Part A: Theory
Evaluation as a general approach to problem driven mathematical modeling
Multivariate Data Sets for Inference of Order: Some Considerations and Explorations
Measures of Incomparability and of Inequality and their Applications
Measuring structural dissimilarity between finite partial orders
Measuring complexity of partially ordered sets
Part B: Partial Order as Tool to Analyse Composite Indicators
Comparative Knowledge Discovery with Partial Order and Composite Indicator
A software platform Towards a Comparison of Cars - A case study for Handling Ratio-Based Decisions
Part C: New Trends in Partial Order
Coordination of Contrariety and Ambiguity in Comparative Compositional Contexts: Balance of Normalized Definitive Status in Multi-indicator Systems
Partial orders in socio-economics: an applicative challenge for poset theorists or a cultural challenge for social scientists
Part D: Applications
Ranking Hazardous Chemicals with a heuristic Approach to reduce Isolated Objects in Hasse Diagrams
Hasse diagram Technique can further improve the interpretation of results in multi-elemental large-scale biomonitoring studies of atmospheric metal pollution
Application of Partial Orders and Hasse Matrices in Ranking Contaminated sites
Evaluating Ranking Robustness in Multi-indicator uncertain matrices: An application based on Simulation and Global Sensitivity Analysis
Hasse Diagram technique Contributions to Environmental Risk Assessment
Part E: Software Aspects
PARSEC: an R package for poset-based evaluation in socioeconomic sciences
Higher-Order indicator with Rank-Related Clustering in Multi-Indicator Systems
Pyhasse Software Features Applied on the Evaluation of Chemicals in Human Breast Milk Samples in Turkey
Indicator Analyses, What is important - and for what?
PyHasse software for partial order analysis; Scientific background and?description of some modules.