Toward Visualization in Policy Modeling

Kohlhammer, Jörn; Nazemi, Kawa; Ruppert, Tobias; Burkhardt, Dirk

doi:10.1109/mcg.2012.107

Cited by 31 publications

(14 citation statements)

References 3 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Though we agree with Kohlhammer et al (2012) that visualization and visual analytics are vital for informed decision-making and policy modeling in a highly complex information environment overloaded with data and information, we do not advocate using network visualizations as the only evidence for decision-making or policy setting. The literacy of decision makers in visual analytics and network metrics is just beginning to emerge.…”

Section: Limitationsmentioning

confidence: 65%

Relational capital for shared vision in innovation ecosystems

et al. 2015

View full text Add to dashboard Cite

This paper provides an evidence-based approach to understanding the relationship infrastructure of spatially defined innovation ecosystems in three metropolitan areas. With the Triple Helix framework, the ecosystem perspective, and shared vision for transformation initiatives, we explore relationships as structure in the metropolitan areas of Austin, TX; Minneapolis, MN; and Paris, France. Network metrics are interpreted as indicators of relational capital; and network visualizations reveal distinct patterns of relational space that structure business ecosystems at the enterprise, growth, and startup levels in each geographic area. We illustrate that network metrics, relationship indicators, and their visualization can be valuable resources for quantitatively and qualitatively investigating and analyzing the complexities of engagement, agility, vitality, linking, and embeddedness in innovation ecosystems. We suggest that data-driven indicators of relational capital may be used for network orchestration, evidence-based policy, and the development of shared vision in spatially defined business ecosystems.Keywords: Ecosystem; Networks; Innovation; Business; Metropolitan; Relationships; Visualization Spanish: El capital relacional por una visión compartida en los ecosistemas de innovación. Resumen: Este artículo ofrece un enfoque basado en evidencias que permite comprender la infraestructura de relaciones en los ecosistemas de innovación de tres áreas metropolitanas. Empleando el marco de trabajo de Triple Hélice, la perspectiva de ecosistema y una visión compartida por iniciativas de transformación, exploramos las relaciones, entendidas como estructura, en las áreas metropolitanas de Austin (Texas, EE.UU.), Minneapolis (Minnesota, EE.UU.) y París (Francia). Los datos de red son interpretados como indicadores de capital relacional y las visualizaciones de red revelan patrones claros de espacio relacional que estructuran los ecosistemas de empresas, crecimiento y niveles de startup en cada área geográfica. Mostramos que las métricas de red, los indicadores de relación y sus visualizaciones pueden ser valiosos recursos a la hora de investigar y analizar tanto cuantitativa como cualitativamente la diversidad de compromiso, agilidad, vitalidad, conexión e implantación en los ecosistemas de innovación. Sugerimos que los indicadores de datos relacionados con el capital relacional pueden ser empleados para la orquestación de redes, políticas de evidencia y el desarrollo de visiones compartidas en ecosistemas empresariales delimitados espacialmente. Portuguese: Capital Relacional para uma visão partilhada dos ecossistemas de inovação. Resumo: Esse artigo fornece uma abordagem baseada na evidência para compreender o relacionamento entre infraestrutura e espacialidade definidas pelos ecossistemas de inovação em três áreas metropolitanas. Com a estrutura teórica da Hélice Tríplice, a perspectiva de ecossistema e uma visão compartilhada para a transformação de iniciativas nós exploramos os relacionamentos como uma estru...

show abstract

Section: Limitationsmentioning

confidence: 65%

Relational capital for shared vision in innovation ecosystems

et al. 2015

View full text Add to dashboard Cite

show abstract

“…In terms of remote area electrification planning, both types of infrastructure are vital. Accessibility to social infrastructure is considered an influential factor in remote area development decisions [16,35]. Improving electricity in remote areas can help address gaps in service delivery and social infrastructure.…”

Section: Infrastructurementioning

confidence: 99%

Data Visualisation for Remote Area Electrification Decision-Making

Alshardy

Goodwin

Liebman

2021

Proceedings of the Twelfth ACM International Conference on Future Energy Systems

View full text Add to dashboard Cite

Energy poverty is a key challenge in many developing countries. Given that energy poverty contributes to a variety of social issues, the governments of these countries have aimed to bring electricity to as many remote areas as possible. However, this presents challenges because of the significant uncertainties arising from the geographic, social, demographic, economic and political characteristics that must be considered. These characteristics must be clearly communicated in such a way that supports the decision-making process. Using Indonesia as a case study, this research interviews experts in the field and seeks to cohesively integrate various visualisation techniques that may facilitate informed decision-making regarding remote area electrification.

show abstract

“…Kohlhammer et al proposed a differentiation of visualizations in context of policy modeling [KNRB12]. Their differentiation proposes a classification based on the role of human and machine in the data processing pipeline.…”

Section: The Early and Most Influential Definition Of Visual Analytics Was Proposed By Thomas And Cook [Tc05]mentioning

confidence: 99%

Adaptive Semantics Visualization

Nazemi¹

2016

Studies in Computational Intelligence

Self Cite

View full text Add to dashboard Cite

Human access to the increasing amount of information and data plays an essential role for the professional level and also for everyday life. While information visualization has developed new and remarkable ways for visualizing data and enabling the exploration process, adaptive systems focus on users' behavior to tailor information for supporting the information acquisition process. Recent research on adaptive visualization shows promising ways of synthesizing these two complementary approaches and make use of the surpluses of both disciplines. The emerged methods and systems aim to increase the performance, acceptance, and user experience of graphical data representations for a broad range of users. Although the evaluation results of the recently proposed systems are promising, some important aspects of information visualization are not considered in the adaptation process. The visual adaptation is commonly limited to change either visual parameters or replace visualizations entirely. Further, no existing approach adapts the visualization based on data and user characteristics. Other limitations of existing approaches include the fact that the visualizations require training by experts in the field. VII VIIIFinally, I thank my loved ones -my wife Mariam, my son Kian, my brothers and parents for their unlimited support, love, and patience.

show abstract

Toward Visualization in Policy Modeling

Abstract: This article looks at the current and future roles of information visualization, semantics visualization, and visual analytics in policy modeling. Many experts believe that you can't overestimate visualization's role in this respect.

Cited by 31 publications

References 3 publications

Relational capital for shared vision in innovation ecosystems

Relational capital for shared vision in innovation ecosystems

Data Visualisation for Remote Area Electrification Decision-Making

Adaptive Semantics Visualization

Contact Info

Product

Resources

About