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With the continued advancement of digitalization in the healthcare and education sectors, the data types, service objects, and application tasks carried by Web information systems are becoming increasingly complex. Online medical platforms, educational resource platforms, and multimodal interactive environments are continuously generating large-scale, heterogeneous, and knowledge-intensive data, requiring systems to possess semantic understanding, knowledge organization, and intelligent interaction capabilities in addition to basic functions such as information storage, data access, and resource management. In recent years, Large Language Models (LLMs) have developed rapidly, demonstrating strong capabilities in tasks such as natural language understanding, question answering, content generation, and human-computer interaction, providing new technological pathways for Web information systems in the healthcare and education sectors to handle complex knowledge resources, support personalized services, and achieve intelligent interaction.

However, directly applying general-purpose LLMs to Web information systems in healthcare and education still faces several challenges. First, the generation process of LLMs primarily relies on parametric knowledge and contextual relationships, lacking explicit representations of domain knowledge boundaries, professional semantic relationships, and task constraints. Therefore, when handling tasks such as medical knowledge and personalized services, it is prone to problems such as factual bias or inconsistent results. Second, medical and educational applications typically require systems with high interpretability and traceability, while the reasoning process of general LLMs is highly implicit, making it difficult to clearly present the relationship between the generated results and domain knowledge and service goals. Furthermore, the data resources upon which network information systems rely often have characteristics such as dynamic updates and multimodal representation, placing higher demands on knowledge integration, semantic alignment, and security management. Therefore, relying solely on the language understanding and generation capabilities of general-purpose LLMs is insufficient to support the reliability, explainability, and controllability required by Web information systems in healthcare and education.

Knowledge-enhanced LLMs provide an important research direction for addressing the above challenges. By incorporating structured knowledge, Web semantics, and multimodal knowledge representation into LLMs, it becomes possible to introduce more explicit domain constraints and semantic associations into generation and reasoning processes, thereby improving the task adaptability of LLMs to professional knowledge and enhancing the explainability of their outputs. Furthermore, knowledge-enhancement mechanisms facilitate the coordinated operation of LLMs with functional modules in Web information systems, such as data integration, information retrieval, and application management, providing more reliable technical support for tasks including medical information services, health question answering, and learning analytics. Against this background, this special issue focuses on knowledge-enhanced LLMs for Web information systems in healthcare and education, and solicits high-quality research contributions on theoretical models, key methods, system frameworks, evaluation mechanisms, and practical applications. It particularly welcomes studies that investigate how knowledge-driven artificial intelligence technologies improve the reliability, explainability, and adaptability of Web-based healthcare and education services, while promoting interdisciplinary advances in generative artificial intelligence, AI agents, multimodal artificial intelligence, and privacy-preserving artificial intelligence.

List of Topic Areas

• Knowledge-enhanced LLM architectures for Web information systems.
• Knowledge graphs, ontologies, and Web semantics for LLM reasoning and generation.
• Retrieval-augmented generation for Web-based health and education services.
• Web knowledge mining, information extraction, and knowledge integration for LLM-based systems.
• Multimodal knowledge representation and fusion for health and learning applications on the Web.
• Trustworthy, explainable, and privacy-preserving LLMs for sensitive Web environments.
• LLM-enhanced medical information retrieval, health question answering, and decision support.
• LLM-enhanced personalized learning, intelligent tutoring, automated assessment, and learning feedback.
• Agentic LLMs and AI agents for Web-based health and education service management.
• Benchmarks, datasets, evaluation metrics, and real-world applications of knowledge-enhanced LLMs in Web information systems.

Submission Information

Submissions of full manuscripts are made using ScholarOne Manuscripts. Registration and access are available here:

Submit via ScholarOne

Author guidelines must be strictly followed. Please see:

Author guidelines

Authors should select (from the drop-down menu) the special issue title at the appropriate step in the submission process, i.e. in response to “Please select the issue you are submitting to”.

Submitted articles must not have been previously published, nor should they be under consideration for publication anywhere else, while under review for this journal.

Abstract Submissions

Abstracts should be emailed to the lead Guest Editor, Weimin Li, at Wmli@shu.edu.cn.

Journal Information: Scopus Journal Q2, H-Index 27

Key Dates

Closing date for abstract submissions: 1 October 2026

Closing date for manuscript submissions: 1 November 2026

For more details refer here

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Healthcare is a relevant setting for examining how innovation management shapes competitiveness, sustainability, and value-creation capabilities. Recent debate has shifted from a focus on the technical performance of AI systems to broader concerns related to implementation, accountability, trustworthiness, evaluation, and organisational sustainability (Papagiannidis et al., 2025; Bankins et al., 2024; Xiong et al., 2026). This shift is crucial in healthcare, where Agentic AI and GenAI are not merely digital transformation tools, but sociotechnical systems that potentially affect clinical practices, decision-making processes, care coordination, patient-doctor relationships, resource allocation and costs optimization.

