scholarly journals KnetMaps: a BioJS component to visualize biological knowledge networks

F1000Research ◽  
2018 ◽  
Vol 7 ◽  
pp. 1651 ◽  
Author(s):  
Ajit Singh ◽  
Christopher J. Rawlings ◽  
Keywan Hassani-Pak
Keyword(s):  
Information Overload ◽  
Interactive Visualization ◽  
Knowledge Networks ◽  
Biological Knowledge ◽  
Single View ◽  
Touch Gestures ◽  
Rich Data ◽  
Effective Visualization ◽  
Visualization Techniques ◽  
Link Component

KnetMaps is a BioJS component for the interactive visualization of biological knowledge networks. It is well suited for applications that need to visualise complementary, connected and content-rich data in a single view in order to help users to traverse pathways linking entities of interest, for example to go from genotype to phenotype. KnetMaps loads data in JSON format, visualizes the structure and content of knowledge networks using lightweight JavaScript libraries, and supports interactive touch gestures. KnetMaps uses effective visualization techniques to prevent information overload and to allow researchers to progressively build their knowledge.

scholarly journals A Novel Framework for Interactive Visualization and Analysis of Hyperspectral Image Data

2016 ◽  
Vol 2016 ◽  
pp. 1-17 ◽  
Author(s):  
Johannes Jordan ◽  
Elli Angelopoulou ◽  
Andreas Maier
Keyword(s):  
Hyperspectral Image ◽  
Imaging Modality ◽  
High Capacity ◽  
Interactive Visualization ◽  
Image Data ◽  
Hyperspectral Image Analysis ◽  
Supervised Segmentation ◽  
Hyperspectral Image Data ◽  
Visualization Techniques ◽  
Application Specific

Multispectral and hyperspectral images are well established in various fields of application like remote sensing, astronomy, and microscopic spectroscopy. In recent years, the availability of new sensor designs, more powerful processors, and high-capacity storage further opened this imaging modality to a wider array of applications like medical diagnosis, agriculture, and cultural heritage. This necessitates new tools that allow general analysis of the image data and are intuitive to users who are new to hyperspectral imaging. We introduce a novel framework that bundles new interactive visualization techniques with powerful algorithms and is accessible through an efficient and intuitive graphical user interface. We visualize the spectral distribution of an image via parallel coordinates with a strong link to traditional visualization techniques, enabling new paradigms in hyperspectral image analysis that focus on interactive raw data exploration. We combine novel methods for supervised segmentation, global clustering, and nonlinear false-color coding to assist in the visual inspection. Our framework coined Gerbil is open source and highly modular, building on established methods and being easily extensible for application-specific needs. It satisfies the need for a general, consistent software framework that tightly integrates analysis algorithms with an intuitive, modern interface to the raw image data and algorithmic results. Gerbil finds its worldwide use in academia and industry alike with several thousand downloads originating from 45 countries.

scholarly journals Towards FAIRer Biological Knowledge Networks Using a Hybrid Linked Data and Graph Database Approach

2018 ◽  
Vol 15 (3) ◽  
Author(s):  
Marco Brandizi ◽  
Ajit Singh ◽  
Christopher Rawlings ◽  
Keywan Hassani-Pak
Keyword(s):  
Scientific Discovery ◽  
Data Access ◽  
Knowledge Networks ◽  
Biological Knowledge ◽  
Graph Databases ◽  
Share Data ◽  
Application Ontology ◽  
Knowledge Graphs ◽  
Genome Scale

Abstract The speed and accuracy of new scientific discoveries – be it by humans or artificial intelligence – depends on the quality of the underlying data and on the technology to connect, search and share the data efficiently. In recent years, we have seen the rise of graph databases and semi-formal data models such as knowledge graphs to facilitate software approaches to scientific discovery. These approaches extend work based on formalised models, such as the Semantic Web. In this paper, we present our developments to connect, search and share data about genome-scale knowledge networks (GSKN). We have developed a simple application ontology based on OWL/RDF with mappings to standard schemas. We are employing the ontology to power data access services like resolvable URIs, SPARQL endpoints, JSON-LD web APIs and Neo4j-based knowledge graphs. We demonstrate how the proposed ontology and graph databases considerably improve search and access to interoperable and reusable biological knowledge (i.e. the FAIRness data principles).

