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Hire Dr. Kody M.

Netherlands

USD 90 /hr

Senior Research Software Engineer | 10+ years engineering experience | Semantic Web, Knowledge Graphs, AI, NLP

Profile Summary

Driven by creativity and innovation, with strong expertise in software development, research, the Web, and information management. I adapt quickly to new tools, languages, and frameworks, and am particularly skilled at understanding and contributing to others' code given limited documentation. I have a proven aptitude for explaining complex technical concepts clearly and effectively. I thrive in open, collaborative environments where ideas are encouraged, discussed, and thoughtfully evaluated. Although my core expertise is in Software Engineering, Semantic Web, Linked Data, Ontologies and Knowledge Graphs, I also have documented experience with applied AI, NLP and Text Mining.

Subject Matter Expertise

• ★ Software Engineering
• ★ Artificial Intelligence
• ★ Information & Knowledge Management
• ☆ Computer Science
• ☆ Information Technology
• ☆ Information Engineering
• ☆ Software Architecture
• ☆ Data Analysis
• ☆ Algorithm Design
• ☆ Data Processing
• ☆ Data Exploration
• ☆ Data Visualization
• ☆ Text Mining & Analytics
• ☆ Natural Language Processing
• ☆ Pure Mathematics
• ☆ Mathematical Logic
• ☆ Knowledge Management
• ☆ Information Systems
• ☆ Logic
• ☆ Computer Science Education
• ☆ Python
• ☆ SQL
• ☆ Excel
• ☆ Java
• ☆ LaTex
• ☆ R
• ☆ Scikit-learn
• ☆ Markup Languages
• ☆ Hypothesis
• ☆ Peer Review
• ☆ Research Methodology
• ☆ Animation & Illustration
• ☆ Video Production
• ☆ Instructional Webinars
• ☆ Skills Training
• ☆ Technical & Scientific Writing
• ☆ Manuscript & Journal Article Writing
• ☆ Instructional Materials
• ☆ Release Notes
• ☆ Science Communication
• ☆ Scientific Proofreading & Editing
• ☆ Proofreading & Editing
• ☆ Creative Writing
• ☆ Audio Transcription
• ☆ Course Content Writing
• ☆ Grant Writing

Services

• Writing
• Research
• Consulting
• Data & AI
• Product Development

Writing Technical Writing, Creative Writing, General Proofreading & Editing

Research Scientific and Technical Research

Consulting Scientific and Technical Consulting

Data & AI Data Visualization, Text Mining & Analytics

Product Development Concept Development, Prototyping, Reverse Engineering

Work Experience

senior research software engineer

Netherlands eScience Center

April 2022 - April 2026

Assistant Professor (tenured)

Maastricht University

April 2021 - April 2022

Maastricht University

- March 2022

Postdoctoral Researcher

Maastricht University

April 2019 - April 2021

Postdoctoral Researcher

Maastricht University

April 2017 - April 2019

Education

PhD Computer Science

University of Manchester & University of KwaZulu-Natal (Durban)

April 2011 - April 2015

Certifications

• University Teaching Qualification

  Maastricht University

  September 2021 - Present

Publications

JOURNAL ARTICLE

TAPS Responsibility matrix @article{4b663390a8624dd0a0feeff7766962d9, title = "TAPS Responsibility matrix: a tool for responsible data science by design", abstract = "Data-science is an interdisciplinary research working on data from different fields. When analyzing these data, data scientists implicitly agree to follow the rules governing these fields. However, the responsibilities of the involved actors are not necessarily explicit. While novel frameworks supporting open-science are being proposed, there are currently no frameworks that focus on the responsibilities within a data-science project. In this paper, we describe the Transparency, Accountability, Privacy, and Societal Responsibility Matrix (TAPS-RM) as framework to explore social, legal, and ethical aspects of data-science projects. TAPS-RM is a tool for providing a holistic view of a project beyond key outcomes and to clarify responsibilities of actors. We map TAPS-RM to well-known initiatives for open-data (FACT/FAIR and Datasheets for datasets). We conclude that TAPS-RM is a tool to reflect on responsibilities at a data science project level and can be used to advance responsible data science by design.", keywords = "Responsible data science, responsibility framework, transparency, privacy/confidentiality, accountability, societal values", author = "Visara Urovi and Remzi Celebi and Chang Sun and Parveen Kumar and Linda Rieswijk and Michael Erard and Arif Yilmaz and Kody Moodley and Michel Dumontier", year = "2024", month = dec, day = "2", doi = "10.1080/23299460.2024.2414530", language = "English", volume = "11", pages = "1--32", journal = "Journal of Responsible Innovation", issn = "2329-9460", publisher = "Routledge/Taylor \& Francis Group", number = "1", } . Journal of Responsible Innovation.

