scholarly journals Editorial

2018 ◽  
Vol 5 ◽  
pp. 1-2
Author(s):  
Paul Puschmann ◽  
Luciana Quaranta
Keyword(s):  
Data Structure ◽  
Life Course ◽  
Comparative Research ◽  
Population Studies ◽  
Data Format ◽  
Standard Data ◽  
Intermediate Data ◽  
Historical Databases ◽  
Life Course Studies ◽  
Historical Life

Historical Life Course Studies, a journal in population studies, aims to stimulate and facilitate the implementation of IDS (Intermediate Data Structure, a standard data format for large historical databases), and to publish the results from (comparative) research with the help of large historical databases. The journal publishes not only empirical articles, but also descriptions (of the construction) of new and existing large historical databases, as well as articles dealing with database documentation, the transformation of existing databases into the IDS format, the development of algorithms and extraction software and all other issues related to the methodology of large historical databases.

scholarly journals Editorial

2015 ◽  
Vol 2 ◽  
pp. 37-37
Author(s):  
Koen Matthijs ◽  
Paul Puschmann
Keyword(s):  
Data Structure ◽  
Life Course ◽  
Comparative Research ◽  
Population Studies ◽  
Data Format ◽  
Standard Data ◽  
Intermediate Data ◽  
Historical Databases ◽  
Life Course Studies ◽  
Historical Life

Historical Life Course Studies, a journal in population studies, aims to stimulate and facilitate the implementation of IDS (Intermediate Data Structure, a standard data format for large historical databases), and to publish the results from (comparative) research with the help of large historical databases. The journal publishes not only empirical articles, but also descriptions (of the construction) of new and existing large historical databases, as well as articles dealing with database documentation, the transformation of existing databases into the IDS format, the development of algorithms and extraction software and all other issues related to the methodology of large historical databases.

scholarly journals The Intermediate Data Structure (IDS) for Longitudinal Historical Microdata, version 4

2014 ◽  
Vol 1 ◽  
pp. 1-26
Author(s):  
George Alter ◽  
Kees Mandemakers
Keyword(s):  
Data Structure ◽  
Social Research ◽  
Geospatial Information ◽  
Data Format ◽  
Standard Data ◽  
Intermediate Data ◽  
Hierarchical Relationships ◽  
Life Courses ◽  
Historical Life

The Intermediate Data Structure (IDS) is a standard data format that has been adopted by several large longitudinal databases on historical populations. Since the publication of the first version in Historical Social Research in 2009, two improved and extended versions have been published in the Collaboratory Historical Life Courses. In this publication we present version 4 which is the latest ‘official’ standard of the IDS. Discussions with users over the last four years resulted in important changes, like the inclusion of a new table defining the hierarchical relationships among ‘contexts’, decision schemes for recording relationships, additional fields in the metadata table, rules for handling stillbirths, a reciprocal model for relationships, guidance for linking IDS data with geospatial information, and the introduction of an extended IDS for computed variables.

scholarly journals Reflections on the Intermediate Data Structure (IDS)

2021 ◽  
Vol 10 ◽  
pp. 71-75
Author(s):  
George Alter
Keyword(s):  
Data Structure ◽  
Life Course ◽  
Data Structures ◽  
Relational Database ◽  
Life Histories ◽  
Social Scientists ◽  
Database Model ◽  
Intermediate Data ◽  
Value Model ◽  
Historical Life

The Intermediate Data Structure (IDS) encourages sharing historical life course data by storing data in a common format. To encompass the complexity of life histories, IDS relies on data structures that are unfamiliar to most social scientists. This article examines four features of IDS that make it flexible and expandable: the Entity-Attribute-Value model, the relational database model, embedded metadata, and the Chronicle file. I also consider IDS from the perspective of current discussions about sharing data across scientific domains. We can find parallels to IDS in other fields that may lead to future innovations.

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.

