A Morphological Box for Handling Temporal Data in B2C Systems

User interfaces are key properties of Business-to-Consumer (B2C) systems, and Web-based reservation systems are an important class of B2C systems. In this paper we show that these systems use a surprisingly broad spectrum of different approaches to handling temporal data in their Web inter faces. Based on these observations and on a literature analysis we develop a Morphological Box to present the main options for handling temporal data and give examples. The results indicate that the present state of developing and maintaining B2C systems has not been much influenced by modern Web Engi neering concepts and that there is considerable potential for improvement.

Electronic medical record systems, data quality and loss to follow-up: survey of antiretroviral therapy programmes in resource-limited settings

OBJECTIVE: To describe the electronic medical databases used in antiretroviral therapy (ART) programmes in lower-income countries and assess the measures such programmes employ to maintain and improve data quality and reduce the loss of patients to follow-up. METHODS: In 15 countries of Africa, South America and Asia, a survey was conducted from December 2006 to February 2007 on the use of electronic medical record systems in ART programmes. Patients enrolled in the sites at the time of the survey but not seen during the previous 12 months were considered lost to follow-up. The quality of the data was assessed by computing the percentage of missing key variables (age, sex, clinical stage of HIV infection, CD4+ lymphocyte count and year of ART initiation). Associations between site characteristics (such as number of staff members dedicated to data management), measures to reduce loss to follow-up (such as the presence of staff dedicated to tracing patients) and data quality and loss to follow-up were analysed using multivariate logit models. FINDINGS: Twenty-one sites that together provided ART to 50 060 patients were included (median number of patients per site: 1000; interquartile range, IQR: 72-19 320). Eighteen sites (86%) used an electronic database for medical record-keeping; 15 (83%) such sites relied on software intended for personal or small business use. The median percentage of missing data for key variables per site was 10.9% (IQR: 2.0-18.9%) and declined with training in data management (odds ratio, OR: 0.58; 95% confidence interval, CI: 0.37-0.90) and weekly hours spent by a clerk on the database per 100 patients on ART (OR: 0.95; 95% CI: 0.90-0.99). About 10 weekly hours per 100 patients on ART were required to reduce missing data for key variables to below 10%. The median percentage of patients lost to follow-up 1 year after starting ART was 8.5% (IQR: 4.2-19.7%). Strategies to reduce loss to follow-up included outreach teams, community-based organizations and checking death registry data. Implementation of all three strategies substantially reduced losses to follow-up (OR: 0.17; 95% CI: 0.15-0.20). CONCLUSION: The quality of the data collected and the retention of patients in ART treatment programmes are unsatisfactory for many sites involved in the scale-up of ART in resource-limited settings, mainly because of insufficient staff trained to manage data and trace patients lost to follow-up.

Open Data and Earth Observations The Case of Opening Up Access to and Use of Earth Observation Data Through the Global Earth Observation System of Systems

Earth observations (EO) represent a growing and valuable resource for many scientific, research and practical applications carried out by users around the world. Access to EO data for some applications or activities, like climate change research or emergency response activities, becomes indispensable for their success. However, often EO data or products made of them are (or are claimed to be) subject to intellectual property law protection and are licensed under specific conditions regarding access and use. Restrictive conditions on data use can be prohibitive for further work with the data. Global Earth Observation System of Systems (GEOSS) is an initiative led by the Group on Earth Observations (GEO) with the aim to provide coordinated, comprehensive, and sustained EO and information for making informed decisions in various areas beneficial to societies, their functioning and development. It seeks to share data with users world-wide with the fewest possible restrictions on their use by implementing GEOSS Data Sharing Principles adopted by GEO. The Principles proclaim full and open exchange of data shared within GEOSS, while recognising relevant international instruments and national policies and legislation through which restrictions on the use of data may be imposed.The paper focuses on the issue of the legal interoperability of data that are shared with varying restrictions on use with the aim to explore the options of making data interoperable. The main question it addresses is whether the public domain or its equivalents represent the best mechanism to ensure legal interoperability of data. To this end, the paper analyses legal protection regimes and their norms applicable to EO data. Based on the findings, it highlights the existing public law statutory, regulatory, and policy approaches, as well as private law instruments, such as waivers, licenses and contracts, that may be used to place the datasets in the public domain, or otherwise make them publicly available for use and re-use without restrictions. It uses GEOSS and the particular characteristics of it as a system to identify the ways to reconcile the vast possibilities it provides through sharing of data from various sources and jurisdictions on the one hand, and the restrictions on the use of the shared resources on the other. On a more general level the paper seeks to draw attention to the obstacles and potential regulatory solutions for sharing factual or research data for the purposes that go beyond research and education.

An Exploratory Study of Data Quality Management Practices in the ERP Software Systems Context

Quality data are not only relevant for successful Data Warehousing or Business Intelligence applications; they are also a precondition for efficient and effective use of Enterprise Resource Planning (ERP) systems. ERP professionals in all kinds of businesses are concerned with data quality issues, as a survey, conducted by the Institute of Information Systems at the University of Bern, has shown. This paper demonstrates, by using results of this survey, why data quality problems in modern ERP systems can occur and suggests how ERP researchers and practitioners can handle issues around the quality of data in an ERP software Environment.