scholarly journals Reflections on the Use of the Intermediate Data Structure (IDS) in Historical Demographic Research

2021 ◽  
Vol 10 ◽  
pp. 76-80
Author(s):  
Luciana Quaranta
Keyword(s):  
Data Structure ◽  
Demographic Data ◽  
Demographic Research ◽  
Intermediate Data ◽  
Micro Level

The Intermediate Data Structure (IDS) was developed as a strategy aimed at standardizing the dissemination of micro-level historical demographic data. The structure provides a common and clear data strategy which facilitates studies that consider several databases, and the development and exchange of software. Based on my own experiences from working with the IDS, in this article I provide reflections on the use of IDS to create datasets for analysis and to conduct comparative demographic research.

scholarly journals Using the Intermediate Data Structure (IDS) to Construct Files for Statistical Analysis

2015 ◽  
Vol 2 ◽  
pp. 86-107
Author(s):  
Luciana Quaranta
Keyword(s):  
Data Structure ◽  
Statistical Analysis ◽  
Demographic Data ◽  
Intermediate Data ◽  
Micro Level ◽  
And Storage

The use of longitudinal historical micro-level demographic data for research presents many challenges. The Intermediate Data Structure (IDS) was developed to try to solve some of these challenges by facilitating the storing and sharing of such data. This article proposes an extension to the IDS, which allows the standardization and storage of constructed variables. It also describes how to produce a rectangular episodes file for statistical analysis from data stored in the IDS and presents programs developed for such purpose.

scholarly journals Introduction: Intergenerational Transmissions of Infant Mortality using the Intermediate Data Structure (IDS)

2018 ◽  
Vol 7 ◽  
pp. 1-10
Author(s):  
Luciana Quaranta ◽  
Hilde Leikny Sommerseth
Keyword(s):  
Data Structure ◽  
Infant Mortality ◽  
Empirical Studies ◽  
Special Issue ◽  
Maternal Line ◽  
Demographic Research ◽  
Intermediate Data ◽  
Current Article ◽  
Death Clustering ◽  
Intergenerational Transmissions

It has previously been shown that infant mortality clusters in a subset of families, a phenomenon which was observed in historical populations as well as contemporary developing countries. A transmission of death clustering across generations has also been shown in Belgium, but it is unknown whether such effects are specific to the studied context or are also found in other areas. The current article introduces a special issue devoted to analysing intergenerational transmissions of infant mortality across the maternal line in Belgium, the Netherlands, northern and southern Sweden, and Norway. Taking advantage of the Intermediate Data Structure (IDS), the five empirical studies created datasets for analysis and ran statistical models using exactly the same programs, which are also published within the special issue. These works are the first set of studies using the IDS on several databases for comparative purposes. Consistent results across the studied contexts were shown: transfers of infant mortality across the maternal line were seen in all five areas. In addition, the works have shown that there are large advantages of adopting the IDS for historical demographic research. The structure has in fact allowed researchers to conduct studies which were fully comparable, transparent and replicable.

scholarly journals Program for Studying Intergenerational Transmissions in Infant Mortality Using the Intermediate Data Structure (IDS)

2018 ◽  
Vol 7 ◽  
pp. 11-27
Author(s):  
Luciana Quaranta
Keyword(s):  
Data Structure ◽  
Infant Mortality ◽  
Demographic Data ◽  
Intergenerational Transfers ◽  
Infant Deaths ◽  
Intermediate Data ◽  
Different Populations ◽  
Social And Cultural Factors ◽  
Death Clustering ◽  
Intergenerational Transmissions

Studies conducted in historical populations and developing countries have evidenced the existence of clustering in infant deaths, which could be related to genetic inheritance and/or to social and cultural factors such as education, socioeconomic status or parental care. A transmission of death clustering has also been found across generations. One way of expanding the knowledge on intergenerational transfers in infant mortality is by conducting comparable studies across different populations. The Intermediate Data Structure (IDS) was developed as a strategy aimed at simplifying the collecting, storing and sharing of historical demographic data. The current work presents two programs that were developed in STATA to construct a dataset for analysis and run statistical models to study intergenerational transfers in infant mortality using databases that are stored in the IDS. The programs use information stored in the IDS tables and after elaborating such information produce Excel files with results. They can be used with any longitudinal database constructed from church books, civil registers, or population registers.

scholarly journals STATA Programs for Using the Intermediate Data Structure (IDS) to Construct Files for Statistical Analysis

2016 ◽  
Vol 3 ◽  
pp. 1-19
Author(s):  
Luciana Quaranta
Keyword(s):  
Data Structure ◽  
Statistical Analysis ◽  
Open Access ◽  
Demographic Data ◽  
Intermediate Data ◽  
Common Structure ◽  
Current Article ◽  
Using Data ◽  
New Variables ◽  
Extract Information

The Intermediate Data Structure (IDS) provides a common structure for storing and sharing historical demographic data. The structure also facilitates the construction of different open-access software to extract information from these tables and construct new variables. The article Using the Intermediate Data Structure (IDS) to Construct Files for Analysis (Quaranta 2015) presented a series of concepts and programs that allow the user to construct a rectangular episodes file for longitudinal statistical analysis using data stored in the IDS. The current article discusses, in detail, each of these programs, describing their technicalities, structure and syntax, and also explaining how they can be used.

scholarly journals Extending the Intermediate Data Structure (IDS) for longitudinal historical databases to include geographic data

2014 ◽  
Vol 1 ◽  
pp. 27-46
Author(s):  
Finn Hedefalk ◽  
Lars Harrie ◽  
Patrick Svensson
Keyword(s):  
Data Structure ◽  
Demographic Data ◽  
Extended Version ◽  
Intermediate Data ◽  
Common Structure ◽  
Geographic Data ◽  
Extensible Markup ◽  
Geographic Datasets ◽  
Historical Databases

