Evaluating Process Quality Based on Change Request Data – An Empirical Study of the Eclipse Project

Abstract. The information routinely collected in change request management systems contains valuable information for monitoring of the process quality. However this data is currently utilized in a very limited way. This paper presents an empirical study of the process quality in the product portfolio of the Eclipse project. It is based on a systematic approach for the evaluation of process quality characteristics using change request data. Results of the study offer insights into the development process of Eclipse. Moreover the study allows assessing applicability and limitations of the proposed approach for the evaluation of process quality

Qualitätskontrolle mittels semantischer Technologien in digitalen Bibliotheken

Controlled content quality especially in terms of indexing is one of the major ad-vantages of using digital libraries in contrast to general Web sources or Web search engines. Therefore, more and more digital libraries offer corpora related to a specialized domain. Beyond simple keyword based searches the resulting infor-mation systems often rely on entity centered searches. For being able to offer this kind of search, a high quality document processing is essential. However, considering today’s information flood the mostly manual effort in ac-quiring new sources and creating suitable (semantic) metadata for content indexing and retrieval is already prohibitive. A recent solution is given by automatic genera-tion of metadata, where mostly statistical techniques like e.g. document classifica-tion and entity extraction currently become more widespread. But in this case neglecting quality assurance is even more problematic, because heuristic genera-tion often fails and the resulting low-quality metadata will directly diminish the quality of service that a digital library provides. Thus, the quality assessment of information system’s metadata annotations used for subsequent querying of collections has to be enabled. In this thesis we discuss the importance of metadata quality assessment for information systems and the benefits gained from controlled and guaranteed quality.Eine kontrollierte Qualität der Metadaten ist einer der wichtigsten Vorteile bei der Verwendung von digitalen Bibliotheken im Vergleich zu Web Suchmaschinen. Auf diesen hochqualitativen Inhalten werden immer mehr fachspezifische Portale durch die digitalen Bibliotheken erzeugt. Die so entstehenden Informationssysteme bieten oftmals neben einer simplen Stichwortsuche auch Objekt zentrierte Suchen an. Um solch eine Objekt-Suche zu ermöglichen, ist aber eine hochqualitative Verarbeitung der zugrunde liegenden Dokumente notwendig. Betrachtet man hingegen die heutige Informationsflut, so stellt man fest, dass der Aufwand für eine manuelle Erschließung von neuen Quellen und die Erzeugung von (semantischen) Metadaten für die Indexierung schon heute unerschwinglich ist. Eine aktuelle Lösung für dieses Problem ist die zumeist automatische Erzeugung von (semantischen) Metadaten, durch statistische Methoden, wie die automatische Dokumenten Klassifizierung Entitäten Extraktion. Aber bei der Verwendung sol-cher Methoden ist die Vernachlässigung der Qualität noch problematischer, da eine heuristische Erzeugung oftmals fehlerbehaftet ist. Diese schlechte Qualität der so erzeugten Metadaten wird dabei direkt die Servicequalität einer digitalen Biblio-thek herabmindern. Somit muss eine Qualitätsbewertung der Metadaten garantiert werden. In dieser Arbeit diskutieren wir die Bedeutung von Metadaten Qualität für Digitale Bibliotheken und die Chancen die aus kontrollierter und garantierter Qua-lität gewonnen werden können

Provenance of "after the fact" harmonised community-based demographic and HIV surveillance data from ALPHA cohorts

Background: Data about data, metadata, for describing Health and Demographic Surveillance System (HDSS) data have often received insufficient attention. This thesis studied how to develop provenance metadata within the context of HDSS data harmonisation - the network for Analysing Longitudinal Population-based HIV/ AIDS data on Africa (ALPHA). Technologies from the data documentation community were customised, among them: A process model - Generic Longitudinal Business Process Model (GLBPM), two metadata standards - Data Documentation Initiative (DDI) and Standard for Data and Metadata eXchange (SDMX) and a data transformations description language - Structured Data Transform Language (SDTL). Methods: A framework with three complementary facets was used: Creating a recipe for annotating primary HDSS data using the GLBPM and DDI; Approaches for documenting data transformations. At a business level, prospective and retrospective documentation using GLBPM and DDI and retrospectively recovering the more granular details using SDMX and SDTL; Requirements analysis for a user-friendly provenance metadata browser. Results: A recipe for the annotation of HDSS data was created outlining considerations to guide HDSS on metadata entry, staff training and software costs. Regarding data transformations, at a business level, a specialised process model for the HDSS domain was created. It has algorithm steps for each data transformation sub-process and data inputs and outputs. At a lower level, the SDMX and SDTL captured about 80% (17/21) of the variable level transformations. The requirements elicitation study yielded requirements for a provenance metadata browser to guide developers. Conclusions: This is a first attempt ever at creating detailed metadata for this resource or any other similar resources in this field. HDSS can implement these recipes to document their data. This will increase transparency and facilitate reuse thus potentially bringing down costs of data management. It will arguably promote the longevity and wide and accurate use of these data