What Does the User Want to See? What do the Data Want to Be?

2009 ◽  
Vol 8 (3) ◽  
pp. 153-166 ◽  
Author(s):  
A. Johannes Pretorius ◽  
Jarke J. Van Wijk
Keyword(s):  
Information Visualization ◽  
User Requirements ◽  
User Centered Design ◽  
Effective Visualization ◽  
Visualization Techniques ◽  
User Centered

Information visualization is a user-centered design discipline. In this article we argue, however, that designing information visualization techniques often requires more than designing for user requirements. Additionally, the data that are to be visualized must also be carefully considered. An approach based on both the user and their data is encapsulated by two questions, which we argue information visualization designers should continually ask themselves: ‘What does the user want to see?’ and ‘What do the data want to be?’ As we show by presenting cases, these two points of departure are mutually reinforcing. By focusing on the data, new insight is gained into the requirements of the user, and vice versa, resulting in more effective visualization techniques.

Bio4j: a high-performance cloud-enabled graph-based data platform

2015 ◽  
Author(s):  
Pablo Pareja-Tobes ◽  
Raquel Tobes ◽  
Marina Manrique ◽  
Eduardo Pareja ◽  
Eduardo Pareja-Tobes
Keyword(s):  
High Performance ◽  
Cost Effective ◽  
Data Access ◽  
Biological Data ◽  
Biological Knowledge ◽  
Graph Models ◽  
Domain Specific ◽  
Data Querying ◽  
Knowledge Intensive ◽  
Rich Data

Background. Next Generation Sequencing and other high-throughput technologies have brought a revolution to the bioinformatics landscape, by offering sheer amounts of data about previously unaccessible domains in a cheap and scalable way. However, fast, reproducible, and cost-effective data analysis at such scale remains elusive. A key need for achieving it is being able to access and query the vast amount of publicly available data, specially so in the case of knowledge-intensive, semantically rich data: incredibly valuable information about proteins and their functions, genes, pathways, or all sort of biological knowledge encoded in ontologies remains scattered, semantically and physically fragmented. Methods and Results. Guided by this, we have designed and developed Bio4j. It aims to offer a platform for the integration of semantically rich biological data using typed graph models. We have modeled and integrated most publicly available data linked with proteins into a set of interdependent graphs. Data querying is possible through a data model aware Domain Specific Language implemented in Java, letting the user write typed graph traversals over the integrated data. A ready to use cloud-based data distribution, based on the Titan graph database engine is provided; generic data import code can also be used for in-house deployment. Conclusion. Bio4j represents a unique resource for the current Bioinformatician, providing at once a solution for several key problems: data integration; expressive, high performance data access; and a cost-effective scalable cloud deployment model.

Three Dimensional Visualization Technologies for Water Conservancy Works

2012 ◽  
Vol 263-266 ◽  
pp. 1809-1812
Author(s):  
Nan Xie
Keyword(s):  
Field Data ◽  
3D Visualization ◽  
Three Dimensional ◽  
Interactive Visualization ◽  
Simulation System ◽  
Hydraulic Engineering ◽  
Visual Simulation ◽  
Complex Field ◽  
Water Conservancy ◽  
Visualization Techniques

The advances in the study of three dimensional (3D) interactive visualization techniques in hydraulic engineering are reviewed. Main contents, key technologies and the difficulties with their solutions in the application of 3D interactive visualization techniques to water conservancy works are analyzed and summarized. A true 3D visual simulation system prototype for large-scale water conservancy project was built. A framework for building 3D visual simulation system for complex field data in hydraulic engineering is presented to illustrate potentiality and effectiveness of 3D visualization techniques for hydraulic engineering. Aspects like navigation and presentations of complex field data with spatial dependence are presented.

scholarly journals Use Of Bayesian Networks And Augmented Reality To Reliability Testing Of Complex Technical Objects

2015 ◽  
Vol 35 (1) ◽  
pp. 179-190
Author(s):  
Tomasz Wójcicki
Keyword(s):  
Augmented Reality ◽  
Probability Distribution ◽  
Information Technologies ◽  
Total Probability ◽  
Reliability Testing ◽  
Basic Functions ◽  
Modern Information ◽  
Effective Visualization ◽  
Visualization Techniques ◽  
Data Processing Methods

