Databases and Information Systems Commons^™

Human Subject Studies For The Alignment Of Llm-As-A-Judge Evaluation Metric For Science News, Gabriel Vega Osborne

Knowledge and Creativity Expo

Science news has become an important vehicle to disseminate scientific breakthroughs, discoveries, and technological innovations. With the advancement of large language models and related AI models, it is possible to automatically generate science news from scientific papers, extending the reader population from domain scientists to a broader scope. However, how to evaluate the quality of the generated news warrants research. Traditional token based metrics have been shown to fail to evaluate the semantics and nuances of science news. Inspired by the fact that a major goal of science news is to educate readers with new knowledge, we thus propose knowledge …

Exploring Marshall–Olkin Models Through Bibliometric And Topic Modeling Approaches Uses Latent Dirichlet Allocation (1981-2025): A Study Based On Scopus Data, Humberto Llinás, Brian Llinás, Carlos López, Daniela Nuñez

Computer Science Faculty Publications

The Marshall–Olkin family of distributions has gained increasing attention in fields such as reliability engineering, survival analysis, financial risk modeling, and actuarial science because of its flexibility in modeling dependence among events and its wide range of extensions. Despite its growing relevance, a systematic understanding of how research on Marshall–Olkin models has evolved over time is still limited. This study addresses this gap by combining bibliometric techniques with topic modeling to analyze the structure and evolution of the scientific literature on Marshall–Olkin models. The analysis includes all 266 peer-reviewed publications on Marshall–Olkin models indexed in Scopus between 1981 and 2025. …

Open Scholarly Information Systems: Status Quo, Challenges, Opportunities, Hannah Bast, Guillaume Cabanac, Paolo Manghi, Jian Wu, Marcel R. Ackermann

Computer Science Faculty Publications

Over the past 30 years, a rich ecosystem of scholarly information systems has developed that openly provide their services to the scientific community. These systems include aggregators of bibliographic metadata (e.g., DBLP, OpenCitations, OpenAIRE Graph, OpenAlex, ORKG, Semantic Scholar, CiteSeerX, and CORE); publication, data, and software repositories (e.g., Arxiv.org, Figshare, Zenodo, Software Heritage, and Dataverse); and PID authorities (e.g., ORCID, ROR, Crossref, and DataCite). This interdisciplinary Dagstuhl Seminar "Open Scholarly Information Systems: Status Quo, Challenges, Opportunities" (25381) was the first of its kind to bring together practitioners from this ecosystem, as well as researchers investigating related questions or relying on …

Digital Thread: Bridging Macro–Micro Services In System-Of-Systems, Joshit Mohanty

Graduate Student Government Association Research Conference

Organizations and industries increasingly rely on distributed services in decentralized environments—ranging from large-scale, system-of-system architectures to fine-grained, agent-based microservices. While this distributed paradigm offers flexibility and innovation, it presents critical challenges such as interoperability gaps, inconsistent data formats, and a lack of holistic oversight. Traditional integration approaches, including ad-hoc middleware or enterprise service buses, tend to solve these issues reactively. As a result, technical debt accumulates, stakeholder misalignments persist, and scaling to new demands becomes complex.

This research proposes digital thread (DT) as the unifying framework to create an authoritative source of truth: a continuous flow of information across the …

Meta-Clustering For Specialized Language Models: Enhancing Contextual Adaptation And Mitigating Hallucinations In Diverse Healthcare Environments, Joshit Mohanty, Vaishali Vaishali, Sandeep Kumar Nayak, Sumit Lahiri

Graduate Student Government Association Research Conference

Large Language Models (LLMs) have significantly advanced conversational AI by enabling dialogic information-seeking and task execution across diverse domains. However, their extensive parameters and broad domain scope lead to “data hallucinations.” These shortcomings are particularly evident in dynamic and diverse environments like India’s healthcare sector, where myriad languages, regional practices, and cultural nuances demand specialized, localized expertise rather than one-size-fits-all generalist models. This paper introduces a meta-clustering framework that integrates Distilled Language Models (DLMs) and Small/Specialized Language Models (SLMs) with meta-learning principles to address these limitations. By drawing on evidence from works such as MedHalu and Med-HALT, the framework seeks …

Tamos: Task-Aware Multi-Agent Orchestrator System, Joshit Mohanty, Sandeep Kumar Nayak, Sumit Lahiri

