Internal Revenue Service

About: Internal Revenue Service is a based out in . It is known for research contribution in the topics: Taxpayer & Tax credit. The organization has 171 authors who have published 185 publications receiving 3338 citations. The organization is also known as: IRS & Agenzia delle Entrate – Ministero dell’Economia e delle Finanze.

Myths and realities: Defining re-engineering for a large organization

Abstract: This paper describes the background and results of three studies concerning software reverse engineering, re-engineering, and reuse (R3) hosted by the Internal Revenue Service in 1991 and 1992. The situation at the Internal Revenue--aging, piecemeal computer systems and outdated technology maintained by a large staff--is familiar to many institutions, especially among management information systems. The IRS is distinctive for the sheer magnitude and diversity of its problems; the country's tax records are processed using assembly language and COBOL and spread across tape and network DBMS files. How do we proceed with replacing legacy systems? The three software re-engineering studies looked at methods, CASE tool support, and performed a prototype project using re-engineering methods and tools. During the course of these projects, we discovered critical issues broader than the mechanical definitions of methods and tool technology.

Perceptions of confidentiality protection at statistical agencies: Some evidence from data on businesses and households

Abstract: This paper provides an overview of research into public perceptions of confidentiality. Statistical agencies expend a great deal of time and resources to protect the data that they collect from unauthorized disclosure and identification of individual responses. However, data protection, by its very nature, involves either reducing data quality or limiting access to the very information that statistical agencies go to so much trouble and expense to collect. Many statistical agencies know little about an important input into the data protection decision: the degree to which their own respondents - both businesses and households - understand and believe that statistical agencies have, in fact, delivered on their confidentiality promises and how such perceptions affect their responses. This paper provides a brief survey of the selected knowledge in the area. Results for the United States suggest that much work needs to be done to further this knowledge, and the paper argues that research into perceptions should be institutionalised by statistical agencies and used to inform data protection decisions. 1. Background Statistical agencies enter into an implicit pact with their respondents to protect the data with which they are entrusted - both because they are so mandated by law and because the protect is needed to maintain the trust necessary for high quality responses. In fulfilling this pact, they expend a great deal of effort applying different access protocols and data protection techniques. This protection comes at quite some cost - data protection, by its very nature, involves either reducing data quality or limiting access to the very information that statistical agencies go to so much trouble and expense to collect. However, it is ironic that many statistical agencies, whose role it is to provide information to make decisions, know little about an important input into the data protection decision: the degree to which their own respondents - both business and households - understand and believe that statistical agencies have, in fact, delivered on their confidentiality promises and how such perceptions affect their responses. This paper provides a survey of what is known about the public perceptions of how statistical agencies protect their data. 1 Note: This paper reports the results of research and analysis, part of which was undertaken by Census Bureau staff. It has undergone a Census Bureau review more limited in scope than that given to official Census Bureau publications. This report is released to inform interested parties of ongoing research and to encourage discussion of work in progress. All views expressed represent those of the authors, and not necessarily the institutions they represent.