Understanding and Modeling Context in Data Integration

Author(s):  
William T. Sabados ◽  
Harry S. Delugach

The pragmatic context of information is a fundamental characteristic that is not often formally addressed in data integration. This paper discusses the challenges of modeling the multiple contexts at play in data integration. A simple data integration context modeling framework is introduced that we believe addresses important issues of representing a pragmatic context. It allows for multiple data sources from similar domains to be brought together without having to designate one as the “true” semantics. An example is provided showing how this approach supports integration efforts.

Author(s):  
Lijing Wang ◽  
Aniruddha Adiga ◽  
Srinivasan Venkatramanan ◽  
Jiangzhuo Chen ◽  
Bryan Lewis ◽  
...  

Omega ◽  
2021 ◽  
pp. 102479
Author(s):  
Zhongbao Zhou ◽  
Meng Gao ◽  
Helu Xiao ◽  
Rui Wang ◽  
Wenbin Liu

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Jin Chen ◽  
Tianyuan Chen ◽  
Yifei Song ◽  
Bin Hao ◽  
Ling Ma

AbstractPrior literature emphasizes the distinct roles of differently affiliated venture capitalists (VCs) in nurturing innovation and entrepreneurship. Although China has become the second largest VC market in the world, the unavailability of high-quality datasets on VC affiliation in China’s market hinders such research efforts. To fill up this important gap, we compiled a new panel dataset of VC affiliation in China’s market from multiple data sources. Specifically, we drew on a list of 6,553 VCs that have invested in China between 2000 and 2016 from CVSource database, collected VC’s shareholder information from public sources, and developed a multi-stage procedure to label each VC as the following types: GVC (public agency-affiliated, state-owned enterprise-affiliated), CVC (corporate VC), IVC (independent VC), BVC (bank-affiliated VC), FVC (financial/non-bank-affiliated VC), UVC (university endowment/spin-out unit), and PenVC (pension-affiliated VC). We also denoted whether a VC has foreign background. This dataset helps researchers conduct more nuanced investigations into the investment behaviors of different VCs and their distinct impacts on innovation and entrepreneurship in China’s context.


2012 ◽  
Vol 24 (2) ◽  
pp. 280-291 ◽  
Author(s):  
Christine M. Anderson-Cook ◽  
Richard M. Klamann ◽  
Jerome Morzinski

2017 ◽  
Vol 9 (1) ◽  
pp. 2-12 ◽  
Author(s):  
Evan Mayo-Wilson ◽  
Tianjing Li ◽  
Nicole Fusco ◽  
Kay Dickersin ◽  

Sign in / Sign up

Export Citation Format

Share Document