Graduate Student Government Association Research Conference

Large language models (LLMs) are increasingly at the core of multi-agent systems (MAS). However, the high resource demand, error propagation, and lack of adaptive evaluation mechanisms pose significant challenges in deploying these agentic solutions at scale. To address these concerns, this research proposes a Task-Aware Multi-Agent Orchestrator System designed to refine the agentic framework, categorizing tasks autonomously, assigning specialized evaluation datasets, and balancing token usage against functional effectiveness. This approach underscores robust data management, including AsyncHow, Mosaic AI, and Synthetic Preference Optimization (PO) corpora. Each dataset targets specific dimensions of agent performance, such as dynamic task decomposition and tool integration …

A Global Application Programming Interface-Enabled Earthquake Ground Motion Relational Database For Engineering Applications, Tristan E. Buckreis, Chukwuebuka C. Nweke, Pengfei Wang, Scott J. Brandenberg, Maria E. Ramos-Sepúlveda, Rashid Shams, Shako Mohammed, Renmin Pretell, Silvia Mazzoni, Paolo Zimmaro, Jonathan P. Steward

Civil & Environmental Engineering Faculty Publications

We present a application programming interface (API)-enabled relational database of global earthquake ground motion intensity measures, associated metadata, and processed time-series data. Raw ground motion records were processed by the authors using either manual or semi-automated processing procedures, and every processed record has passed a quality review by a trained analyst. Computed intensity measures include peak acceleration and velocity, pseudo-spectral acceleration response spectra, cumulative absolute velocity, Arias Intensity, and Fourier amplitude spectra. The processed time-series data, associated metadata, and ground motion intensity measures were organized into a web-served relational database consisting of 32 tables connected by primary/foreign key pairs. Ground …

Coming Back Differently: An Exploratory Case Study Of Near Death Experiences Of Webpages, Lesley Frew, Michael L. Nelson, Michele Weigle

Computer Science Faculty Publications

In this case study, we use web archives to analyze 8,824 webpages that were taken offline and subsequently put back online, thus experiencing a “near death experience.” We enumerate the stages of a webpage’s near death experience, including the change from a successful HTTP status code to non-successful and back, the intermediate stage with markers such as an under construction banner, and an analysis of how the pages came back differently.

Digital Humanities: Using Computational Methods On Literature To Understand Human-Water Relations, Ariel Yang

Cybersecurity Undergraduate Research Showcase

By using computational techniques to analyze literature, deeper insights can be gained into human-water relationships across different historical and cultural contexts. Natural Language Processing (NLP) and other data science methods can explore applications of traditional ecological knowledge (TEK) and underlying emotions or beliefs in literature to help understand sustainability. Protecting this sensitive cultural data through ethical applications can further secure future implementations of policies, urban planning, and environmental relationships.

A Design Science Approach To Investigating Decentralized Identity Technology, Janelle Krupicka

Cybersecurity Undergraduate Research Showcase

The internet needs secure forms of identity authentication to function properly, but identity authentication is not a core part of the internet’s architecture. Instead, approaches to identity verification vary, often using centralized stores of identity information that are targets of cyber attacks. Decentralized identity is a secure way to manage identity online that puts users’ identities in their own hands and that has the potential to become a core part of cybersecurity. However, decentralized identity technology is new and continually evolving, which makes implementing this technology in an organizational setting challenging. This paper suggests that, in the future, decentralized identity …

What Students Have To Say On Data Privacy For Educational Technology, Stephanie Choi

Cybersecurity Undergraduate Research Showcase

The literature on data privacy in terms of educational technology is a growing area of study. The perspective of educators has been captured extensively. However, the literature on students’ perspectives is missing, which is what we explore in this paper. We use a pragmatic qualitative approach with an experiential lens to capture students’ attitudes towards data privacy in terms of educational technology. We identified preliminary, common themes that appeared in the survey responses. The paper concludes by calling for more research on how students perceive data privacy in terms of educational technology.

