VisFlow: A Visual Database Integration and Workflow Querying System

Mou, Xin; Jamil, Hasan M.; Ma, Xiaogang

doi:10.1109/icde.2017.204

Cited by 7 publications

(2 citation statements)

References 6 publications

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“…Many visualization techniques have already been developed, such as scatter plots, box plots, histograms, stem-and-lead plots, and more. For EDA in cross-disciplinary studies, other types of visualization techniques may also be applied, such as mind maps [18], conceptual maps [19], and workflow visualizations [20]. Through the usage of those visualization techniques, researchers from different backgrounds can quickly obtain an overview of the subject under study, gain insights about the datasets, and discuss hypotheses for the focused work of the next step [21,22].…”

Section: Introductionmentioning

confidence: 99%

Using Visual Exploratory Data Analysis to Facilitate Collaboration and Hypothesis Generation in Cross-Disciplinary Research

Hummer

Golden

et al. 2017

IJGI

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Massive open data resources are changing the way that people do science. To make use of those data resources, data science methods and technology can be leveraged by stakeholders of various disciplines. The objective of this paper is to present our experience of using visual exploratory data analysis as a method to facilitate collaboration and hypothesis generation in geoscience research. The research team consisted of both geoscientists and computer scientists. A use case-driven, iterative approach was applied to create a collaborative and communicative environment. Through several rounds of use case analysis and technological development, a data visualization pilot system was created for studying the co-relationships between chemical elements and mineral species. The exploratory data analyses conducted in those use case studies led to several research hypotheses for future work. This research illustrates the usefulness of exploratory data analysis for hypothesis generation in a data science process. Although the presented project is in geoscience, the discussed method and experience can also be translated into other disciplines.

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Section: Introductionmentioning

confidence: 99%

Using Visual Exploratory Data Analysis to Facilitate Collaboration and Hypothesis Generation in Cross-Disciplinary Research

Hummer

Golden

et al. 2017

IJGI

Self Cite

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“…In our own lab, we are focused on developing smart declarative querying and workflow engines for distributed and heterogenous scientific databases. We have developed a declarative query language for data integration called BioFlow [38,39] based on which we have developed two visual interfaces called VizBuilder [33,28] and VisFlow [55,53,54] to support distributed workflow queries for Life Sciences data management and querying system called the LifeDB [9]. To complement LifeDB, we have also develop an ID mapping database called the MapBase [35] and phylogenetic database PhyloBase [37,36].…”

Section: Related Researchmentioning

confidence: 99%

Knowledge Rich Natural Language Queries over Structured Biological Databases

Jamil

2017

Proceedings of the 8th ACM International Conference on Bioinformatics, Computational Biology,and Health Informatics

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Increasingly, keyword, natural language and NoSQL queries are being used for information retrieval from traditional as well as non-traditional databases such as web, document, image, GIS, legal, and health databases. While their popularity are undeniable for obvious reasons, their engineering is far from simple. In most part, semantics and intent preserving mapping of a well understood natural language query expressed over a structured database schema to a structured query language is still a difficult task, and research to tame the complexity is intense. In this paper, we propose a multi-level knowledge-based middleware to facilitate such mappings that separate the conceptual level from the physical level. We augment these multi-level abstractions with a concept reasoner and a query strategy engine to dynamically link arbitrary natural language querying to well defined structured queries. We demonstrate the feasibility of our approach by presenting a Datalog based prototype system, called BioSmart, that can compute responses to arbitrary natural language queries over arbitrary databases once a syntactic classification of the natural language query is made.

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Crowd enabled curation and querying of large and noisy text mined protein interaction data

Jamil

Sadri

2017

Distrib Parallel Databases

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VisFlow: A Visual Database Integration and Workflow Querying System

Cited by 7 publications

References 6 publications

Using Visual Exploratory Data Analysis to Facilitate Collaboration and Hypothesis Generation in Cross-Disciplinary Research

Using Visual Exploratory Data Analysis to Facilitate Collaboration and Hypothesis Generation in Cross-Disciplinary Research

Knowledge Rich Natural Language Queries over Structured Biological Databases

Crowd enabled curation and querying of large and noisy text mined protein interaction data

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