Notably, AI and GenAI are sociotechnical systems with growing autonomy and interactive capabilities, thereby raising new questions around trust, responsibility, human oversight, and governance. As such, they pose a significant challenge to enterprise information management, affecting processes, data, professional roles, compliance, procurement, and monitoring systems (Schiavone et al., 2021).

Thus, the deployment of Agentic AI and GenAI occurs in high-risk, highly regulated, data and human-intensive settings. Healthcare organizations must balance innovation with patient safety, care quality, ethical and regulatory issues, data protection and human oversight preservation. In this context, errors, biases and unclear accountability may affect patients, professionals and healthcare ecosystems. This SI moves beyond the broader discussions of GenAI-enabled digital transformation or Agentic AI in organisational functions. It focuses on how healthcare organizations design, implement, manage and scale AI semi-autonomous systems within complex care environments.

This SI seeks theoretical and empirical contributions examining how health systems, healthcare organizations, and providers develop capabilities, governance structures, and evaluation practices to move from experimentation to technology adoption and integration. Particular attention will be given to agentic workflow integration, responsible value creation, data governance, clinical and managerial accountability, human oversight, professional role reconfiguration, patient-doctor relationship, organisational capabilities and compliance with existing regulatory frameworks.

By focusing on healthcare as the empirical and theoretical context, this SI aims to generate new insights into how Agentic and GenAI systems can be responsibly embedded in healthcare organizations while balancing innovation, safety, equity, trust, regulatory compliance and measurable clinical, organisational, and societal value.

List of Topic Areas

In this context, we invite researchers to address topics including, but not limited to, the following:

• How are GenAI and Agentic AI reshaping clinical, administrative, and managerial workflows in healthcare organizations?
• How do healthcare organizations govern Agentic AI systems across care pathways?
• What organizational capabilities are needed to move from experimental GenAI applications to integrated and scalable Agentic healthcare systems?
• How can healthcare organizations ensure meaningful human oversight when AI systems become more autonomous, proactive, and embedded in clinical or administrative processes?
• How do GenAI and agentic AI create, capture, or potentially destroy value for different healthcare stakeholders?
• How do Agentic and GenAI systems transform healthcare knowledge management?
• How can healthcare organizations evaluate and measure the clinical, organizational, economic, ethical, and societal value generated by GenAI and Agentic AI adoption?
• What governance mechanisms are needed to ensure accountability, transparency and regulatory compliance in AI-enabled healthcare organizations?
• How do GenAI and Agentic AI affect decision-making processes within healthcare organizations?
• How can healthcare organizations manage risks related to automation bias, inequitable outcomes and over-reliance on AI?
• How do agentic AI and GenAI support healthcare system sustainability?

Submission Information

Submissions are made using ScholarOne Manuscripts. Registration and access are available here:

Submit via ScholarOne

Author guidelines must be strictly followed. Please see:

Author guidelines

Authors should select (from the drop-down menu) the special issue title at the appropriate step in the submission process, i.e. in response to “Please select the issue you are submitting to”.

Submitted articles must not have been previously published, nor should they be under consideration for publication anywhere else, while under review for this journal.

Journal Information: Scopus Journal Q1, H-Index 100

Key Dates

Opening date for manuscript submissions: 1 January 2027

Closing date for manuscript submissions: 30 June 2027

For more details refer here

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Friday, the 13th of November 2026, is Doomsday. According to von Foerster et al. (1960), it is the day when population growth will reach infinity, thus ending the possibilities of humanity to survive. Interestingly enough, it is also the day of Heinz von Foerster’s 115th birthday anniversary, which gives us a good reason to review his contribution to systems research. Heinz von Foerster has been a pioneer in this field, working closely with other leading figures such as John von Neumann, Margaret Mead, Norbert Wiener, Humberto Maturana, Francisco Varela, Gregory Bateson, or Niklas Luhmann (Umpleby, 2008). Originally trained as a physicist, he addressed numerous different topics across many disciplines. Von Foerster has shaped our understanding of second-order cybernetics and contributed significantly to the development of radical constructivism (Scott, 2004). To him, we owe the notion of the trivial machine (von Foerster, 1984), the ethical imperative (von Foerster, 2003), and many other thought-provoking concepts and expressions.

The Doomsday Calculation, of course, is also a provocation. While it concerns a serious issue, is also raises questions about the use of simple mathematics to make predictions of future social development. Setting the date on Friday, the 13th associates it with superstition. Setting it on von Foerster’s birthday adds a sense of humour. Nevertheless, this article is not just a tongue-in-cheek comment on the limitations of formal modelling. Knowing that he was a leading figure of second-order cybernetics, von Foerster et al.’s (1960) article can also be read as a reflection on the possibilities to approach grand challenges in society objectively, and the dangers of ideology and self-referentiality. In this sense, Doomsday is significant for today’s scientific discourse on many levels, showing the topicality of von Foerster’s work in different ways.