It Is Not Only About Having Good Attitudes: Factor Exploration Of The Attitudes Toward Security Recommendations, Miguel A. Toro-Jarrin, Pilar Pazos, Miguel A. Padilla

Engineering Management & Systems Engineering Faculty Publications

Numerous factors determine information security-related actions (IS-actions) in the workplace. Attitudes toward following security rules and recommendations and attitudes toward specific IS actions determine intentions associated with those actions. IS research has examined the role of the instrumental aspect of attitudes. However, authors argue that attitudes toward a behavioral object are a multidimensional construct. We examined the dimensionality of attitudes toward security recommendations, hypothesized its multidimensional nature, and developed a new scale [attitudes toward security recommendations (ASR scale)]. The results indicated the multidimensional nature of attitudes toward security recommendations supporting our hypothesis. The results revealed two dimensions corresponding to the …

A New Cache Replacement Policy In Named Data Network Based On Fib Table Information, Mehran Hosseinzadeh, Neda Moghim, Samira Taheri, Nasrin Gholami

VMASC Publications

Named Data Network (NDN) is proposed for the Internet as an information-centric architecture. Content storing in the router’s cache plays a significant role in NDN. When a router’s cache becomes full, a cache replacement policy determines which content should be discarded for the new content storage. This paper proposes a new cache replacement policy called Discard of Fast Retrievable Content (DFRC). In DFRC, the retrieval time of the content is evaluated using the FIB table information, and the content with less retrieval time receives more discard priority. An impact weight is also used to involve both the grade of retrieval …

Short: Can Citations Tell Us About A Paper's Reproducibility? A Case Study Of Machine Learning Papers, Rochana R. Obadage, Sarah M. Rajtmajer, Jian Wu

Computer Science Faculty Publications

The iterative character of work in machine learning (ML) and artificial intelligence (AI) and reliance on comparisons against benchmark datasets emphasize the importance of reproducibility in that literature. Yet, resource constraints and inadequate documentation can make running replications particularly challenging. Our work explores the potential of using downstream citation contexts as a signal of reproducibility. We introduce a sentiment analysis framework applied to citation contexts from papers involved in Machine Learning Reproducibility Challenges in order to interpret the positive or negative outcomes of reproduction attempts. Our contributions include training classifiers for reproducibility-related contexts and sentiment analysis, and exploring correlations between …

Retrogressive Document Manipulation Of Us Federal Environmental Websites, Lesley Frew, Michael L. Nelson, Michele C. Weigle

Computer Science Faculty Publications

Changes made to webpages can affect their retrievability. Often this is done with the intention of increasing the page's search engine ranking to improve overall access to information on the page. The Environmental Data and Governance Initiative (EDGI) created a dataset that describes changes on US federal environmental webpages between 2016 and 2020. EDGI noted that many environmental terms were deleted from the pages, but without user data, claims that page retrievability and public information access were lowered are only anecdotal. The Open Resource for Click Analysis in Search (ORCAS) dataset was created during the same time frame, from 2017 …

A Review Of Threat Vectors To Dna Sequencing Pipelines, Tyler Rector

Cybersecurity Undergraduate Research Showcase

Bioinformatics is a steadily growing field that focuses on the intersection of biology with computer science. Tools and techniques developed within this field are quickly becoming fixtures in genomics, forensics, epidemiology, and bioengineering. The development and analysis of DNA sequencing and synthesis have enabled this significant rise in demand for bioinformatic tools. Notwithstanding, these bioinformatic tools have developed in a research context free of significant cybersecurity threats. With the significant growth of the field and the commercialization of genetic information, this is no longer the case. This paper examines the bioinformatic landscape through reviewing the biological and cybersecurity threats within …

Fair Signposting Profile, Herbert Van De Sompel, Martin Klein, Shawn Jones, Michael L. Nelson, Simeon Warner, Anusuriya Devaraju, Robert Huber, Wilko Steinhoff, Vyacheslav Tykhonov, Luc Boruta, Enno Meijers, Stian Soiland-Reyes, Mark Wilkonson

Computer Science Faculty Publications

[First paragraph] This page details concrete recipes that platforms that host research outputs (e.g. data repositories, institutional repositories, publisher platforms, etc.) can follow to implement Signposting, a lightweight yet powerful approach to increase the FAIRness of scholarly objects.

