The accuracy and biases of diary communication data

A study to determine the accuracy and reliability of telephone communications data obtained via self-recording diaries was undertaken. The methodology involved comparing data obtained from the diaries to the more objective data provided by the recording capabilities of a PBX (Private branch Exchange). Two questions formed the basis for the analysis. First, what is the level of accuracy of diary data, and, second what biases are inherent in data obtained from self-recorded diaries. The findings indicate that diary data significantly understate the actual frequency of communications. There were also several biases inherent in the diary data. One involved a significant understatement of very short communications (i.e. those lasting less than 90 seconds). The others showed an under-recording of received calls and a likelihood to record internal rather than external cals. The conclusion drawn is that in the absence of objective data (i.e. data obtained from machine recording) diaries can provide usable data as long as one pays attention to the biases inherent in their use.     

Secondary Data Analysis in Family Research

This article first provides an overview of the part that secondary data analysis plays in the field of family studies in the early 21st century. It addresses changes over time in the use of existing omnibus data sets and discusses their advantages and disadvantages. The second part of the article focuses on the elements that make a study a “family” study. It describes sources of existing data and the process of selecting a data set. The third part presents special issues and concerns in using existing data, and the fourth part addresses the future of secondary data analysis in the field of family research.     

The use of GIS in informal settlement upgrading: its role and impact on the community and on local government

The Urban Geographical Information Systems (GIS) Group within the Department of Civil Engineering at the University of Cape Town has been coordinating a pilot informal settlement upgrading in Cape Town since 1998. The project objective has been the evolution of a model-based approach to informal settlement upgrading that is both structured and replicable. It was felt that the only way this could be achieved was through the use of a spatial data management system operated through a GIS system. The spatial database has been used for all facets of data collection and data process and forms the basis for all decision-making. Thus it covers all physical data pertaining to the site, cadastral and shack data, demographic and socio-economic data (with an in-depth review of every household) economic opportunities and physical planning and design data. The result is a comprehensive, integrated, settlement upgrading methodology that is built upon a GIS-based spatial data management framework. Such a framework is seen as the basic building block for large-scale informal settlement upgrading.     

CALIBRATING MEASURES OF FAMILY ACTIVITIES BETWEEN LARGE- AND SMALL-SCALE DATA SETS

Two studies of working families are combined to demonstrate a strategy for producing reliable estimates from the combination of self-reported (large N) and observational (small N) data. Both studies examine where and how dual-career families spend time at home. The 500 Family Study is sociological and uses self-reported time diary data from a national sample; the CELF study is anthropological and uses observational scan sampling data from a regional sample of 32 families. The data are combined as if they constitute one sample, and an analytic solution for establishing the reliability of the resulting composite estimates of time use is provided. Merging the data sets provides validation for each study, neither of which is without potential methodological weaknesses. The advantages of combining data from the independent data collection methods are discussed, and selected substantive findings on families' activities are highlighted, illustrating similarities and differences between findings in the independent and combined data sets. Results show that working families spend significant time in a small spectrum of home spaces, particularly kitchens and living rooms, with leisure activities prevailing, but mothers, fathers, and children differ in where and how they spend their time. Overall, a template for merging data from different disciplines and methods is provided.     

Data culture as a change agent for organizations serving families and children experiencing homelessness

Over the past decade there have been considerable developments in the use of data in the field of child and family homelessness. The development of high-quality data collection processes—including Housing Management Information Systems (HMIS), community point-in-time counts, and school district data and evaluation infrastructure—has given nonprofit and social sector leaders unprecedented access to client-level data. However, it remains a challenge for nonprofits and community-based organizations to engage in work with families experiencing homelessness and demonstrate meaningful impact across a variety of outcomes. In this policy brief, the authors discuss (1) challenges facing the field of child and family homelessness with respect to data use, (2) recent advancements in the use of data, and (3) strategies to create an organizational culture of data that makes use of recent advancements in data use and addresses current challenges facing the field. The brief makes the argument that fostering a data culture at the organizational level has the capacity to operate as an organizational change agent that improves programs.     

Fehlermultiplikation und Pfadabhängigkeit

Secondary analyses, i.e. analyses of data which were not collected for this purpose and/or not by these people, are widely used due to their outstanding advantages. However, their methodological implications are seldom discussed. The widespread secondary use of few data sets has implications for the published knowledge base of the discipline. Known and unknown biases and random error in a particular data set are multiplied in published knowledge. The realm of undetected errors increases if data producer and data user are separated. Furthermore available data sets limit the possibility of introducing new concepts resulting in a path dependency of scientific progress. Consequently, primary data should be valued; using only partly appropriate data sets can improve and validate our knowledge; data sets have to be considered in literature reviews; and indirect measurement or additional macro variables may be used to integrate unconventional concepts. User conferences help closing the gap between data producers and users.     

