Like many countries, the COVID-19 pandemic has forced Statistics Netherlands to make changes in its fieldwork strategy. Since mid-March 2020, there have been limited opportunities to conduct face-to-face interviews. Therefore, from September 2020, CAPI sampled people are offered the opportunity to respond by telephone. For this purpose, face-to-face interviewers are instructed to persuade the potential respondent at the doorway. When people refuse a face-to-face interview, interviewers ask for a telephone number and try to make an appointment to conduct the interview by telephone. The aim of our study was to investigate the effects of conducting the interview by telephone instead of face-to-face on important survey outcome variables. We were particularly interested in whether differences are due to selection effects or caused by mode-specific measurement errors. Because we did not have the time or capacity to set up a controlled experiment, we performed regression analyses to decompensate the differences between selection effects and mode-specific measurement errors. We used data of the Labour Force Survey (LFS) and the Housing Survey (WoON). Our analysis showed that there were differences in important target variables, for both LFS and WoON. These differences were, however, mainly caused by selection effects – which can be taken into account for during weighting – and were less likely to be caused by mode specific measurement errors. Although there are important limitations and caveats, these findings are supportive to further implement this field strategy.
Moving away from the strong body of critique of pervasive ‘bad data’ practices by both governments and private actors in the globalized digital economy, this book aims to paint an alternative, more optimistic but still pragmatic picture of the datafied future. The authors examine and propose ‘good data’ practices, values and principles from an interdisciplinary, international perspective. From ideas of data sovereignty and justice, to manifestos for change and calls for activism, this collection opens a multifaceted conversation on the kinds of futures we want to see, and presents concrete steps on how we can start realizing good data in practice.
Charging an electric vehicle needs to be as simple as possible for the user. He needs to park his car, plug his vehicle and identify to start charging. There is no need to understand the technology and protocols needed to reach this simple task.For the students and researchers of the Amsterdam University of Applied Science (AUAS / HvA), there is a need to understand as deep as possible all the techniques involved in this technology.The purpose of this document is to give to the reader the information he needs to understand how an electric car can be charged and how he can use these knowledges to analyses and interpret data.
Developing a framework that integrates Advanced Language Models into the qualitative research process.Qualitative research, vital for understanding complex phenomena, is often limited by labour-intensive data collection, transcription, and analysis processes. This hinders scalability, accessibility, and efficiency in both academic and industry contexts. As a result, insights are often delayed or incomplete, impacting decision-making, policy development, and innovation. The lack of tools to enhance accuracy and reduce human error exacerbates these challenges, particularly for projects requiring large datasets or quick iterations. Addressing these inefficiencies through AI-driven solutions like AIDA can empower researchers, enhance outcomes, and make qualitative research more inclusive, impactful, and efficient.The AIDA project enhances qualitative research by integrating AI technologies to streamline transcription, coding, and analysis processes. This innovation enables researchers to analyse larger datasets with greater efficiency and accuracy, providing faster and more comprehensive insights. By reducing manual effort and human error, AIDA empowers organisations to make informed decisions and implement evidence-based policies more effectively. Its scalability supports diverse societal and industry applications, from healthcare to market research, fostering innovation and addressing complex challenges. Ultimately, AIDA contributes to improving research quality, accessibility, and societal relevance, driving advancements across multiple sectors.
National forestry Commission (SBB) and National Park De Biesbosch. Subcontractor through NRITNational parks with large flows of visitors have to manage these flows carefully. Methods of data collection and analysis can be of help to support decision making. The case of the Biesbosch National Park is used to find innovative ways to figure flows of yachts, being the most important component of water traffic, and to create a model that allows the estimation of changes in yachting patterns resulting from policy measures. Recent policies oriented at building additional waterways, nature development areas and recreational concentrations in the park to manage the demands of recreation and nature conservation offer a good opportunity to apply this model. With a geographical information system (GIS), data obtained from aerial photographs and satellite images can be analyzed. The method of space syntax is used to determine and visualize characteristics of the network of leisure routes in the park and to evaluate impacts resulting from expected changes in the network that accompany the restructuring of waterways.
To treat microbial infections, antibiotics are life-saving but the increasing antimicrobial resistance is a World-wide problem. Therefore, there is a great need for novel antimicrobial substances. Fruit and flower anthocyanins have been recognized as promising alternatives to traditional antibiotics. How-ever, for future application as innovative alternative antibiotics, the full potential of anthocyanins should be further investigated. The antimicrobial potential of anthocyanin mixtures against different bacterial species has been demonstrated in literature. Preliminary experiments performed by our laboratories, using grape, rose and red cabbage anthocyanins against S. aureus and E. coli confirmed the antimicrobial potential of these substances. Hundreds of different anthocyanin entities have been described. However, which of these entities hold antimicrobial effects is currently unknown. Our preliminary data show that an-thocyanins extracted from grape, rose and red cabbage contain different collections of anthocyanin entities with differential antimicrobial efficacies. Our focus is on the extraction and characterization of anthocyanins from various crop residues. Grape peels are residues in the production of wine, while red rose and tulip leaves are residues in the production of tulip bulbs and regular horticulture. The presence of high-grade substances for pharmacological purposes in these crops may provide an innovative strategy to add value to other-wise invaluable crop residues. This project will be performed by the collaborative effort of our institute together with the Medi-cal Microbiology department of the University Medical Center Groningen (UMCG), 'Wijnstaete', a small-scale wine-producer (Lemelerveld) and Imenz Bioengineering (Groningen), a company that develops processes to improve the production of biobased chemicals from waste products. Within this project, we will focus on the antimicrobial efficacy of anthocyanin-mixtures from sources that are abundantly and locally available as a residual waste product. The project is part of a larger re-search effect to further characterize, modify and study the antimicrobial effects of specific anthocy-anin entities.
