Scale      Complex Longitudinal Data
{'Code': '04050300', 'Directorate': {'Abbreviation': 'SBE', 'LongName': 'Direct For Social, Behav & Economic Scie'}, 'Division': {'Abbreviation': 'SES', 'LongName': 'Divn Of Social and Economic Sciences'}}
{'SignBlockName': 'Larry Whittaker', 'PO_EMAI': None, 'PO_PHON': None}
SIPP ACCESS represents a prototype for managing data of the social              sciences and producing a scientific understanding of what is required to        approach large-scale data bases.  It is an experimental facility aimed          at the discovery of improved techniques for creating scientific                 knowledge through the application of computer and information science to        the social sciences.  Its goals include (1) increasing the utilization          of stored longitudinal data, (2) improving data retrieval from                  large-scale complex data collection activities, (3) clarifying the              meaning of replicated measurements, and (4) training researchers in             understanding such data in order to produce new knowledge of social and         economic phenomena.  The experiment incorporates an evaluation component        to determine whether this conception of managing large-scale complex            data can be appled to data other than SIPP (the Survey of Income and            Program Participation).                                                                                                                                         SIPP ACCESS mobilizes new technologies to make complex panel data               available to researchers, analysts, and policymakers at low cost.  SIPP         ACCESS links measurements to documentation, online data to a national           network of users, and results of research to users, thereby accelerating        research developments.  Its public utility aspect creates economies in          data handling by reducing the complexity of materials that a researcher         must deal with and by reorganizing replicated measurements into a form          consistent with the conceptual structure of analytical models of dynamic        phenomena.  Efficiencies in retrieval and clarity in the longitudinal           design of SIPP are achieved through eliminating redundant data and              through restructuring cross-sectional data into time series and event           histories.                                                                                                                                                      Data and documentation are integrated through an information                    management system that improves the delivery of data by eliminating             delays, clarifying the meaning of measurements, and ensuring the                retrieval of appropriate measures for analysis.                                                                                                                 Interactive access to data and documentation is provided through a              national dial-in system, a relational data base management system which         allows researchers to "build" their own data files and reorganize,              transform, and link data over time according to their particular                research questions.  Optical archival data storage eliminates all               programmer interventions between users and the data base.  The data base        management system improves retrieval of data from very large files,             thereby assisting researchers in solving problems related to analysis           such as identifying longitudinal samples, converting events to time             series, time series to event histories, and identifying inconsistent            data.  Training workshops are used to introduce researchers and policy          analysts to the subtleties of longitudinal data, relational theory, and         the relational data base management system.
[{'FirstName': 'Alice', 'LastName': 'Robbin', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Alice Robbin', 'EmailAddress': None, 'NSF_ID': '000192803', 'StartDate': '08/15/1987', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Martin', 'LastName': 'David', 'PI_MID_INIT': 'H', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Martin H David', 'EmailAddress': 'David@ssc.wisc.edu', 'NSF_ID': '000154697', 'StartDate': '08/15/1987', 'EndDate': None, 'RoleCode': 'Principal Investigator'}]
{'Name': 'University of Wisconsin-Madison', 'CityName': 'MADISON', 'ZipCode': '537151218', 'PhoneNumber': '6082623822', 'StreetAddress': '21 North Park Street', 'StreetAddress2': 'Suite 6301', 'CountryName': 'United States', 'StateName': 'Wisconsin', 'StateCode': 'WI', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_ORG': 'WI02', 'ORG_DUNS_NUM': '161202122', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF WISCONSIN SYSTEM', 'ORG_PRNT_DUNS_NUM': '041188822'}
{'Name': None, 'CityName': None, 'StateCode': None, 'ZipCode': None, 'StreetAddress': None, 'CountryCode': None, 'CountryName': None, 'StateName': None, 'CountryFlag': None, 'CONGRESSDISTRICT': None, 'CONGRESS_DISTRICT_PERF': '""'}
[{'Code': '1333', 'Text': 'Methodology, Measuremt & Stats'}, {'Code': '3133', 'Text': None}, {'Code': '9145', 'Text': 'SPECIAL PROGRAMS-RESERVE'}]
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=1987&All=true', 'xml': '8701911.xml'}