scholarly journals Growing Potentials for Migration Research using the German Socio-Economic Panel Study

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Jannes Jacobsen ◽  
Magdalena Krieger ◽  
Felicitas Schikora ◽  
Jürgen Schupp
Keyword(s):  
Panel Study ◽  
Data Sources ◽  
Private Households ◽  
External Data ◽  
Migration Research ◽  
Concise Overview ◽  
Basic Features

Abstract This article highlights the potentials for migration research using the German Socio-Economic Panel Study (SOEP), a longitudinal panel dataset of private households in Germany running since 1984. We provide a concise overview of its basic features, describe the survey contents and research potentials, and demonstrate opportunities to link external data sources to the SOEP thereby presenting its diverse and impactful applications in migration research.

Diversity in the teachers’ lounge in Germany – casting doubt on the statistical category of ‘migration background’

2021 ◽  
pp. 147490412110549
Author(s):  
Lisa Rosen ◽  
Marita Jacob
Keyword(s):  
Panel Study ◽  
Migration Background ◽  
The Other ◽  
Educational Science ◽  
National Education ◽  
Migration Research ◽  
Intercultural Competencies ◽  
Educational Migration ◽  
Methodological Considerations ◽  
Teacher Data

Teachers with so-called migration backgrounds are often assumed to possess higher intercultural competencies or skills for more adequately dealing with migration-related diversity than other teachers. However, these assumptions of higher intercultural competencies, specific pedagogical orientations and attitudes have rarely been systematically empirically examined. On the other hand, such a utilitarian ethnicization is increasingly criticized by migration researchers in educational science in Germany as furthering stigmatization and deprofessionalization. Against this background, our paper aims to contribute to the lively discourse about teacher with so-called migration backgrounds. We start with analysing teacher data from the German National Education Panel Study (NEPS). Our analyses indicate that teachers with and without so-called migration backgrounds do not differ significantly in most respects. These findings led us to methodological considerations with regard to the (non-)usefulness of the statistical category of ‘migration background’ in educational migration research.

scholarly journals DATA SOURCES FOR BUSINESS INTELLIGENCE

2021 ◽  
Author(s):  
Naveen Kunnathuvalappil Hariharan
Keyword(s):  
Big Data ◽  
Business Intelligence ◽  
Personal Data ◽  
Data Sources ◽  
Enterprise Information System ◽  
Enterprise Information ◽  
External Data ◽  
Operational Systems ◽  
Internal Sources ◽  
Key Questions

As organizations' desire for data grows, so does their search for data sources that are both usable and reliable.Businesses can obtain and collect big data in a variety of locations, both inside and outside their own walls.This study aims to investigate the various data sources for business intelligence. For business intelligence,there are three types of data: internal data, external data, and personal data. Internal data is mostly kept indatabases, which serve as the backbone of an enterprise information system and are known as transactionalsystems or operational systems. This information, however, is not always sufficient. If the company wants toanswer market and industry questions or better understand future customers, the analytics team may need to look beyond the company's own data sources. Organizations must have access to a variety of data sources in order to answer the key questions that guide their initiatives. Internal sources, external public sources, andcollaboration with a big data expert could all be beneficial. Companies who are able to extract relevant datafrom their mountain of data acquire new perspectives on their business, allowing them to become morecompetitive

Supporting Position Change through On-Line Location-Based Skyline Queries

2015 ◽  
pp. 325-362
Author(s):  
Marlene Goncalves ◽  
Alberto Gobbi
Keyword(s):  
Information Extraction ◽  
Geographical Location ◽  
Data Sources ◽  
Dynamic Features ◽  
Position Change ◽  
Skyline Queries ◽  
External Data ◽  
On Line ◽  
Tree Index ◽  
The Web

Location-based Skyline queries select the nearest objects to a point that best meet the user's preferences. Particularly, this chapter focuses on location-based Skyline queries over web-accessible data. Web-accessible may have geographical location and be geotagged with documents containing ratings by web users. Location-based Skyline queries may express preferences based on dynamic features such as distance and changeable ratings. In this context, distance must be recalculated when a user changes his position while the ratings must be extracted from external data sources which are updated each time a user scores an item in the Web. This chapter describes and empirically studies four solutions capable of answering location-based Skyline queries considering user's position change and information extraction from the Web inside an area search around the user. They are based on an M-Tree index and Divide & Conquer principle.

scholarly journals Influence of Information Quality via Implemented German RCD Standard in Research Information Systems

Data ◽  
2020 ◽  
Vol 5 (2) ◽  
pp. 30
Author(s):  
Otmane Azeroual ◽  
Joachim Schöpfel ◽  
Dragan Ivanovic
Keyword(s):  
Information Systems ◽  
Data Quality ◽  
Information Quality ◽  
Research Performance ◽  
Data Sources ◽  
Steady Increase ◽  
Research Information ◽  
External Data ◽  
Core Dataset ◽  
The Impact