A Study Of The Collection And Sharing Of Student Data With Virginia Universities, Titus Voell

Cybersecurity Undergraduate Research Showcase

Data collection is a vital component in any organization in regards to keeping track of user activity, gaining statistics and improving the user experience, and user identification. While the underlying basis of data collection is understandable, the use of this data has to be closely regulated and documented. In many cases, the VCDPA (Virginia Consumer Data Protection Act) outlines the guidelines for data use, data controller responsibilities, and limitations however nonprofit organizations are exempt from compliance. Colleges and universities, although still held to some degree of limitation, range in permissiveness with what data they choose to collect and retain but …

Assessing Spurious Correlations In Big Search Data, Jesse T. Richman, Ryan J. Roberts

Political Science & Geography Faculty Publications

Big search data offers the opportunity to identify new and potentially real-time measures and predictors of important political, geographic, social, cultural, economic, and epidemiological phenomena, measures that might serve an important role as leading indicators in forecasts and nowcasts. However, it also presents vast new risks that scientists or the public will identify meaningless and totally spurious ‘relationships’ between variables. This study is the first to quantify that risk in the context of search data. We find that spurious correlations arise at exceptionally high frequencies among probability distributions examined for random variables based upon gamma (1, 1) and Gaussian random …

Progenitor Cell Isolation From Mouse Epididymal Adipose Tissue And Sequencing Library Construction, Qianglin Liu, Chaoyang Li, Yuxia Li, Leshan Wang, Xujia Zhang, Buhao Deng, Peidong Gao, Mohammad Shiri, Fozi Alkaifi, Junxing Zhao, Jacqueline M. Stephens, Constantine A. Simintiras, Joseph Francis, Jiangwen Sun, Xing Fu

Computer Science Faculty Publications

Here, we present a protocol to isolate progenitor cells from mouse epididymal visceral adipose tissue and construct bulk RNA and assay for transposase-accessible chromatin with sequencing (ATAC-seq) libraries. We describe steps for adipose tissue collection, cell isolation, and cell staining and sorting. We then detail procedures for both ATAC-seq and RNA sequencing library construction. This protocol can also be applied to other tissues and cell types directly or with minor modifications.

For complete details on the use and execution of this protocol, please refer to Liu et al. (2023).¹

*¹ Liu, Q., Li, C., Deng, B., Gao, P., …

Smart Manufacturing—Theories, Methods, And Applications, Zhuming Bi, Lida Xu, Puren Ouyang

Information Technology & Decision Sciences Faculty Publications

(First paragraph) Smart manufacturing (SM) distinguishes itself from other system paradigms by introducing ‘smartness’ as a measure to a manufacturing system; however, researchers in different domains have different expectations of system smartness from their own perspectives. In this Special Issue (SI), SM refers to a system paradigm where digital technologies are deployed to enhance system smartness by (1) empowering physical resources in production, (2) utilizing virtual and dynamic assets over the internet to expand system capabilities, (3) supporting data-driven decision making at all domains and levels of businesses, or (4) reconfiguring systems to adapt changes and uncertainties in dynamic environments. …

Did They Really Tweet That?, Caleb Bradford, Michael L. Nelson (Mentor)

Computer & Information Science: Research Experiences for Undergraduates in Disinformation Detection and Analytics

No abstract provided.

Machine Learning In Requirements Elicitation: A Literature Review, Cheligeer Cheligeer, Jingwei Huang, Guosong Wu, Nadia Bhuiyan, Yuan Xu, Yong Zeng

Engineering Management & Systems Engineering Faculty Publications

A growing trend in requirements elicitation is the use of machine learning (ML) techniques to automate the cumbersome requirement handling process. This literature review summarizes and analyzes studies that incorporate ML and natural language processing (NLP) into demand elicitation. We answer the following research questions: (1) What requirement elicitation activities are supported by ML? (2) What data sources are used to build ML-based requirement solutions? (3) What technologies, algorithms, and tools are used to build ML-based requirement elicitation? (4) How to construct an ML-based requirements elicitation method? (5) What are the available tools to support ML-based requirements elicitation methodology? Keywords …

The State Of The Art Of Information Integration In Space Applications, Zhuming Bi, K. L. Yung, Andrew W.H. Ip., Yuk Ming Tang, Chris W.J. Zhang, Li Da Xu

Information Technology & Decision Sciences Faculty Publications

This paper aims to present a comprehensive survey on information integration (II) in space informatics. With an ever-increasing scale and dynamics of complex space systems, II has become essential in dealing with the complexity, changes, dynamics, and uncertainties of space systems. The applications of space II (SII) require addressing some distinctive functional requirements (FRs) of heterogeneity, networking, communication, security, latency, and resilience; while limited works are available to examine recent advances of SII thoroughly. This survey helps to gain the understanding of the state of the art of SII in sense that (1) technical drivers for SII are discussed and …

