About

The Web Science and Digital Libraries (WS-DL) Research Group at Old Dominion University performs research in web archiving, web science, digital libraries, neuro-information retrieval, social media, digital preservation, human-computer interaction, information visualization, natural language processing, accessibility, and mining scholarly data.

Our alumni have been hired by the Internet Archive, MITRE, Amazon, Google, Microsoft, Los Alamos National Laboratory (LANL), and have been faculty and/or researchers at several universities including Drexel University, Indiana University, Emory University, University of California at Berkeley, and Columbia College.

We are grateful for support from the National Science Foundation (NSF), the National Endowment for the Humanities (NEH), the Institute of Museum and Library Services (IMLS), National Aeronautics and Space Administration (NASA), Department of Defense (DOD), Department of Energy (DOE), Department of Education (ED), International Internet Preservation Consortium (IIPC), Protocol Laboratories, and the Andrew W. Mellon Foundation.

Faculty

Students

PhD students

MS students

BS students

Alumni

PhD Alumni

MS Alumni

Research

• Faculty, students, and alumni at Google Scholar
• @WebSciDL retweets highlights and announcements from WS-DL members
• Software and data at GitHub
• Trip reports, paper summaries, announcements, releases, early results at Blogger
• Annual research summaries: 2024, 2023 2022, 2021, 2020, 2019, 2018, 2017, 2016, 2015, 2014, and 2013

Courses

The Web Science and Digital Libraries research group teaches an exciting and unique set of advanced undergraduate and graduate courses, including:

• CS 395 Research Methods in Data and Web Science
  Topics: writing proposals, reading & writing papers, giving presentations, Python, Web APIs, reproducibility, LaTeX, and GitHub.
• CS 418/518 Web Programming
  Topics: LAMP (Linux, Apache, MySQL, PHP), MVC (Model-View-Control), Search Engines, GitHub.  
• CS 431/531 Web Server Design
  Topics: HTTP, REST (Representational State Transfer), HATEOAS.
• CS 432/532 Web Science
  Topics: Python, GitHub, LaTeX, data visualization, information retrieval, social networks, collective intelligence, machine learning.
• CS 480/580 Introduction to Artificial Intelligence
  Topics: problem representation, problem-solving methods, search, pattern recognition, natural language processing, vision processing, machine learning, and expert systems.
• CS 495/595 Intro to Data Mining
  Topics: data preprocessing, pattern mining, outlier analysis, and mining of text, data streams, time series, spatial, and graph data.
• CS 495/595 Web Security
  Topics: HTTP, Cross-Site Request Forgery, Same Origin Policy, Cross-Site Scripting (XSS), Fingerprinting, Denial-of-service, Phishing.
• CS 620 Intro to Data Science & Analytics
  Topics: Python, Pandas, NumPy, NoSQL, Data Wrangling, ML.
• CS 625 Data Visualization
  Topics: Tableau, R, Vega-Lite, Observable, Markdown, OpenRefine, data cleaning, visual perception, visualization design, exploratory data analysis, visual storytelling.
• CS 725/825 Information Visualization and Visual Analytics
  Topics: Vega-Lite, D3, Observable, visual analytics, interactive visualization, dashboard design, reading academic vis papers.
• CS 728/828 Deep Learningbr/>Topics: ully-connected neural networks, recurrent neural networks, convolutional neural networks, regularization, generalization, loss function, backpropagation, attention, transformer, graph neural networks, and deep reinforcement learning
• CS 733/833 Natural Language Processing
  Topics: Language Models, Word2Vec, BERT, Deep Learning, Assistants.
• CS 795/895 Mining Scholarly Big Data
  Topics: Apache Spark, NLP, Data Mining, Recommenders.
• CS 734/834 Information Retrieval
  Topics: crawling, ranking, query processing, retrieval models, evaluation, clustering, machine learning.
• CS 795/895 Natural Language Understanding
  Topics: Fundamentals of neural networks and deep learning, natural language reference, sentiment analysis, and semantic parsing.
• CS 795/895 Web Archiving Forensics
  Topics: Memento, CDX, Twitter, Caching.
• CS 795/895 Intelligent User Interfaces
  Topics: HCI, Assistive Technologies, Speech Interfaces, Wearable Computing, Crowd-Powered Interfaces
• CS 795/895 Human-Computer Interaction
  Topics: cognitive and social phenomena surrounding human use of computers.
• CS 795/895 Foundation Models of Data Science
  Topics: Concept, history, instances of foundation models and their applications in healthcare, biomedicine, law, and education; technology and capabilities as applied to language, vision, robotics, reasoning, search, modeling, training, adaptation, prompt engineering, evaluation, systems, data, security and privacy, robustness to distribution shift, safety and alignment, and interpretability
• CS 891 Emerging Technologies
  Topics: Cloud, Edge, IoT, Blockchain, Security, Agile.

Previous semesters: S26, F25, S25, F24 S24, F23, S23, F22, S22, F21, S21, F20, S20, F19, S19, and F18

Twitter

@WebSciDL: RTs of announcements from WS-DL members

Blog

The most recent blog posts.