scholarly journals A conceptual framework for evaluating data suitability for observational studies

2017 ◽  
Vol 25 (3) ◽  
pp. 248-258 ◽  
Author(s):  
Ning Shang ◽  
Chunhua Weng ◽  
George Hripcsak
Keyword(s):  
Conceptual Framework ◽  
Observational Studies ◽  
Research Needs ◽  
Clinical Database ◽  
Data Governance ◽  
Web Based ◽  
Domain Experts ◽  
Design Considerations ◽  
Points Of View ◽  
Quality Categories

Abstract Objective To contribute a conceptual framework for evaluating data suitability to satisfy the research needs of observational studies. Materials and Methods Suitability considerations were derived from a systematic literature review on researchers’ common data needs in observational studies and a scoping review on frequent clinical database design considerations, and were harmonized to construct a suitability conceptual framework using a bottom-up approach. The relationships among the suitability categories are explored from the perspective of 4 facets of data: intrinsic, contextual, representational, and accessible. A web-based national survey of domain experts was conducted to validate the framework. Results Data suitability for observational studies hinges on the following key categories: Explicitness of Policy and Data Governance, Relevance, Availability of Descriptive Metadata and Provenance Documentation, Usability, and Quality. We describe 16 measures and 33 sub-measures. The survey uncovered the relevance of all categories, with a 5-point Likert importance score of 3.9 ± 1.0 for Explicitness of Policy and Data Governance, 4.1 ± 1.0 for Relevance, 3.9 ± 0.9 for Availability of Descriptive Metadata and Provenance Documentation, 4.2 ± 1.0 for Usability, and 4.0 ± 0.9 for Quality. Conclusions The suitability framework evaluates a clinical data source’s fitness for research use. Its construction reflects both researchers’ points of view and data custodians’ design features. The feedback from domain experts rated Usability, Relevance, and Quality categories as the most important considerations.

Design for Maintenance: How Kms Document Linking Decisions Affect Maintenance Effort and Use

2014 ◽  
Vol 29 (4) ◽  
pp. 312-326 ◽  
Author(s):  
Alan R Dennis ◽  
Binny M Samuel ◽  
Kelly McNamara
Keyword(s):  
Information System ◽  
System Development ◽  
Management Systems ◽  
Information System Development ◽  
Web Based ◽  
Useful Knowledge ◽  
Design Considerations ◽  
Dynamic Content ◽  
System Maintenance ◽  
The Cost

Information system maintenance is an important aspect of information system development, especially in systems that provide dynamic content, such as Web-based systems and Knowledge Management Systems (KMS). Design for Maintenance (DFM) is an approach that argues that maintenance effort should be considered during the design of information systems in addition to the usual system design considerations. This research examines how the design of links among knowledge documents in a KMS affects both their maintenance and use. We argue that providing links among knowledge documents increases the cost of maintenance because when a document changes, the documents that link to and from that document are more likely to need changes. At the same, linking knowledge documents makes it easier to locate useful knowledge and thus increases use. We examine this tension between use and maintenance using 10 years of data from a well-established KMS. Our results indicate that as the number of links among documents increases, both maintenance effort and use for these documents increase. Our analyses suggest two DFM principles for dynamic content in practice. First, knowledge coupling (i.e., linking) to documents internal to the KMS rather than sources external to the KMS better balances maintenance effort and use. Second, designing small, knowledge cohesive documents (e.g., 250-350 words) leads to the best balance between maintenance effort and use.

Ontology Learning from a Domain Web Corpus

Web Mining ◽  
2011 ◽  
pp. 69-98 ◽  
Author(s):  
Roberto Navigli
Keyword(s):  
World Wide ◽  
Shared Vision ◽  
Domain Ontology ◽  
Virtual Organizations ◽  
Semantic Interpretation ◽  
Application Domain ◽  
Web Based ◽  
Domain Experts ◽  
Usable Knowledge ◽  
The World

Domain ontologies are widely recognized as a key element for the so-called semantic Web, an improved, “semantic aware” version of the World Wide Web. Ontologies define concepts and interrelationships in order to provide a shared vision of a given application domain. Despite the significant amount of work in the field, ontologies are still scarcely used in Web-based applications. One of the main problems is the difficulty in identifying and defining relevant concepts within the domain. In this chapter, we provide an approach to the problem, defining a method and a tool, OntoLearn, aimed at the extraction of knowledge from Websites, and more generally from documents shared among the members of virtual organizations, to support the construction of a domain ontology. Exploiting the idea that a corpus of documents produced by a community is the most representative (although implicit) repository of concepts, the method extracts a terminology, provides a semantic interpretation of relevant terms and populates the domain ontology in an automatic manner. Finally, further manual corrections are required from domain experts in order to achieve a rich and usable knowledge resource.