The aim of this special issue is to collect articles that discuss Heinz von Foerster’s work from different angles. It invites contributions from former students and collaborators who give first-hand evidence of von Foerster’s teaching and research activities, as well as conceptual and empirical works that make use of his concepts and models to study today’s world and society. Furthermore, we warmly welcome articles that look beyond the mere application of formal constructs to observe the observers in contemporary science. What can we learn from second-order cybernetics for tackling grand challenges today? How do we find a balance between enforcing the necessary steps to cope with climate changes, over-population, pollution, etc., while at the same time leaving systemic structures intact? How do we use science and engineering to create new opportunities for development and expand abilities to choose instead of limiting them? And how can we add a little bit of humour help us to fight desperation in view of all the problems haunting us?
During submission, please make sure that you pick the right special issue and the right article category. 

Submissions Information

Submissions are made using ScholarOne Manuscripts. Registration and access are available at: https://mc.manuscriptcentral.com/kyb
Author guidelines must be strictly followed. Please see: https://www.emeraldgrouppublishing.com/journal/kyb#jlp_author_guidelines

Authors should select (from the drop-down menu) the special issue title at the appropriate step in the submission process, i.e. in response to “Please select the issue you are submitting to”.

Submitted articles must not have been previously published, nor should they be under consideration for publication anywhere else while under review for this journal.

Journal Information: Scopus journal Q1, H-Index 65

Key deadlines

Opening date for manuscripts submissions: 1 January 2026
Closing date for manuscripts submission: 30 June 2026

For more details refer here

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On the other hand, the human brain possesses remarkable lifelong learning capabilities due to its unique memorial mechanisms, that enable the brain to continually absorb new information while preserving existing knowledge, achieving cumulative knowledge growth. Furthermore, the brain’s hierarchical memory system and memory consolidation processes provide crucial insights for addressing catastrophic forgetting. Therefore, Brain-Like Cognition offers a promising framework for emulating human cognitive processes, which can be particularly valuable in HMS, which can give new insights for foundation models, fusion models, federated learning, and other models to achieve effective continual learning.

This special issue aims to explore novel brain like cognition approaches for continual learning, including theoretical analysis, transforming neuroscientific findings into continual learning computational models, how to leverage foundation model technologies to overcome traditional continual learning limitations, and how to evaluate and validate the effectiveness of these novel approaches.

Key topics

· Brain-like cognition-driven approaches to continual learning.
· Brain memory mechanisms for enhancing continual learning in foundation models.
· Brain-inspired multimodal foundation model fine-tuning, reasoning.
· Personalized solutions for cross-task and cross-distribution continual learning.
· Transparency and interpretability in continual learning models.
· Brain-inspired trustworthy distributed federated learning.
· Brain-inspired collaborative paradigms between foundation models and classical small models. · Brain-inspired generative artificial intelligence.
· Applications of continual learning in real-world domains, including healthcare, robotics, autonomous driving, smart education, etc.
· Brain-like continual learning in embodied intelligence systems, including robotics, sensorimotor control, and interactive environments.

Submission Information

Submissions are made using ScholarOne Manuscripts. Registration and access are available here: https://mc.manuscriptcentral.com/ijwis
Author guidelines must be strictly followed. Please see: https://www.emeraldgrouppublishing.com/journal/ijwis#jlp_author_guidelines

Journal Information: Scopus Journal Q2, H-index 27

Key Dates

Closing date for submissions: 31 August 2026

For more details refer here

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Events leading up to and subsequent to the promulgation of the Epstein Files Transparency Act in the United States have captured the headlines worldwide, providing a rich case study of the power and indeed weaponisation of records in an information environment characterised by mis- and dis-information.  This call for papers is not concerned with the subject matter of the Epstein Files, the individuals mentioned in them, or the politics surrounding the case, but is instead very specifically focused on the recordkeeping dimensions of this case.  

We therefore invite research papers addressing topics ranging from the evaluation of the Files from records-making and -keeping perspectives, to critical analyses of the value assigned to records by the public, and consequences for recordkeeping cultures, society, and the future of the archival profession.

List of Topic Areas

Potential topics may include, but are not limited to, the following:

• Perceptions of the value of records and recordkeeping
• Insight into recordkeeping cultures
• Consequences for the creation and capture of records
• Evaluation of the functionality of management systems from the perspective of international standards for recordkeeping
• Forensic analysis of metadata to assess authenticity, reliability, integrity and useability of records
• Power of records in the “post-truth era”
• Personal vs. Institutional recordkeeping
• Role of records managers and archivists in this case and/or similar cases having records as a key component
• Reflections on privacy and the public’s right to know

Papers concerned with the subject matter of the files, the individuals mentioned in them, or the politics surrounding the case are explicitly excluded.

Submission Information

Submissions of full manuscripts are made using ScholarOne Manuscripts. Registration and access are available here:

Submit via ScholarOne

Author guidelines must be strictly followed. Please see:

Author guidelines

Authors should select (from the drop-down menu) the special issue title at the appropriate step in the submission process, i.e. in response to “Please select the issue you are submitting to”.

Submitted articles must not have been previously published, nor should they be under consideration for publication anywhere else, while under review for this journal.

Journal Information: Scopus Journal Q2, H-Index 30

Key Dates

Opening date for manuscript submissions: 30 April 2026

Closing date for manuscript submissions: 20 October 2026
For more details refer here

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