vol30-1.indd 4 IASSIST Quarterly Spring 2006 Editor’s Notes Welcome to the first issue of the IASSIST Quarterly, vol. 30, the first 2006 issue. From my seat, it is that time of year when days are gray. Danish poet Henrik Nordbrandt has said: “The year has 16 months: November, December, January, February, March, April, May, June, July, August, September, October, November, November, November, November.” But November is a good time for planning, for writing abstracts, and for preparing to go to Montreal in the sun of May 2007 for the next IASSIST conference. Read more about the conference in this issue. IASSIST conferences are international and the first article, “Setting up Acquisition Policies for a New Data Archive,” is international and based on two presentations at the IASSIST conference in Edinburgh, May 2005. In the session, “Enlightened Policies: Improving Collections and Acquisitions,” Finnish and Slovene data archivists found that their two presentations could be combined. Consequently, they compiled a joint article from the presentations. The authors are Helena Laaksonen and Sami Borg from the Finnish Social Science Data Archive, and Janez Stebe from the Social Science Data Archives at the University of Ljubljana in Slovenia. When discussing data quality, central concepts are: accuracy, timeliness, accessibility, comparability, and coherence (Eurostat). Furthermore, the archive must include the cost and burden of acquisition, processing and distribution by the archives. After the initial phase of archiving mostly quantitative social science data, the archives have moved to include qualitative data and also expand the coverage area into educational and health sciences. It is also found that some archives do not reject datasets, but there might be very little processing done if the data are considered to be of low quality. The article not only concerns the two archives, there is also a short report on “what kind of support social science funding organisations give to archiving and data sharing.” A solid kind of support from data producers is when data are “understandable,” have “clarity,” or to put in archivist-lingo, are “well-documented.” That leads us to the second article in this issue, “Problems of Comparability in the German Microcensus over Time and the New DDI Version 3.0,” by Jeanette Bohr, Andrea Janssen and Joachim Wackerow from the Centre for Survey, Research and Methodology (ZUMA) in Mannheim, Germany. The article starts with a short introduction to the Data Documentation Initiative (DDI). The problem with earlier versions of the DDI metadata standard was that it did not have an option for recording changes over time in repeated surveys. The German Microcensus is repeated annually and is undergoing changes from year to year, and these changes must be documented. DDI 3.0 addresses problems of describing the data life cycle. This includes describing groups of studies as well as the relationships within collections of comparable studies. The DDI version 3.0 is not yet a frozen standard and this article is considered a contribution to the exploration of the coming standard. The article demonstrates the hierarchical grouping model with examples of the structure of the German Microcensus. The conclusion consists of some pros and cons concerning the 3.0 version of the DDI. Ultimately the new version is regarded as a better instrument for managing and processing of metadata. The third article is also about metadata: “Everything but the Kitchen Sink: Building a Metadata Repository for Time Series Data at the Federal Reserve Board.” This was presented in the session, “The Essential Role of Metadata in Resource Discovery,” at the IASSIST 2006 in Ann Arbor. The authors are San Cannon and Meredith Krug from the Federal Reserve Board. The Federal Reserve Board uses a variety of time series data for both research and forecasting. As stated in the preface to the article: The tasks consist of collection, maintenance, and upkeep of more than 50,000 time series from many sources, plus documenting the metadata for the compilation and use of the data. The metadata repository will link three kinds of metadata about the time series: structural metadata, reference metadata, and operational metadata. Structural metadata is the short text that brings meaning to what would otherwise just be a number without value. The reference metadata contain more detail about the calculations behind the number, such as data collection, sampling, etc. Operational metadata are the exact processing instructions. While in the past the information was in different formats and on different platforms, this project is building a repository, which includes, among other things, a hierarchical nomenclature system in the structural metadata that is exemplified in the article. Also addressed is the “challenge of time” - an obviously important area for these data. “Everything but the Kitchen Sink” typically means that the kitchen sink would be too much, but I think it also means that a few other things incorporated probably already are too much. However, in my evaluation, the title is supposed to be a catcher of attention - not a statement about having too much metadata. The IASSIST website is always open http://iassistdata.org and you can look at conference information and visit the IASSIST blog - the IASSIST Communiqué – at http:// iassistblog.org. Articles for the IASSIST Quarterly are most welcome. Articles can be papers from IASSIST conferences, from other conferences, from local presentations, discussion input, etc. Contact the editor via e-mail: kbr@sam.sdu.dk. Karsten Boye Rasmussen, November 2006