Abstract This paper presents a methodology developed to support the tests of reliability of complex technical objects. The presented methodology covers the use of modern information technologies in the form of algorithmic models and effective visualization techniques in the form of augmented reality. The possibility of using a probabilistic Bayesian network. The method of determining the probabilities for specific nodes, and the total probability distribution of graph structures are presented. The structure of the model and its basic functions are shown. The results of the verification work for connecting data processing methods and visualization techniques based on augmented reality are presented.

scholarly journals NETME: on-the-fly knowledge network construction from biomedical literature

2022 ◽  
Vol 7 (1) ◽  
Author(s):  
Alessandro Muscolino ◽  
Antonio Di Maria ◽  
Rosaria Valentina Rapicavoli ◽  
Salvatore Alaimo ◽  
Lorenzo Bellomo ◽  
...  
Keyword(s):  
Knowledge Discovery ◽  
Biological Networks ◽  
Biomedical Literature ◽  
Knowledge Networks ◽  
Knowledge Network ◽  
Biological Knowledge ◽  
Web Interface ◽  
Network Construction ◽  
Biological Literature

Abstract Background The rapidly increasing biological literature is a key resource to automatically extract and gain knowledge concerning biological elements and their relations. Knowledge Networks are helpful tools in the context of biological knowledge discovery and modeling. Results We introduce a novel system called NETME, which, starting from a set of full-texts obtained from PubMed, through an easy-to-use web interface, interactively extracts biological elements from ontological databases and then synthesizes a network inferring relations among such elements. The results clearly show that our tool is capable of inferring comprehensive and reliable biological networks.

Meta-Knowledge Based Approach for an Interactive Visualization of Large Amounts of Association Rules

2009 ◽  
pp. 200-223
Author(s):  
Sadok Ben Yahia ◽  
Olivier Couturier ◽  
Tarek Hamrouni ◽  
Engelbert Mephu Nguifo
Keyword(s):  
Data Mining ◽  
Association Rules ◽  
Efficient Solution ◽  
Explicit Knowledge ◽  
Interactive Visualization ◽  
Information Loss ◽  
Compact Representation ◽  
Knowledge Based ◽  
Extraction Step ◽  
Visualization Techniques

Providing efficient and easy-to-use graphical tools to users is a promising challenge of data mining, especially in the case of association rules. These tools must be able to generate explicit knowledge and, then, to present it in an elegant way. Visualization techniques have shown to be an efficient solution to achieve such a goal. Even though considered as a key step in the mining process, the visualization step of association rules received much less attention than that paid to the extraction step. Nevertheless, some graphical tools have been developed to extract and visualize association rules. In those tools, various approaches are proposed to filter the huge number of association rules before the visualization step. However both data mining steps (association rule extraction and visualization) are treated separately in a one way process. Recently different approaches have been proposed that use meta-knowledge to guide the user during the mining process. Standing at the crossroads of Data Mining and Human-Computer Interaction, those approaches present an integrated framework covering both steps of the data mining process. This chapter describes and discusses such approaches. Two approaches are described in details: the first one builds a roadmap of compact representation of association rules from which the user can explore generic bases of association rules and derive, if desired, redundant ones without information loss. The second approach clusters the set of association rules or its generic bases, and uses a fisheye view technique to help the user during the mining of association rules. Generic bases with their links or the associated clusters constitute the meta-knowledge used to guide the interactive and cooperative visualization of association rules.

A Method on Model-Driven Development of Interactive Information Visualization

2014 ◽  
Vol 543-547 ◽  
pp. 2992-2995
Author(s):  
Yang Hu
Keyword(s):  
Information Visualization ◽  
Interactive Visualization ◽  
Effective Solution ◽  
General Development ◽  
Model Driven Development ◽  
Development Method ◽  
Model Driven ◽  
General Support ◽  
Visualization Techniques

Design and realize application oriented field of interactive visualization is very difficult. Lack of general development method and toolkit, provide a general support of administrative levels, network and multi-dimensional data for non-specialist users, provide a general support for various visualization techniques and interactive techniques, and provide a general support for information visualization tasks, specific to this problem, this paper presents a model driven development method for interactive information visualization-Daisy. This method can provide an effective solution for the general support solution of the development for interactive information visualization.

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