4 research outputs found
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Providing a computing environment for a high energy physics workshop
Although computing facilities have been provided at conferences and workshops remote from the host institution for some years, the equipment provided has rarely been capable of providing for much more than simple editing and electronic mail. This report documents the effort involved in providing a local computing facility with world-wide networking capability for a physics workshop so that we and others can benefit from the knowledge gained through the experience
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The Fermilab experience: Integration of UNIX systems in a HEP computing environment
There is an increased emphasis within organizations to migrate to a distributed computing environment. Among the factors responsible for this migration are: (1) a proliferation of high performance systems based on processors such as the Intel 80{times}86, Motorola 680{times}0, RISC architecture CPU's such as MIPS R{times}000, Sun SPARC, Motorola 88000 and Intel 860 series; (2) a significant reduction in hardware costs; (3) configuration based on existing local area network technology; and (4) the same (to a large extent) operating system on all platforms. A characteristic of distributed computing is that communication takes the form of request-reply pairs. This is also referred to as the client-server model. The client-server model is rapidly growing in popularity and in many scientific and engineering environments is replacing transaction-based and mainframe systems. Over the last few years, Fermilab has been in the process of migrating to a client-server model of computing
Evaluating Common De-Identification Heuristics for Personal Health Information
BACKGROUND: With the growing adoption of electronic medical records, there are increasing demands for the use of this electronic clinical data in observational research. A frequent ethics board requirement for such secondary use of personal health information in observational research is that the data be de-identified. De-identification heuristics are provided in the Health Insurance Portability and Accountability Act Privacy Rule, funding agency and professional association privacy guidelines, and common practice. OBJECTIVE: The aim of the study was to evaluate whether the re-identification risks due to record linkage are sufficiently low when following common de-identification heuristics and whether the risk is stable across sample sizes and data sets. METHODS: Two methods were followed to construct identification data sets. Re-identification attacks were simulated on these. For each data set we varied the sample size down to 30 individuals, and for each sample size evaluated the risk of re-identification for all combinations of quasi-identifiers. The combinations of quasi-identifiers that were low risk more than 50% of the time were considered stable. RESULTS: The identification data sets we were able to construct were the list of all physicians and the list of all lawyers registered in Ontario, using 1% sampling fractions. The quasi-identifiers of region, gender, and year of birth were found to be low risk more than 50% of the time across both data sets. The combination of gender and region was also found to be low risk more than 50% of the time. We were not able to create an identification data set for the whole population. CONCLUSIONS: Existing Canadian federal and provincial privacy laws help explain why it is difficult to create an identification data set for the whole population. That such examples of high re-identification risk exist for mainstream professions makes a strong case for not disclosing the high-risk variables and their combinations identified here. For professional subpopulations with published membership lists, many variables often needed by researchers would have to be excluded or generalized to ensure consistently low re-identification risk. Data custodians and researchers need to consider other statistical disclosure techniques for protecting privacy