Kody Moodley, Linda Rieswijk, Tudor I. Oprea, Michel Dumontier (2021). InContext: curation of medical context for drug indications . Journal of Biomedical Semantics.

InContext @article{66cb99e691a94ad496869baba5e0b63e, title = "InContext: curation of medical context for drug indications", abstract = "Accurate and precise information about the therapeutic uses (indications) of a drug is essential for applications in drug repurposing and precision medicine. Leading online drug resources such as DrugCentral and DrugBank provide rich information about various properties of drugs, including their indications. However, because indications in such databases are often partly automatically mined, some may prove to be inaccurate or imprecise. Particularly challenging for text mining methods is the task of distinguishing between general disease mentions in drug product labels and actual indications for the drug. For this, the qualifying medical context of the disease mentions in the text should be studied. Some examples include contraindications, co-prescribed drugs and target patient qualifications. No existing indication curation efforts attempt to capture such information in a precise way. Here we fill this gap by presenting a novel curation protocol for extracting indications and machine processable annotations of contextual information about the therapeutic use of a drug. We implemented the protocol on a reference set of FDA-approved drug product labels on the DailyMed website to curate indications for 150 anti-cancer and cardiovascular drugs. The resulting corpus - InContext - focuses on anti-cancer and cardiovascular drugs because of the heightened societal interest in cancer and heart disease. In order to understand how InContext relates with existing reputable drug indication databases, we analysed it's overlap with a state-of-the-art indications database - LabeledIn - as well as a reputable online drug compendium - DrugCentral. We found that 40\% of indications sampled from DrugCentral (and 23\% from LabeledIn) respectively, could not be accounted for in InContext. This raises questions about the veracity of indications not appearing in InContext. The additional contextual information curated by InContext about disease mentions in drug SPLs provides a foundation for more precise, structured and formal representations of knowledge related to drug therapeutic use, in order to increase accuracy and agreement of drug indication extraction methods for in silico drug repurposing.", keywords = "Ontologies, Drug repurposing, Drug indications, Semantic similarity, Data quality", author = "Kody Moodley and Linda Rieswijk and Oprea, \{Tudor I\} and Michel Dumontier", note = "Funding Information: We would like to thank Tiffany Leung of the Faculty of Health, Medicine and Life Sciences (FHML) at Maastricht University and Stuart J. Nelson from the University of New Mexico (UNM) for their time and medical expertise for determining the equivalence and similarity of pairs of drug indication terms. Thanks also goes to Amrapali J. Zaveri of the Institute of Data Science at Maastricht University (IDS@UM) and the team of indication term annotators who curated the list of drugs, and therapeutic usage annotations, for the drug labels that were used in this study. Finally, we would like to thank Alexander Malic and Seun Adekunle, also of IDS@UM, for their help and expertise in extracting the indications from the various data sources for further analysis. Research reported in this publication was supported by the Biomedical Data Translator program through the National Center for Advancing Translational Sciences of the National Institutes of Health under award number OT3TR002027. Funding Information: We would like to thank Tiffany Leung of the Faculty of Health, Medicine and Life Sciences (FHML) at Maastricht University and Stuart J. Nelson from the University of New Mexico (UNM) for their time and medical expertise for determining the equivalence and similarity of pairs of drug indication terms. Thanks also goes to Amrapali J. Zaveri of the Institute of Data Science at Maastricht University (IDS@UM) and the team of indication term annotators who curated the list of drugs, and therapeutic usage annotations, for the drug labels that were used in this study. Finally, we would like to thank Alexander Malic and Seun Adekunle, also of IDS@UM, for their help and expertise in extracting the indications from the various data sources for further analysis. Research reported in this publication was supported by the Biomedical Data Translator program through the National Center for Advancing Translational Sciences of the National Institutes of Health under award number OT3TR002027. Publisher Copyright: {\textcopyright} 2021, The Author(s).", year = "2021", month = feb, day = "12", doi = "10.1186/s13326-021-00234-4", language = "English", volume = "12", journal = "Journal of biomedical semantics", issn = "2041-1480", publisher = "BioMed Central Ltd", number = "1", } . Journal of biomedical semantics.