Formal Modeling And Verification Of A Blockchain-Based Crowdsourcing Consensus Protocol, Hamra Afzaal, Muhammad Imran, Muhammad Umar Janjua, Sarada Prasad Gochhayat

VMASC Publications

Crowdsourcing is an effective technique that allows humans to solve complex problems that are hard to accomplish by automated tools. Some significant challenges in crowdsourcing systems include avoiding security attacks, effective trust management, and ensuring the system’s correctness. Blockchain is a promising technology that can be efficiently exploited to address security and trust issues. The consensus protocol is a core component of a blockchain network through which all the blockchain peers achieve an agreement about the state of the distributed ledger. Therefore, its security, trustworthiness, and correctness have vital importance. This work proposes a Secure and Trustworthy Blockchain-based Crowdsourcing (STBC) …

Streaminghub: Interactive Stream Analysis Workflows, Yasith Jayawardana, Vikas G. Ashok, Sampath Jayarathna

Computer Science Faculty Publications

Reusable data/code and reproducible analyses are foundational to quality research. This aspect, however, is often overlooked when designing interactive stream analysis workflows for time-series data (e.g., eye-tracking data). A mechanism to transmit informative metadata alongside data may allow such workflows to intelligently consume data, propagate metadata to downstream tasks, and thereby auto-generate reusable, reproducible analytic outputs with zero supervision. Moreover, a visual programming interface to design, develop, and execute such workflows may allow rapid prototyping for interdisciplinary research. Capitalizing on these ideas, we propose StreamingHub, a framework to build metadata propagating, interactive stream analysis workflows using visual programming. We conduct …

Visual Descriptor Extraction From Patent Figure Captions: A Case Study Of Data Efficiency Between Bilstm And Transformer, Xin Wei, Jian Wu, Kehinde Ajayi, Diane Oyen

Computer Science Faculty Publications

Technical drawings used for illustrating designs are ubiquitous in patent documents, especially design patents. Different from natural images, these drawings are usually made using black strokes with little color information, making it challenging for models trained on natural images to recognize objects. To facilitate indexing and searching, we propose an effective and efficient visual descriptor model that extracts object names and aspects from patent captions to annotate benchmark patent figure datasets. We compared two state-of-the-art named entity recognition (NER) models and found that with a limited number of annotated samples, the BiLSTM-CRF model outperforms the Transformer model by a significant …

D-Lib Magazine Pioneered Web-Based Scholarly Communication, Michael L. Nelson, Herbert Van De Sompel

Computer Science Faculty Publications

The web began with a vision of, as stated by Tim Berners-Lee in 1991, “that much academic information should be freely available to anyone”. For many years, the development of the web and the development of digital libraries and other scholarly communications infrastructure proceeded in tandem. A milestone occurred in July, 1995, when the first issue of D-Lib Magazine was published as an online, HTML-only, open access magazine, serving as the focal point for the then emerging digital library research community. In 2017 it ceased publication, in part due to the maturity of the community it served as well as …

Sql Injection & Web Application Security: A Python-Based Network Traffic Detection Model, Nyki Anderson

Cybersecurity Undergraduate Research Showcase

The Internet of Things (IoT) presents a great many challenges in cybersecurity as the world grows more and more digitally dependent. Personally identifiable information (PII) (i,e., names, addresses, emails, credit card numbers) is stored in databases across websites the world over. The greatest threat to privacy, according to the Open Worldwide Application Security Project (OWASP) is SQL injection attacks (SQLIA) [1]. In these sorts of attacks, hackers use malicious statements entered into forms, search bars, and other browser input mediums to trick the web application server into divulging database assets. A proposed technique against such exploitation is convolution neural network …

Interactive Agent-Based Simulation For Experimentation: A Case Study With Cooperatve Game Theory, Andrew J. Collins, Sheida Etemadidavan

Engineering Management & Systems Engineering Faculty Publications

Incorporating human behavior is a current challenge for agent-based modeling and simulation (ABMS). Human behavior includes many different aspects depending on the scenario considered. The scenario context of this paper is strategic coalition formation, which is traditionally modeled using cooperative game theory, but we use ABMS instead; as such, it needs to be validated. One approach to validation is to compare the recorded behavior of humans to what was observed in our simulation. We suggest that using an interactive simulation is a good approach to collecting the necessary human behavior data because the humans would be playing in precisely the …