Handheld computers. A feasible alternative to paper forms for field data collection

Recent advances in handheld computer hardware and software may provide alternatives to paper-based data collection methods. The authors compared data collected with paper forms to data collected with handheld computer-based forms in a field observation study of alcohol purchase attempts at 47 community festivals in a large metropolitan area. Agreement between data collected with paper forms and data collected with handheld computers was greater than 95%. Computer-based forms handled branching patterns better and yielded data that were immediately available for analyses. Paper forms handled written comments better. Handheld computers are a feasible alternative to paper forms for field data collection.     

Using Secondary Data for Grounded Theory Analysis

Abstract

Grounded theory is well utilised in qualitative research for building theoretical understanding of complex social processes. Grounded theory data analysis strategies can be used with different types of data, including secondary data. Despite the potential advantages of secondary data, it is rarely used for grounded theory studies, largely due to a perception that researchers are unable to follow the guidelines of this research design with data that they themselves have not collected. This paper demonstrates the use of secondary data in a study investigating the substantive area of Indigenous empowerment. Potential pitfalls and advantages of using grounded theory methods to analyse secondary data are discussed, as well as factors that facilitated the analytic process in this study. These factors included having a large data set across multiple sites and the use of literature as a source of data. The findings provide a valuable model for combining research and practise.     

The impact of ICT on systems biology and how to assess it

The rise of systems biology has been deeply associated with the application of high-throughput technologies and the development of digital databases. Both have an important impact on how research is done today and what it achieves. The plethora and heterogeneity of data have caused a change in approaches of data handling and processing by using Information and Communication Technology (ICT). To facilitate data management and the access and sharing of data on biological structures and processes as well as to link different databases from disparate data sources, ICT infrastructures have been developed simultaneously with the emergence of systems approaches in biology. Using the concept of technoscience, I explore the relationship of data-driven technologies and scientific approaches in systems biology and how to assess it according to a new understanding of science assessment. The analysis shows that ICT infrastructures play an important role in the systems biology community, taking over all the relevant tasks regarding the integration, access and sharing of data. Therefore, ICT infrastructures are primarily regarded as service facilities to ease research activities. However, the separation of data management and data interpretation as two independent endeavours hides the fact that data-driven technologies fundamentally influence the epistemic status of data and cause epistemic shifts in research practices and processes. Accordingly, the frame of ICT for data management enables doing research, but it shapes the significance and meaning of data, practices and processes at the same time by defining how to handle data in ICT-driven science.     

The myth of the “data‐driven” society: Exploring the interactions of data interfaces,circulations, and abstractions

The prominence of data and data technologies in society, such as algorithms, social media, mobile technology, and artificial intelligence, have heralded numerous claims of the revolutionary potential of these systems. From public policy, to business management, to scientific research, a “data‐driven” society is apparently imminent—or currently happening—where “objective” and asocial data systems are believed to be comprehensively improving human life. Through a review of existing sociological literature, in this article, we critically examine the relationship between data and society and propose a new model for understanding these dynamics. “Using the concept of the informatic,” we argue the relationship between data and society can be understood as representing the interaction of several different social trends around data; that of data interfaces (that connect individuals to digital contexts), data circulation (trends in the movement and storage of data), and data abstraction (data manipulation practices). Data and data technologies are founded to be entwined and embedded in numerous social relationships, and while not all are fair and equitable relationships, there is ample evidence of the deeply social nature of data across many streams of social life. Our three‐part informatic framework allows these complex relationships to be understood in the social dynamic through which they are witnessed and experienced.     

The potential for construction resource planning

The need for construction resource planning to avoid non-completion of, or delays to, projects and potential damage to an economy by trying to undertake programmes for which resources are not available is stressed. Then the availability, and method of application, of data for national use is considered followed by the problems of transferability of data from one country to another. Examples are given of the range of data for a specific country, of the broad labour inputs to construction for a number of countries of different characteristics and of key material requirements for twenty categories of housing over eight countries. The conclusion is that it is now possible to undertake resource planning for any major project or development plan anywhere in the world, though refinement of the available data and an increase in the volume of data is desirable. The authors suggest that a focal point for the collection of data and a clearing house for its use be established.     

Putting the pieces together for queer youth: a model of integrated assessment of need and program planning

Needs assessments require staff with the necessary expertise to design the study, collect the data, analyze the data, and present results. They require money, time, and persistence, because the people one wishes to assess often are difficult to access. This article argues for the centrality of a well-done needs assessment when developing services for LGBTQ youth. Needs assessment methodology and adjunctive uses of the needs assessment data also are discussed. The authors present a needs assessment of LGBTQ youth living in out-of-home care in San Diego, California, as an example of the purpose, practicality, and power of a comprehensive needs assessment. The needs assessment identified several issues, as well as additional data supporting the project's necessity. The data also identified the most significant obstacles youth face in accessing housing and supportive services. Through the data collection process, non-LGBT housing providers better understood their need for additional training, and housing and city leadership communities obtained and spread knowledge of the project.     