Principles of KLM-style Defeasible Description Logics @article{adc45c3f33b24a1496317d5c648d11ac, title = "Principles of KLM-style Defeasible Description Logics", abstract = "The past 25 years have seen many attempts to introduce defeasible-reasoning capabilities into a description logic setting. Many, if not most, of these attempts are based on preferential extensions of description logics, with a significant number of these, in turn, following the so-called KLM approach to defeasible reasoning initially advocated for propositional logic by Kraus, Lehmann, and Magidor. Each of these attempts has its own aim of investigating particular constructions and variants of the (KLM-style) preferential approach. Here our aim is to provide a comprehensive study of the formal foundations of preferential defeasible reasoning for description logics in the KLM tradition.We start by investigating a notion of defeasible subsumption in the spirit of defeasible conditionals as studied by Kraus, Lehmann, and Magidor in the propositional case. In particular, we consider a natural and intuitive semantics for defeasible subsumption, and we investigate KLM-style syntactic properties for both preferential and rational subsumption. Our contribution includes two representation results linking our semantic constructions to the set of preferential and rational properties considered. Besides showing that our semantics is appropriate, these results pave the way for more effective decision procedures for defeasible reasoning in description logics. Indeed, we also analyse the problem of non-monotonic reasoning in description logics at the level of entailment and present an algorithm for the computation of rational closure of a defeasible knowledge base. Importantly, our algorithm relies completely on classical entailment and shows that the computational complexity of reasoning over defeasible knowledge bases is no worse than that of reasoning in the underlying classical DL ALC.", keywords = "Non-monotonic reasoning, defeasible subsumption, preferential semantics, rational closure, NONMONOTONIC DESCRIPTION LOGIC, RATIONAL CLOSURE, COMPLEXITY", author = "Katarina Britz and Giovanni Casini and Thomas Meyer and Kody Moodley and Uli Sattler and Ivan Varzinczak", note = "Publisher Copyright: {\textcopyright} 2020 ACM.", year = "2021", month = jan, doi = "10.1145/3420258", language = "English", volume = "22", journal = "Acm Transactions on Computational Logic", issn = "1529-3785", publisher = "Association for Computing Machinery (ACM)", number = "1", } . Acm Transactions on Computational Logic.

Kody MOODLEY, Pedro V HERNANDEZ-SERRANO, Amrapali J ZAVERI, Marcel GH SCHAPER, Michel DUMONTIER, Gijs VAN DIJCK(2020). The Case for a Linked Data Research Engine for Legal Scholars . European Journal of Risk Regulation. 11. (1). p. 70--93. Cambridge University Press ({CUP})

The Case for a Linked Data Research Engine for Legal Scholars @article{312427be4bdd472297bf4fdf04864b76, title = "The Case for a Linked Data Research Engine for Legal Scholars", abstract = "This contribution explores the application of data science and artificial intelligence to legal research, more specifically an element that has not received much attention: the research infrastructure required to make such analysis possible. In recent years, EU law has become increasingly digitised and published in online databases such as EUR-Lex and HUDOC. However, the main barrier inhibiting legal scholars from analysing this information is lack of training in data analytics. Legal analytics software can mitigate this problem to an extent. However, current systems are dominated by the commercial sector. In addition, most systems focus on search of legal information but do not facilitate advanced visualisation and analytics. Finally, free to use systems that do provide such features are either too complex to use for general legal scholars, or are not rich enough in their analytics tools. In this paper, we motivate the case for building a software platform that addresses these limitations. Such software can provide a powerful platform for visualising and exploring connections and correlations in EU case law, helping to unravel the “DNA” behind EU legal systems. It will also serve to train researchers and students in schools and universities to analyse legal information using state-of-the-art methods in data science, without requiring technical proficiency in the underlying methods. We also suggest that the software should be powered by a data infrastructure and management paradigm following the seminal FAIR (Findable, Accessible, Interoperable and Reusable) principles.", author = "Kody Moodley and \{Hern{\'a}ndez Serrano\}, Pedro and Amrapali Zaveri and Marcel Schaper and Michel Dumontier and \{van Dijck\}, Gijs", note = "Publisher Copyright: {\textcopyright} 2019 The Author(s).", year = "2020", month = mar, doi = "10.1017/err.2019.51", language = "English", volume = "11", pages = "70--93", journal = "European Journal of Risk Regulation", issn = "1867-299X", publisher = "Cambridge University Press", number = "1", } . European Journal of Risk Regulation.

