Data Quality and Information Quality (SIGIQ)


Track Chair:

Yang Lee, Northeastern University, This e-mail address is being protected from spambots. You need JavaScript enabled to view it

Track Description:

This track will focus on ways to better understand and address information quality problems in organizational information systems.  The track will emphasize approaches to system design that ensure high quality information, behavioral issues in the use of information systems with information quality problems, and managerial issues in the design and use of systems with information quality problems.  Studies applying theoretical perspectives from psychology, artificial intelligence, management science, and organization science are sought.  Organizational case studies involving solutions to information quality problems are also sought.

Minitracks:

Exploring Unstructured Data Analytics in Healthcare

Iris Junglas, Florida State University, This e-mail address is being protected from spambots. You need JavaScript enabled to view it

Chon Abraham, College of William and Mary, This e-mail address is being protected from spambots. You need JavaScript enabled to view it

 

Exploring Unstructured Data Analytics in Healthcare "<p>Organizations are facing an increasing challenge managing and understanding unstructured data. In the healthcare arena, unstructured data is an essential factor in understanding the quality of information presented in electronic health records, how clinicians translate unstructured textual data and act upon it, or how patients understand, interpret and form opinions about healthcare providers. Analyzing this data, however, is a major challenge due to its unstructured nature, and also because the tools available are in their infancy and have not yet been commonly deployed in organizations. Unstructured data require a different analytical approach than those traditionally employed, and the exploration of standards and quality issues are necessary to consider when studying the healthcare field. This mini-track will seek to provide an outlet for research and contributions on the effective use of unstructured data analytics in healthcare.

Information Quality and Social Media in e-Government

Yurong Yao, Suffolk University, This e-mail address is being protected from spambots. You need JavaScript enabled to view it

Yang Lee, Northeastern University, This e-mail address is being protected from spambots. You need JavaScript enabled to view it

 

The successful adoption of information systems, development of effective communication channels, and improvement of information quality become increasing important in electronic government. Due to the special features of government, these issues in the government differ from those in the company setting, which directly impact citizens’ satisfaction and democracy. This minitrack seeks papers that address the role of information quality in citizen-government communications, particularly in the usage of social media, such as microblog.

Information Quality in Crowdfunding

Irit Askira Gelman, Tucson, AZ, This e-mail address is being protected from spambots. You need JavaScript enabled to view it

 

Crowdfunding (CF) describes the collective effort of people who network and pool their resources, usually via the Internet, to finance efforts initiated by other people or organizations. A recent industry report by Crowdsourcing.org suggests that CF platforms raised almost $1.5 billion in 2011 and are expected to nearly double that amount in 2012. However, despite the impressive growth rate of the CF industry and heated debates over the potential risks and benefits of CF, academic studies of CF are still very rare. This minitrack aims to draw researchers’ interest to CF from the angle of information quality. We assume that information can play a critical role in clarifying the risks of CF to stakeholders and mitigating them. Hence, there is a need to define the information and information quality requirements in the different CF settings and to use such definitions in information quality assessments and improvement efforts.

Quality of Data Standards and Standards-Based Data

Hongwei Zhu, Old Dominion University, This e-mail address is being protected from spambots. You need JavaScript enabled to view it

 

This mini-track focuses on quality issues that involve data standards and data produced according to certain data standards. Similar to other computing artifacts, data standards are costly to develop and can have long-term impacts on the quality and effectiveness of downstream data and systems. This mini-track invites original contributions that investigate various aspects of data standards and other related standards. Topics include, but are not limited to, standards development, standards quality, and impacts of standards on quality of standards-based data, systems, and organizations.