Special issue introduction: Approaching spatial uncertainty visualization to support reasoning and decision making

Mason, Jennifer Smith; Klippel, Alexander; Bleisch, Susanne; Slingsby, Aidan; Deitrick, Stephanie

doi:10.1080/13875868.2016.1138117

Cited by 10 publications

(7 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Visualisation techniques have gained importance in dealing with the increasing amount of earth system data. Since much of this data is geospatially referenced, geographic visualisation techniques are increasingly referred to for processing and communicating data by means of visual representations and interactive visualisation tools (DiBiase 1990;Forni et al 2016;Kraak 2003; J. S. Mason et al 2016;Rhyne et al 2004).…”

Section: Accountabilitymentioning

confidence: 99%

See 1 more Smart Citation

Transformations towards Sustainable Food Systems : Pathways, Governance, and Actors in a Swedish and European Union Context

Eliasson

2023

Linköping Studies in Arts and Sciences

View full text Add to dashboard Cite

Food systems are central to global sustainability, while being complex systems where places and people are intertwined over large distances and at different scales. Transformations towards sustainable food systems have been called for in both research and policy, and Sweden and the European Union have declared high ambitions to act as global leaders in these transformations. While food production in Sweden and the European Union is often portrayed as largely sustainable in a global context, the region is highly dependent on food imports, with relatively large environmental footprints globally.This thesis aims to explore transformative pathways towards sustainability, with a particular focus on sustainable food systems, in a Swedish and European Union context. The thesis specifically studies the following research questions: (1) What constitutes transformations towards sustainability, and in particular sustainable food systems, from the perspectives of Swedish stakeholders, including food system practitioners, and European Union policy frameworks? (2) What roles, responsibilities, and agency do Swedish stakeholders, including food system practitioners and European Union policy frameworks, attribute to different actors? (3) How can interconnections and accountability in global food systems be understood and governed in light of societal transformations towards sustainability? (4) What are the implications for transformative pathways towards sustainability?The thesis builds on four papers that use focus group methodology (PI and PII), involving Swedish stakeholders, including food-system practitioners, analyses of European Green Deal policies (PII and PIII), and quantitative investigation of phosphorus fertiliser use in Brazilian soybean production and related biodiversity impacts (PIV).Four overarching conclusions are drawn from the findings: (I) Shared goals and consensus are emphasised as essential, while a diversity of transformative pathways and understandings of challenges and priorities needs to be recognised, with attention being paid to how specific choices might include and exclude pathways and actors. (II) Emerging shifts in how food is valued open up opportunities for transformative change in which the 'true' cost of food is acknowledged, alongside a recognition of non-economic values of food, which presupposes alignment at the practical, political, and personal levels. (III) The identified pathways comprise public accountability regimes, incentives for more sustainable consumption, regulations to reduce resource use and impacts of food production. (IV) The attribution of accountability to trading operators in the accountability regime proposed by the European Union highlights an extended focus from food production and consumption towards regulating flows and intermediate actors in food systems.

show abstract

Section: Accountabilitymentioning

confidence: 99%

“…This results from the data collection, various steps of manipulation, analyses, visualisation, and human cognitive processing. These layers of complexity can lead to uncertainties in interpretation, reasoning, and decision-making by the user (Mason et al 2016).…”

Section: Accountabilitymentioning

confidence: 99%

Transformations towards Sustainable Food Systems : Pathways, Governance, and Actors in a Swedish and European Union Context

Eliasson

2023

Linköping Studies in Arts and Sciences

View full text Add to dashboard Cite

show abstract

“…The common theme behind the heterogeneous landscape of terminology is that uncertainty is present in all parts of the data-driven scientific research process [38], starting with measurement and data capture, data transformations and processing, data modeling and visualization, and finally human inference and decision making with visual data displays [33], [28]. Uncertainty in data sources can be of locational, temporal, and/or semantic nature [38].…”

Section: Sets and Uncertaintymentioning

confidence: 99%

“…There are many ways to depict data uncertainty [13], [15], [8], [28], [6], [11], [19]. Much empirically-grounded research on the representation of uncertainty exists in geospatial visualization [26], [27], [22], [29], [32], graph visualization [17], statistical visualization [18], and temporal visualization [16], [20], [7].…”

Section: Uncertainty Visualizationmentioning

confidence: 99%

Visualizing Uncertainty in Sets

Tominski¹,

Behrisch²,

Bleisch³

et al. 2023

Preprint

View full text Add to dashboard Cite

“…O'Sullivan and Udwin [4] presented a framework of how to address ignorance statistically by discovering a hypothesized spatial process and assessing observed patterns against it. Mason et al [5] show that smart visualization of spatial ignorance may essentially improve human reasoning and decision-making. Yuan et al [6] argue that geographic data have unique properties, which require special consideration.…”

Section: Introductionmentioning

confidence: 99%

Semantics of Voids within Data: Ignorance-Aware Machine Learning

Terziyan¹,

Nikulin²

2021

IJGI

View full text Add to dashboard Cite

Operating with ignorance is an important concern of geographical information science when the objective is to discover knowledge from the imperfect spatial data. Data mining (driven by knowledge discovery tools) is about processing available (observed, known, and understood) samples of data aiming to build a model (e.g., a classifier) to handle data samples that are not yet observed, known, or understood. These tools traditionally take semantically labeled samples of the available data (known facts) as an input for learning. We want to challenge the indispensability of this approach, and we suggest considering the things the other way around. What if the task would be as follows: how to build a model based on the semantics of our ignorance, i.e., by processing the shape of “voids” within the available data space? Can we improve traditional classification by also modeling the ignorance? In this paper, we provide some algorithms for the discovery and visualization of the ignorance zones in two-dimensional data spaces and design two ignorance-aware smart prototype selection techniques (incremental and adversarial) to improve the performance of the nearest neighbor classifiers. We present experiments with artificial and real datasets to test the concept of the usefulness of ignorance semantics discovery.

show abstract

Special issue introduction: Approaching spatial uncertainty visualization to support reasoning and decision making

Cited by 10 publications

References 16 publications

Transformations towards Sustainable Food Systems : Pathways, Governance, and Actors in a Swedish and European Union Context

Transformations towards Sustainable Food Systems : Pathways, Governance, and Actors in a Swedish and European Union Context

Visualizing Uncertainty in Sets

Semantics of Voids within Data: Ignorance-Aware Machine Learning

Contact Info

Product

Resources

About