PREPRINT

Kody Moodley, Malte Lüken, Eva Viviani, Christian Pipal, Gijs Schumacher (2024). MEXCA - A Simple and Robust Pipeline for Capturing Emotion Expressions in Faces, Vocalization, and Speech .

TAPS Responsibility Matrix @techreport{993303ddb6b14a6d864bb9f59442a3ff, title = "TAPS Responsibility Matrix: A tool for responsible data science by design", abstract = "Data science is an interdisciplinary research area where scientists are typically working with data coming from different fields. When using and analyzing data, the scientists implicitly agree to follow standards, procedures, and rules set in these fields. However, guidance on the responsibilities of the data scientists and the other involved actors in a data science project is typically missing. While literature shows that novel frameworks and tools are being proposed in support of open-science, data reuse, and research data management, there are currently no frameworks that can fully express responsibilities of a data science project. In this paper, we describe the Transparency, Accountability, Privacy, and Societal Responsibility Matrix (TAPS-RM) as framework to explore social, legal, and ethical aspects of data science projects. TAPS-RM acts as a tool to provide users with a holistic view of their project beyond key outcomes and clarifies the responsibilities of actors. We map the developed model of TAPS-RM with well-known initiatives for open data (such as FACT, FAIR and Datasheets for datasets). We conclude that TAPS-RM is a tool to reflect on responsibilities at a data science project level and can be used to advance responsible data science by design.", keywords = "Computer Science - Computers and Society, Computer Science - Artificial Intelligence, I.2.1", author = "Visara Urovi and Remzi Celebi and Chang Sun and Linda Rieswijk and Michael Erard and Arif Yilmaz and Kody Moodley and Parveen Kumar and Michel Dumontier", year = "2023", month = feb, day = "2", doi = "10.48550/arXiv.2302.01041", language = "English", pages = "2302.01041v1", type = "WorkingPaper", } .

Kody Moodley (2017). Practical Reasoning for Defeasible Description Logics .

BOOK CHAPTER

P.V. Hernandez Serrano, K. Moodley, G. Van Dijck, M. Dumontier(2020). Sleeping Beauties in Case Law . LEGAL KNOWLEDGE AND INFORMATION SYSTEMS. 334. p. 231--234. IOS Press

CONFERENCE PAPER

Similarity and relevance of court decisions: A computational study on CJEU cases @inproceedings{50b0889622a74193922a51c5a7fcabfc, title = "Similarity and relevance of court decisions: A computational study on CJEU cases", abstract = "Identification of relevant or similar court decisions is a core activity in legal decision making for case law researchers and practitioners. With an ever increasing body of case law, a manual analysis of court decisions can become practically impossible. As a result, some decisions are inevitably overlooked. Alternatively, network analysis may be applied to detect relevant precedents and landmark cases. Previous research suggests that citation networks of court decisions frequently provide relevant precedents and landmark cases. The advent of text similarity measures (both syntactic and semantic) has meant that potentially relevant cases can be identified without the need to manually read them. However, how close do these measures come to approximating the notion of relevance captured in the citation network? In this contribution, we explore this question by measuring the level of agreement of state-of-the-art text similarity algorithms with the citation behavior in the case citation network. For this paper, we focus on judgements by the Court of Justice of the European Union (CJEU) as published in the EUR-Lex database. Our results show that similarity of the full texts of CJEU court decisions does not closely mirror citation behaviour, there is a substantial overlap. In particular, we found syntactic measures surprisingly outperform semantic ones in approximating the citation network. ", keywords = "CJEU, case law, computational, similarity, NETWORK ANALYSIS, Text Similarity, LAW, LEGAL, Network Analysis, Word Embeddings", author = "Kody Moodley and \{Hern{\'a}ndez Serrano\}, Pedro and \{van Dijck\}, Gijs and Michel Dumontier", note = "Publisher Copyright: {\textcopyright} 2019 The authors and IOS Press.", year = "2019", month = dec, doi = "10.3233/FAIA190307", language = "English", isbn = "978-16-4368-048-4", series = "Frontiers in Artificial Intelligence and Applications", publisher = "IOS Press", pages = "63--72", editor = "Micha{\l} Araszkiewicz and V{\'i}ctor Rodr{\'i}guez-Doncel", booktitle = "Legal knowledge and information systems", address = "Netherlands", } . Legal knowledge and information systems.