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 IDS Transposer: A Users Guide

2017 ◽  
Vol 4 ◽  
pp. 59-96
Author(s):  
Emily Klancher Merchant ◽  
George Alter
Keyword(s):  
Data Structure ◽  
Life Course ◽  
Software Tool ◽  
Standard Format ◽  
Individual Level ◽  
Intermediate Data ◽  
Source Data ◽  
Standard Set

The Intermediate Data Structure (IDS) provides a standard format for storing and sharing individual-level longitudinal life-course data (Alter and Mandemakers 2014; Alter, Mandemakers and Gutmann 2009). Once the data are in the IDS format, a standard set of programs can be used to extract data for analysis, facilitating the analysis of data across multiple databases. Currently, life-course databases store information in a variety of formats, and the process of translating data into IDS can be long and tedious. The IDS Transposer is a software tool that automates this process for source data in any format, allowing database administrators to specify how their datasets are to be represented in IDS. This article describes how the IDS Transposer works, first by going through an example step-bystep, and then by discussing each part of the process and potential options and exceptions in detail.

International Centre for Life course Studies in Society and Health

Impact ◽  
2017 ◽  
Vol 2017 (9) ◽  
pp. 88-90
Author(s):  
Amanda Sacker ◽  
Yvonne Kelly ◽  
Tarani Chandola
Keyword(s):  
Life Course ◽  
Life Course Studies

scholarly journals BIM Interoperability Analyses in Structure Design

CivilEng ◽  
2021 ◽  
Vol 2 (1) ◽  
pp. 174-192
Author(s):  
Alcinia Zita Sampaio ◽  
Augusto Martins Gomes
Keyword(s):  
Data Transfer ◽  
Structure Design ◽  
Data Format ◽  
Industry Foundation Classes ◽  
Standard Data ◽  
Transfer Processes ◽  
Building Information ◽  
Modeling Software ◽  
Efficient Level ◽  
Alternative Solutions

The building information modelling (BIM) methodology supports collaborative works, based on the centralization of all information in a federated BIM model and on an efficient level of interoperability between BIM-based platforms. Concerning the structure design, the interoperability capacity of the most used software presents limitations that must be identified and alternative solutions must be proposed. This study analyzes the process of transfer of structure models between modeling and structure analysis tools. Distinct building cases were performed in order to recognize the type of limitations verified in the transfer processes concerning two-way data flow between several software. The study involves the modeling software ArchiCAD 2020, Revit 2020, and AECOsim 2019 and the structure analyzes tools SAP 2020, Robot 2020, and ETABS 22020. The transfer processes are realized in two ways: using the native data format; using a universal standard data transfer, the Industry Foundation Classes (IFC) format. The level of maturity of BIM in structure design is still relatively low, caused essentially by interoperability problems, but despite the limitations detected, this study shows throughout the development of several building case, that the methodology has clear advantages in the development of the structure project.

scholarly journals Terahertz Image Detection with the Improved Faster Region-Based Convolutional Neural Network

Sensors ◽  
2018 ◽  
Vol 18 (7) ◽  
pp. 2327 ◽  
Author(s):  
Jinsong Zhang ◽  
Wenjie Xing ◽  
Mengdao Xing ◽  
Guangcai Sun
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Detection System ◽  
Terahertz Imaging ◽  
Image Detection ◽  
Data Format ◽  
Standard Data ◽  
Concealed Weapons ◽  
Special Distribution ◽  
Effectiveness And Efficiency

In recent years, terahertz imaging systems and techniques have been developed and have gradually become a leading frontier field. With the advantages of low radiation and clothing-penetrable, terahertz imaging technology has been widely used for the detection of concealed weapons or other contraband carried on personnel at airports and other secure locations. This paper aims to detect these concealed items with deep learning method for its well detection performance and real-time detection speed. Based on the analysis of the characteristics of terahertz images, an effective detection system is proposed in this paper. First, a lots of terahertz images are collected and labeled as the standard data format. Secondly, this paper establishes the terahertz classification dataset and proposes a classification method based on transfer learning. Then considering the special distribution of terahertz image, an improved faster region-based convolutional neural network (Faster R-CNN) method based on threshold segmentation is proposed for detecting human body and other objects independently. Finally, experimental results demonstrate the effectiveness and efficiency of the proposed method for terahertz image detection.

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