A5073404100- Semantic Web and Ontologies
- Service-Oriented Architecture and Web Services
- Advanced Database Systems and Queries
- Biomedical Text Mining and Ontologies
- Natural Language Processing Techniques
- Data Quality and Management
- Advanced Graph Neural Networks
- Topic Modeling
- Geographic Information Systems Studies
- Data Management and Algorithms
- Research Data Management Practices
- Business Process Modeling and Analysis
- Scientific Computing and Data Management
- Web Data Mining and Analysis
- Environmental Monitoring and Data Management
- Machine Learning and ELM
- Fuzzy Logic and Control Systems
- Advanced Computational Techniques and Applications
- Library Science and Information Systems
- Space Science and Extraterrestrial Life
- Intelligent Tutoring Systems and Adaptive Learning
- Text Readability and Simplification
- Smart Agriculture and AI
- Explainable Artificial Intelligence (XAI)
- Graph Theory and Algorithms
Wright State University
2017-2025
Kansas State University
2019-2024
Abstract Knowledge graphs (KGs) are a novel paradigm for the representation, retrieval, and integration of data from highly heterogeneous sources. Within just few years, KGs their supporting technologies have become core component modern search engines, intelligent personal assistants, business intelligence, so on. Interestingly, despite large‐scale availability, they yet to be as successful in realm environmental intelligence. In this paper, we will explain why spatial require special...
Social networks have been widely studied over the last century from multiple disciplines to understand societal issues such as inequality in employment rates, managerial performance, and epidemic spread. Today, these many more can be at global scale thanks digital footprints that we generate when browsing Web or using social media platforms. Unfortunately, scientists often struggle access data primarily because it is proprietary, even shared with privacy guarantees, either no representative...
Knowledge graphs (KGs) are a novel paradigm for the representation, retrieval, and integration of data from highly heterogeneous sources. Within just few years, KGs their supporting technologies have become core component modern search engines, intelligent personal assistants, business intelligence, so on. Interestingly, despite large-scale availability, they yet to be as successful in realm environmental intelligence. In this paper, we will explain why spatial require special treatment, how...
Reusing ontologies for new purposes, or adapting them to use-cases, is frequently difficult. In our experiences, we have found this be the case several reasons: (i) differing representational granularity in and (ii) lacking conceptual clarity potentially reusable ontologies, (iii) lack difficulty of adherence good modeling principles, (iv) a reuse emphasis process support available ontology engineering tooling. order address these concerns, developed Modular Ontology Modeling (MOMo)...
Global challenges such as food supply chain disruptions, public health crises, and natural hazard responses require access to integration of diverse datasets, many which are geospatial. Over the past few years, a growing number (geo)portals have been developed address this need. However, most existing stacked by separated or sparsely connected data "silos" impeding effective consolidation. A new way sharing reusing geospatial is therefore urgently needed. In work, we introduce...
Pattern-based, modular ontologies have several beneficial properties that lend themselves to FAIR data practices, especially as it pertains Interoperability and Reusability. However, developing such has a high upfront cost, e.g. reusing pattern is predicated upon being aware of its existence in the first place. Thus, help overcome these barriers, we developed MODL: ontology design library. MODL curated collection well-documented patterns, drawn from wide variety interdisciplinary use-cases....
Knowledge graphs (KGs) are increasingly utilized for data integration, representation, and visualization. While KG population is critical, it often costly, especially when must be extracted from unstructured text in natural language, which presents challenges, such as ambiguity complex interpretations. Large Language Models (LLMs) offer promising capabilities tasks, excelling language understanding content generation. However, their tendency to ``hallucinate'' can produce inaccurate outputs....
Ontology alignment has taken a critical place for helping heterogeneous resources to interoperate. It been studied over decade, and that time many systems methods have developed by researchers find simple 1:1 equivalence matches between two ontologies. However, very few focus on finding complex correspondences. Even if the are developed, performance of relations still lot room improvement. One reason this limitation may be there applicable benchmarks contain such relationships can raise...
People often value the sensual, celebratory, and health aspects of food, but behind this experience exists many other value-laden agricultural production, distribution, manufacturing, physiological processes that support or undermine a healthy population sustainable future. The complexity such is evident in both every-day food preparation recipes industrial packaging storage, each which depends critically on human machine agents, chemical organismal ingredient references, explicit...
Knowledge graphs are a rapidly growing paradigm and technology stack for integrating large-scale, heterogeneous data in an AI-ready form, i.e., combining with the formal semantics required to understand it. However, toolchains that support synthesis knowledge discovery through information organization, search, filtering, visualization have been developed at pace lagging graph technology. In this paper, we present Explorer, open-source faceted search interface provides environmentally...
As pre-diagnostic technologies are becoming increasingly accessible, using them to improve the quality of care available dementia patients and their caregivers is increasing interest. Specifically, we aim develop a tool for non-invasively assessing task performance in simple gaming application. To address this, have developed Caregiver Assessment Smart Gaming Technology (CAST), mobile application that personalizes traditional word scramble game. Its core functionality uses Fuzzy Inference...