The Intermediate Data Structure (IDS) is a standardised database structure for longitudinal historical databases. Such a common structure facilitates data sharing and comparative research. In this study, we propose an extended version of IDS, named IDS-Geo, that also includes geographic data. The geographic data that will be stored in IDS-Geo are primarily buildings and/or property units, and the purpose of these geographic data is mainly to link individuals to places in space. When we want to assign such detailed spatial locations to individuals (in times before there were any detailed house addresses available), we often have to create tailored geographic datasets. In those cases, there are benefits of storing geographic data in the same structure as the demographic data. Moreover, we propose the export of data from IDS-Geo using an eXtensible Markup Language (XML) Schema. IDS-Geo is implemented in a case study using historical property units, for the period 1804 to 1913, stored in a geographically extended version of the Scanian Economic Demographic Database (SEDD). To fit into the IDS-Geo data structure, we included an object lifeline representation of all of the property units (based on the snapshot time representation of single historical maps and poll-tax registers). The case study verifies that the IDS-Geo model is capable of handling geographic data that can be linked to demographic data.

scholarly journals Historical Databases Now and in the Future

2021 ◽  
Vol 10 ◽  
pp. 9-12
Author(s):  
Kris Inwood ◽  
Hamish Maxwell-Stewart
Keyword(s):  
Data Structure ◽  
The Netherlands ◽  
Longitudinal Data ◽  
Practical Implementation ◽  
High Quality ◽  
Rule Based ◽  
Intermediate Data ◽  
The Future ◽  
Historical Databases ◽  
Historical Sample

Kees Mandemakers has enriched historical databases in the Netherlands and internationally through the development of the Historical Sample of the Netherlands, the Intermediate Data Structure, a practical implementation of rule-based record linking (LINKS) and personal encouragement of high quality longitudinal data in a number of countries.

Suffix Tree Constructing Algorithm for Datasets with Discrete Contents

2015 ◽  
Vol 733 ◽  
pp. 867-870
Author(s):  
Zhen Zhong Jin ◽  
Zheng Huang ◽  
Hua Zhang
Keyword(s):  
Data Structure ◽  
Sensor Network ◽  
Association Analysis ◽  
Data Structures ◽  
Suffix Tree ◽  
Analysis Data ◽  
Large Datasets ◽  
Intermediate Data ◽  
Input Strings

The suffix tree is a useful data structure constructed for indexing strings. However, when it comes to large datasets of discrete contents, most existing algorithms become very inefficient. Discrete datasets are need to be indexed in many fields like record analysis, data analyze in sensor network, association analysis etc. This paper presents an algorithm, STD, which stands for Suffix Tree for Discrete contents, that performs very efficiently with discrete input datasets. It imports several wonderful intermediate data structures for discrete strings; we also take care of the situation that the discrete input strings have similar characteristics. Moreover, STD keeps the advantages of existing implementations which are for successive input strings. Experiments were taken to evaluate the performance and shown that the method works well.

Child Pornography Sentencing and Demographic Data: Reforming Through Research

2011 ◽  
Vol 24 (2) ◽  
pp. 102-107
Author(s):  
SpearIt
Keyword(s):  
Child Pornography ◽  
Demographic Data ◽  
The Internet ◽  
Sentencing Guidelines ◽  
Demographic Research ◽  
Related Research ◽  
Federal Sentencing Guidelines ◽  
Sentencing Reform ◽  
History Of ◽  
Sentencing Policy

This article examines demographic research on child pornography offenders and considers its utility for sentencing reform. It begins by tracing the history of the Internet and federal possession law, detailing particularly how public and political panic about child pornography evolved within a growing fear of the Internet itself. The article continues by surveying current demographic research on possession offenders. Drawing on this data and related research, the article considers what the literature can contribute to sentencing policy, simultaneously showcasing vast differences between the type of offender Congress intended to punish and those actually receiving the harsh punishment. Taken wholly, this article explains why child pornography guidelines represent a departure from the normal process of creating Federal Sentencing Guidelines; it tells how law succumbed to the forces of fear and stacked the scale against child pornography offenders.

scholarly journals Intergenerational Transfers of Infant Mortality in 19th-Century Northern Sweden

2018 ◽  
Vol 7 ◽  
pp. 106-122
Author(s):  
Göran Broström ◽  
Sören Edvinsson ◽  
Elisabeth Engberg
Keyword(s):  
Infant Mortality ◽  
Infant Death ◽  
Comparative Research ◽  
Demographic Data ◽  
Intergenerational Transfers ◽  
Intermediate Data ◽  
International Comparative ◽  
Further Development ◽  
Analytical Power ◽  
Intergenerational Transmissions

This contribution is part of an international comparative initiative with the aim to assess the analytical power of the Intermediate Data Structure (IDS) in a study of possible intergenerational transmissions of death in infancy. An evaluation of the data in applied research will be useful for further development of the IDS structure and for its future use in comparative research. An additional methodological aim for this part of the study is to evaluate and compare different models for statistical analysis of intergenerational transfers. The analysis is based on a cohort of mothers born 1826-1854, whose experiences of infant mortality are compared to the ones of the previous generation, the grandmothers. Data are collected from Swedish parish records, available in the database POPUM at the Demographic Data Base in Umeå. The analysis shows a clear association between infant mortality among mothers and grandmothers. The probability of an infant death for a woman is increased if her mother also had experienced an infant death. Having tested for different approaches of analysis, we found that simple models with few restrictive assumptions gave similar results as more complicated models. Since it is easy to feel confident in the models with the weakest assumptions, we argue that such models are preferred for this type of analysis.

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