Building Multi-Level Data Warehouse Based on Hybrid-Ontology

Author(s):  
Huamin Wang ◽  
Zhiwei Ye
2016 ◽  
Vol 12 (3) ◽  
pp. 32-50
Author(s):  
Xiufeng Liu ◽  
Nadeem Iftikhar ◽  
Huan Huo ◽  
Per Sieverts Nielsen

In data warehousing, the data from source systems are populated into a central data warehouse (DW) through extraction, transformation and loading (ETL). The standard ETL approach usually uses sequential jobs to process the data with dependencies, such as dimension and fact data. It is a non-trivial task to process the so-called early-/late-arriving data, which arrive out of order. This paper proposes a two-level data staging area method to optimize ETL. The proposed method is an all-in-one solution that supports processing different types of data from operational systems, including early-/late-arriving data, and fast-/slowly-changing data. The introduced additional staging area decouples loading process from data extraction and transformation, which improves ETL flexibility and minimizes intervention to the data warehouse. This paper evaluates the proposed method empirically, which shows that it is more efficient and less intrusive than the standard ETL method.


2008 ◽  
Vol 14 (4) ◽  
pp. 949-959 ◽  
Author(s):  
Nelli Westercamp ◽  
Christine L. Mattson ◽  
Michelle Madonia ◽  
Stephen Moses ◽  
Kawango Agot ◽  
...  

2017 ◽  
Vol 141 ◽  
pp. 120-124 ◽  
Author(s):  
Xiao Yu ◽  
Yue Zhao ◽  
Chao Li ◽  
Chaoquan Hu ◽  
Liang Ma ◽  
...  

2011 ◽  
Vol 41 (10) ◽  
pp. 2221-2231 ◽  
Author(s):  
N. M. Menezes ◽  
K. Georgiades ◽  
M. H. Boyle

BackgroundMany studies have reported an increased incidence of psychiatric disorder (particularly psychotic disorders) among first generation adult immigrants, along with an increasing risk for ethnic minorities living in low-minority concentration neighborhoods. These studies have depended mostly on European case-based databases. In contrast, North American studies have suggested a lower risk for psychiatric disorder in immigrants, although the effect of neighborhood immigrant concentration has not been studied extensively.MethodUsing multi-level modeling to disaggregate individual from area-level influences, this study examines the influence of first generation immigrant status at the individual level, immigrant concentration at the neighborhood-level and their combined effect on 12-month prevalence of mood, anxiety and substance-dependence disorders and lifetime prevalence of psychotic disorder, among Canadians.ResultsIndividual-level data came from the Canadian Community Health Survey (CCHS) 1.2, a cross-sectional study of psychiatric disorder among Canadians over the age of 15 years; the sample for analysis wasn=35 708. The CCHS data were linked with neighborhood-level data from the Canadian Census 2001 for multi-level logistic regression. Immigrant status was associated with a lower prevalence of psychiatric disorder, with an added protective effect for immigrants living in neighborhoods with higher immigrant concentrations. Immigrant concentration was not associated with elevated prevalence of psychiatric disorder among non-immigrants.ConclusionsThe finding of lower 12-month prevalence of psychiatric disorder in Canadian immigrants, with further lessening as the neighborhood immigrant concentration increases, reflects a model of person–environment fit, highlighting the importance of studying individual risk factors within environmental contexts.


2020 ◽  
pp. 135406882094470
Author(s):  
Athanassios Gouglas ◽  
Gabriel Katz ◽  
Bart Maddens ◽  
Marleen Brans

This paper examines the influence of party change on party-level legislative turnover. Analyzing a novel dataset tracking 251 parties in eight West European democracies between 1945 and 2015, we assess how transformational party events affect the renewal of parties’ parliamentary delegations. Transformational party events refer to party changes resulting from deliberate strategic decisions that redistribute power within parties, change their identity, and/or shift alliances within and between them. We focus in particular on changes in parties’ leadership and name, the formation of electoral cartels, mergers and divisions, applying empirical methods suitable for dealing with fractional outcomes and multi-level data to test their impact on turnover rates. Our estimates indicate that leadership change is a key determinant of MP renewal, leading to systematically higher rates of legislative turnover. Party relabeling and divisions affect turnover as well, although their influence is contingent on other characteristics of the parties and their environment.


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