With the steady increase in the number of data sources to be stored and processed by higher education and research institutions, it has become necessary to develop Research Information Systems, which will store this research information in the long term and make it accessible for further use, such as reporting and evaluation processes, institutional decision making and the presentation of research performance. In order to retain control while integrating research information from heterogeneous internal and external data sources and disparate interfaces into RIS and to maximize the benefits of the research information, ensuring data quality in RIS is critical. To facilitate a common understanding of the research information collected and to harmonize data collection processes, various standardization initiatives have emerged in recent decades. These standards support the use of research information in RIS and enable compatibility and interoperability between different information systems. This paper examines the process of securing data quality in RIS and the impact of research information standards on data quality in RIS. We focus on the recently developed German Research Core Dataset standard as a case of application.

scholarly journals Merging Data Diversity of Clinical Medical Records to Improve Effectiveness

2019 ◽  
Vol 16 (5) ◽  
pp. 769 ◽  
Author(s):  
Berit I. Helgheim ◽  
Rui Maia ◽  
Joao C. Ferreira ◽  
Ana Lucia Martins
Keyword(s):  
Language Processing ◽  
Medical Records ◽  
Healthcare Services ◽  
Data Sources ◽  
Digital Data ◽  
External Data ◽  
Knowledge Area ◽  
Effective Use ◽  
Technical Solutions

Medicine is a knowledge area continuously experiencing changes. Every day, discoveries and procedures are tested with the goal of providing improved service and quality of life to patients. With the evolution of computer science, multiple areas experienced an increase in productivity with the implementation of new technical solutions. Medicine is no exception. Providing healthcare services in the future will involve the storage and manipulation of large volumes of data (big data) from medical records, requiring the integration of different data sources, for a multitude of purposes, such as prediction, prevention, personalization, participation, and becoming digital. Data integration and data sharing will be essential to achieve these goals. Our work focuses on the development of a framework process for the integration of data from different sources to increase its usability potential. We integrated data from an internal hospital database, external data, and also structured data resulting from natural language processing (NPL) applied to electronic medical records. An extract-transform and load (ETL) process was used to merge different data sources into a single one, allowing more effective use of these data and, eventually, contributing to more efficient use of the available resources.

scholarly journals The CoBiS Linked Open Data Project and Portal

2018 ◽  
Vol 186 ◽  
pp. 12013 ◽  
Author(s):  
Luisa Schiavone ◽  
Federico Morando ◽  
Keyword(s):  
Open Data ◽  
Heterogeneous Data ◽  
Data Sources ◽  
External Data ◽  
Heterogeneous Data Sources ◽  
Historical Archives ◽  
Technical Realization ◽  
Metrological Research ◽  
Academy Of Sciences ◽  
Mapping Language

The CoBiS is a network formed by 65 libraries. The project is a pilot for Piedmont that is aiming to provide the Committee with an infrastructure for LOD publishing, thus creating a triplification pipeline designed to be easy to automate and replicate. This is being realized with open source technologies, such as the RML mapping language or the JARQL tool that uses Linked Data to describe the conversion of XML, JSON or tabular data into RDF. The first challenge consisted in making possible the dialog of heterogeneous data sources, coming from four different library software (Clavis, Erasmo, SBNWeb and BIBLIOWin 5.0web) and different types of data (bibliographic, multimedia, and archival). The information contained in the catalogs is progressively interlinked with external data sources, such as Wikidata, VIAF, LoC and BNF authority files, Wikipedia and the Dizionario Biografico degli Italiani. Partners of the CoBiS LOD Project are: National Institute for Astrophysics (INAF), Turin Academy of Sciences, Olivetti Historical Archives Association, Alpine Club National Library, Deputazione Subalpina di Storia Patria, National Institute for Metrological Research (INRIM). The technical realization of the project is entrusted to Synapta, and it is partially sponsored by Piedmont Region.

scholarly journals The Establishment and Refinement of the National Basketball Association Player Injury and Illness Database

2019 ◽  
Vol 54 (5) ◽  
pp. 466-471 ◽  
Author(s):  
Christina D. Mack ◽  
Peter Meisel ◽  
Mackenzie M. Herzog ◽  
Lisa Callahan ◽  
Eva E. Oakkar ◽  
...  
Keyword(s):  
Medical Record ◽  
Electronic Medical Record ◽  
Health And Safety ◽  
Electronic Medical Record System ◽  
National Basketball Association ◽  
Data Sources ◽  
Record System ◽  
Additional Information ◽  
External Data ◽  
Data Linkages

The National Basketball Association (NBA; also referred to as “the league”) has established a centralized, audited electronic medical record system that has been linked with external sources to provide a platform for robust research and to allow the NBA to conduct player health and safety reviews. The system is customized and maintained by the NBA and individual teams as part of the employment records for each player and is deployed uniformly across all 30 teams in the league, thereby allowing for standardized data on injuries, illnesses, and player participation in NBA games and practices. The electronic medical record data are enriched by linkage with other league external data sources that provide additional information about injuries, players, game and practice participation, and movement. These data linkages allow for the assessment of potential injury trends, development of injury-prevention programs, and rule changes, with the ultimate goal of improving player health and wellness. The purpose of this article is to describe this NBA injury database, including the details of data collection, data linkages with external data sources, and activities related to reporter training and data quality improvement.

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