Morpheus – An Innovative Approach to Remote Data Access
Julia Höninger
State Statistical Institute Berlin-Brandenburg, Berlin, Germany

Due to the increasing demand for micro data access by the scientific community, data providers are constantly improving ways of data access, trying to facilitate data access for users and reduce the work load for data providers. The system Morpheus is a novel approach in providing remote access to micro data of official statistics. Researchers work on anonymous micro data files with common statistical software packages and get their results back in real time. Additionally, a measure of goodness of fit will be provided for every single result. Therefore researchers can work with the anonymous results as they can have confidence that they would have obtained the same or very similar results analysing the original data. All statistical analyses and all commands are allowed. Furthermore, users can browse through the anonymous data which is very helpful when developing program syntax and not possible in most other systems of remote access.

Research data centres would greatly benefit from such a system as well, as the cumbersome manual disclosure control would be eliminated. All results would be safe and automatically returned to the researcher. This system respects the special requirements to micro data access even in Germany where laws are especially strict.

References:

Australian Bureau of Statistics (2010): Technical Manual: Remote Access Data Laboratory (RADL), User Guide. Website accessed 14th of February 2011, http://www.abs.gov.au/AUSSTATS/abs@.nsf/DetailsPage/1406.0.55.002Mar%202006?OpenDocument.

Brandt, M. and M. Zwick (2009): Improvement of the Informational Infrastructure – on the Way to Remote Data Access in Germany. Joint UNECE/Eurostat Work Session on Statistical Data Confidentiality, Bilbao, Spain, 2-4 December 2009, Working Paper No. 16.

Hundepool, A., J. Domingo-Ferrer, L. Franconi, S. Giessing, R. Lenz, J. Naylor, E. Schulte Nordholt, G. Seri and P.-P. de Wolf (2010): Handbook on Statistical Disclosure Control. Version 1.2, available from http://neon.vb.cbs.nl/casc/ SDC_Handbook.pdf.

National Center for Health Statistics - Research Data Center (2010): Disclosure Manual. Website accessed 14th February 2011, www.cdc.gov/rdc/Data/B4/DisclosureManual.pdf and www.cdc.gov/rdc/Data/B2/SASSUDAANRestrictions.pdf.

O'Keefe, C.M. and N.M. Good (2009): Regression Output from a Remote Analysis Server. Data & Knowledge Engineering 68: 1175-1186.

Oganian, A., Reiter, J. P. and Karr, A. F. (2009): Verification servers: Enabling analysts to assess the quality of inferences from public use data. Computational Statistics and Data Analysis 53(4): 1475-1482.

Keywords: future data access; research data centre; confidential micro data; statistical disclosure control

Biography: Julia Höninger works at the Research Data Centre of the Statistical Offices of the German Länder in the State Statistical Office Berlin-Brandenburg. She studied at the University of Tübingen, Germany, and the Universidade Federal Fluminense, Brasil, and holds a Diploma in International Economics.