Web-Based Systems Development

2010 ◽  
pp. 161-179
Author(s):  
Michael Lang
Keyword(s):  
Conceptual Framework ◽  
Qualitative Interviews ◽  
Systems Development ◽  
Web Development ◽  
Situated Action ◽  
Web Based ◽  
Development Data ◽  
Depth Study ◽  
Elementary Statistics

This chapter encapsulates the main findings of an in-depth study of Web development practices in Ireland. The essential research objective was to build a richer understanding of the modern context of Web development and of how that context influences design practices. At the outset, a conceptual framework was derived through a synthesis of issues in the literature and an analysis of existing models of IS development. Data was then gathered through a dual-mode (Web and postal) quantitative survey which yielded 165 usable responses, and later through a series of 14 semi-structured qualitative interviews in a follow-up field study. Following an interpretive approach, elementary statistics and grounded theory were used to iteratively analyze the data until a reasonably comprehensive and stable explanation emerged. This is presented in the form of an elaborated conceptual framework of Web-based systems development as “situated action.”

scholarly journals TeamTat: a collaborative text annotation tool

2020 ◽  
Vol 48 (W1) ◽  
pp. W5-W11
Author(s):  
Rezarta Islamaj ◽  
Dongseop Kwon ◽  
Sun Kim ◽  
Zhiyong Lu
Keyword(s):  
Project Managers ◽  
Biomedical Literature ◽  
Task Completion ◽  
Annotation Tool ◽  
Web Based ◽  
Domain Experts ◽  
Plain Text ◽  
Text Annotation ◽  
User Friendly ◽  
Input Format

Abstract Manually annotated data is key to developing text-mining and information-extraction algorithms. However, human annotation requires considerable time, effort and expertise. Given the rapid growth of biomedical literature, it is paramount to build tools that facilitate speed and maintain expert quality. While existing text annotation tools may provide user-friendly interfaces to domain experts, limited support is available for figure display, project management, and multi-user team annotation. In response, we developed TeamTat (https://www.teamtat.org), a web-based annotation tool (local setup available), equipped to manage team annotation projects engagingly and efficiently. TeamTat is a novel tool for managing multi-user, multi-label document annotation, reflecting the entire production life cycle. Project managers can specify annotation schema for entities and relations and select annotator(s) and distribute documents anonymously to prevent bias. Document input format can be plain text, PDF or BioC (uploaded locally or automatically retrieved from PubMed/PMC), and output format is BioC with inline annotations. TeamTat displays figures from the full text for the annotator's convenience. Multiple users can work on the same document independently in their workspaces, and the team manager can track task completion. TeamTat provides corpus quality assessment via inter-annotator agreement statistics, and a user-friendly interface convenient for annotation review and inter-annotator disagreement resolution to improve corpus quality.

scholarly journals Development of a Conceptual Framework for Improving Safety for Pedestrians Using Smartphones While Walking: Challenges and Research Needs

2015 ◽  
Vol 3 ◽  
pp. 3636-3643 ◽  
Author(s):  
Xiangzhen Kong ◽  
Shengwu Xiong ◽  
Zhixing Zhu ◽  
Senwen Zheng ◽  
Guoyang Long
Keyword(s):  
Conceptual Framework ◽  
Research Needs

scholarly journals Design and implementation of observational studies to measure disease burden with a focus on stroke

2017 ◽  
Vol 13 (2) ◽  
pp. 157-165
Author(s):  
George Howard ◽  
Virginia J Howard
Keyword(s):  
Cohort Studies ◽  
Study Design ◽  
Observational Studies ◽  
Disease Burden ◽  
Epidemiological Studies ◽  
Cross Sectional ◽  
Surveillance Studies ◽  
Design And Implementation ◽  
Design Considerations ◽  
Cross Sectional Studies

Observational epidemiological studies have the dual goals of measuring disease burden and assessing the association between exposures and outcomes. This report focuses on the first of these goals and provides an overview of design considerations of commonly used approaches, specifically community surveillance studies, cross-sectional studies, and longitudinal cohort studies. Each of these designs has strengths and weaknesses, with no study design being superior in all cases. Rather, these designs are complementary to achieve a better understanding of the burden of stroke.

scholarly journals A Conceptual Framework for Designing Data Governance for Cloud Computing

2016 ◽  
Vol 94 ◽  
pp. 160-167 ◽  
Author(s):  
Majid Al-Ruithe ◽  
Elhadj Benkhelifa ◽  
Khawar Hameed
Keyword(s):  
Cloud Computing ◽  
Conceptual Framework ◽  
Data Governance
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