Kody Moodley, Amrapali Zaveri, Chunlei Wu, Michel Dumontier(2018). A model for capturing provenance of assertions about chemical substances . Semantic Web Applications and Tools for Health Care and Life Sciences. 2275. CEUR-WS.org

Giovanni Casini and Thomas Meyer and Kody Moodley and Uli Sattler and Ivan Varzinczak(2015). Introducing Defeasibility into OWL Ontologies . International Semantic Web Conference. 9367. p. 409--426. Springer

Giovanni Casini and Thomas Meyer and Kody Moodley and Riku Nortjé(2014). Relevant Closure: A New Form of Defeasible Reasoning for Description Logics. European Conference on Logics in Artificial Intelligence. 8761. p. 92--106. Springer

Kody Moodley and Thomas Meyer and Uli Sattler(2014). Practical Defeasible Reasoning for Description Logics. European Starting AI Researcher Symposium. 264. p. 191--200. IOSPress

Kody Moodley and Thomas Meyer and Ivan Jos{\'e} Varzinczak(2012). A Defeasible Reasoning Approach for Description Logic Ontologies. South African Institute for Computer Scientists and Information Technologists. p. 69--78. ACM

CONFERENCE PRESENTATION

Assessing Schema.org's Coverage of Terms from Key Biomedical Datasets @conference{c22746a48a204d07976afd5cdf63c4e7, title = "Assessing Schema.org's Coverage of Terms from Key Biomedical Datasets", author = "Kody Moodley and Josef Hardi and John Graybeal and Musen, \{Mark A.\} and Michel Dumontier", year = "2018", month = jul, day = "6", language = "English", note = "Bio-Ontologies ; Conference date: 24-07-2017 Through 25-07-2018", url = "https://sites.google.com/site/bioontologies2017/", } . Bio-Ontologies, Prague, Czech Republic, 24/07/17.

Assessing the quality of manually curated drug indication and usage information via ontology term mappings @conference{07d8c95abc51490ea46ea4b4771b1fea, title = "Assessing the quality of manually curated drug indication and usage information via ontology term mappings", author = "Kody Moodley and Linda Rieswijk and Oprea, \{Tudor I.\} and Michel Dumontier", year = "2017", month = jul, day = "21", language = "English", note = "Bio-Ontologies ; Conference date: 24-07-2017 Through 25-07-2018", url = "https://sites.google.com/site/bioontologies2017/", } . Bio-Ontologies, Prague, Czech Republic, 24/07/17.

DISSERTATION THESIS

(2015). Practical Defeasible Reasoning for Description Logics. University of KwaZulu-Natal.

(2011). Debugging and Repair of Description Logic Ontologies. University of KwaZulu-Natal.

CONFERENCE POSTER

Kody Moodley and Thomas Meyer and Uli Sattler(2014). DIP: A Defeasible-Inference Platform for OWL Ontologies. International Workshop on Description Logics. p. 671-683. CEUR Workshop Proceedings

Giovanni Casini and Thomas Meyer and Kody Moodley and Ivan Jos{\'e} Varzinczak(2013). Nonmonotonic reasoning in Description Logics. Rational Closure for the ABox. International Workshop on Description Logics. p. 600--615. CEUR Workshop Proceedings

Giovanni Casini and Thomas Meyer and Kody Moodley and Ivan Jos{\'e} Varzinczak(2013). Towards Practical Defeasible Reasoning for Description Logics. International Workshop on Description Logics. p. 587--599. CEUR Workshop Proceedings

Thomas Meyer and Kody Moodley and Ivan Jos{\'e} Varzinczak(2012). A Protege Plug-in for Defeasible Reasoning. International Workshop on Description Logics. CEUR Workshop Proceedings

Kody Moodley and Thomas Meyer and Ivan José Varzinczak(2011). Root Justifications for Ontology Repair. International Conference on Web Reasoning and Rule Systems. 6902. p. 275--280. Springer