Linking Migration Intentions with Flows: Evidence and Potential Use

In the absence of reliable, internationally available migration flow data necessary for statistical forecasting, policymakers increasingly turn to survey data on emigration intentions to evaluate future migration trends. The important assumption – i.e. that there is a measurable and systematic relationship between the intention to migrate and actual migration – has not been firmly established at the international level. We examine the association between estimated population averages of emigration intentions and official migration flow data based on data for more than 160 countries. The results show a strong association between emigration intentions and recorded bilateral flows to industrialized countries, as well as between intentions and aggregated out‐migration. The results provide policymakers with a reliability assessment of survey data on emigration intentions and encourage future attempts to incorporate survey data in formal statistical migration forecasting models.     

Enhancing Longitudinal Studies by Linkage to National Databases: Growing Up in Australia,the Longitudinal Study of Australian Children†

Growing Up in Australia is a national longitudinal study of the development and wellbeing of 10,000 Australian children. The study has been committed since inception to support data linkage to other datasets, to value‐add to the primary modes of data collection from parents and others. It can increase the efficiency of data collection by reducing respondent and interviewer burden as well as adding new dimensions to addressing key research questions. The viability of data linkage needs to take into account the relevance of the data for research and policy, as well as data quality and cost, privacy and consent issues and the ease of access. This article documents the various sources for data linkage considered for Growing Up in Australia, including government health and education records, child care accreditation data, and community‐level data, and examines the strengths and challenges associated with each.     

Using national recording systems for the measurement and analysis of immigration to the United States

This article considers the kinds of data required to increase scientific knowledge about US immigration and, in light of those requirements, assesses the principal currently available data sets and makes recommendations for improving the data environment. Study of US immigration phenomena requires data with 3 properties: 1) that they cover immigrants, sponsors, and nation-states; 2) that they measure and link the migration-relevant attributes of the immigrants, sponsors, and nation-states, including the visa histories of both immigrants and sponsors; and 3) that they capture the migration-relevant attributes in a longitudinal manner. The 2 principal data sources currently available for studying immigration--the US decennial censuses and the administrative records of the Immigration and Naturalization Service--fall far short of the data requirements dictated by current reasoning and models about the migration process. Current data sources do not permit, except under stringent assumptions, the estimation of models of such phenomena as earnings, language acquisition, marital behavior, and fertility behavior. The authors propose both a new data-collection effort and a set of enhancements to existing data sources. Perhaps the most efficient way to learn more about immigration would be to design and implement a new data-collection effort with great success. In the meantime, proposed enhancements to existing data sources could help fill some gaps in present knowledge.     

When do simpler sexual behavior data collection techniques suffice? An analysis of consequent uncertainty in HIV acquisition risk estimates

The "gold standard" for evaluating human immunodeficiency virus (HIV) prevention programs is a partner-by-partner sexual behavior assessment that elicits information about each sex partner and the activities engaged in with that partner. When collection of detailed partner-by-partner data is not feasible, aggregate data (e.g., total numbers of partners and acts of various types) must suffice. Lack of specificity in the primary data often translates into uncertainty in modeled outcomes, such as participants' risk of HIV acquisition. To our knowledge, no previous study has attempted to quantify this uncertainty. The results of the present analysis of the risk of HIV acquisition by men vacationing in Key West indicate that the use of aggregate rather than partner-by-partner data introduced relatively little uncertainty into the HIV risk estimates. Collection of aggregate data is a viable alternative to detailed partner-by-partner data, at least in some circumstances.     

Sizing up Australia: toward a national sizing survey

This paper reports on the outcomes of research on the use of anthropometric data by designers of Australian workplaces and products used in Australian workplaces. Australian designers were asked how they used anthropometric data, and about the adequacy of data that were available to them for their needs as designers. In addition to a review of published and grey literature, designers were surveyed and asked for detailed information about their use of anthropometric data and about their needs. Thirty-two completed questionnaires were received. Two focus groups of designers were conducted; 13 people attended in Adelaide and 16 in Melbourne. The data indicated that designers either did not use anthropometric data at all or had difficulty finding data that were reliable and relevant to their specific needs. In response to the findings the Human Factors and Ergonomics Society of Australia developed a Special Interest Group for anthropometry that currently has over 150 members. The Group is actively lobbying government for an Australian Sizing Survey, so this research is an important stimulus to a major policy investment for Australia.     

Register data in the evaluation and program planning of addiction treatment programs: Using Sweden as an example

Data from large-scale registers is often underutilized when evaluating addiction treatment programs. Since many programs collect register data regarding clients and interventions, there is a potential to make greater use of such records for program evaluation. The purpose of this article is to discuss the value of using large-scale registers in the evaluation and program planning of addiction treatment systems and programs. Sweden is used as an example of a country where register data is both available and is starting to be used in national evaluation and program planning efforts.The article focuses on possibilities, limitations and practicalities when using large-scale register data to conduct evaluations and program planning of addiction treatment programs. Main conclusions are that using register data for evaluation provides large amounts of data at low cost, limitations associated to the use of register data may be handled statistically, register data can answer important questions in planning of addiction treatment programs, and more accurate measures are needed to account for the diversity of client populations.