-------- Forwarded Message --------
Subject: [WI] [CFP] Special Issue "Advances in Explainable Artificial
Intelligence" - MDPI Information, open access
Date: Thu, 29 Oct 2020 15:24:30 +0100
From: Fulvio Frati <fulvio.frati(a)unimi.it>
Reply-To: Fulvio Frati <fulvio.frati(a)unimi.it>
To: wi(a)lists.uni-karlsruhe.de
Special Issue "Advances in Explainable Artificial Intelligence"
[Apologies if you receive multiple copies of this CFP]
****************************************************************
Special Issue "Advances in Explainable Artificial Intelligence"
MDPI Information, open access
Website:
https://www.mdpi.com/journal/information/special_issues/advance_explain_AI
****************************************************************
The following special issue will be published in Information (ISSN
2078-2489, https://www.mdpi.com/journal/information), and is now open to
receive submissions of full research articles and comprehensive review
papers for peer-review and possible publication.
The papers will be published, after a standard peer-review procedure, in
Open Access journal Information.
The official deadline for submission is 31 May 2021. However, you may
send your manuscript at any time before the deadline.
If accepted, the paper will be published very soon.
** SPECIAL ISSUE INFORMATION
Machine Learning (ML)-based Artificial Intelligence (AI) algorithms can
learn from known examples of various abstract representations and models
that, once applied to unknown examples, can perform classification,
regression, or forecasting tasks, to name a few.
Very often, these highly effective ML representations are difficult to
understand; this holds true particularly for Deep Learning models, which
can involve millions of parameters. However, for many applications, it
is of utmost importance for the stakeholders to understand the decisions
made by the system, in order to use them better. Furthermore, for
decisions that affect an individual, the legislation might even advocate
in the future a “right to an explanation”. Overall, improving the
algorithms’ explainability may foster trust and social acceptance of AI.
The need to make ML algorithms more transparent and more explainable has
given rise to several lines of research that form an area known as
explainable Artificial Intelligence (XAI).
Among the goals of XAI are adding transparency to ML models by providing
detailed information about why the system has reached a particular
decision; designing more explainable and transparent ML models, while at
the same time maintaining high-performance levels; finding a way to
evaluate the overall explainability and transparency of the models and
quantifying their effectiveness for different stakeholders.
The objective of this Special Issue is to explore recent advances and
techniques in the XAI area.
Research topics of interest include (but are not limited to):
- Devising machine learning models that are transparent-by-design;
- Planning for transparency, from data collection up to training, test,
and production;
- Developing algorithms and user interfaces for explainability;
- Identifying and mitigating biases in data collection;
- Performing black-box model auditing and explanation;
- Detecting data bias and algorithmic bias;
- Learning causal relationships;
- Integrating social and ethical aspects of explainability;
- Integrating explainability into existing AI systems;
- Designing new explanation modalities;
- Exploring theoretical aspects of explanation and interpretability;
- Investigating the use of XAI in application sectors such as
healthcare, bioinformatics, multimedia, linguistics, human–computer
interaction, machine translation, autonomous vehicles, risk assessment,
justice, etc.
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-------- Forwarded Message --------
Subject: [AISWorld] JSAIS Special CFP and Virtual Research Workshop
Date: Thu, 29 Oct 2020 15:04:03 +0000
From: Jignya Patel <jpatel(a)fit.edu>
To: aisworld(a)lists.aisnet.org <aisworld(a)lists.aisnet.org>
Journal of the Southern Association of Information Systems (JSAIS)
Special Call for Papers: "IS in the Time of Covid-19"
Deadlines
March 1, 2021: Submit Extended Abstract for Presentation in JSAIS
Virtual Research Workshop at https://papers.southernais.org
March 26, 2021: JSAIS Virtual Research Workshop
June 1, 2021: Submit Full Paper at https://aisel.aisnet.org/jsais/
August 1, 2021: Notification of Expedited First Round review - Workshop
Participants
September 1, 2021: Notification of First Round review - General Submission
October 1, 2021: Revised manuscript submission
Fall 2021: Notification of Final decisions for publication in JSAIS
Special Issue
Description
Advances in Information Systems (IS) are constantly changing the way we
work, live, and learn. IS has impacted the way we communicate and
collaborate for decades. However, the critical importance of IS was
brought to the forefront by the COVID-19 pandemic. The COVID-19 pandemic
suddenly and dramatically impacted all aspects of human life, most
notability the traditional workday and education. Organizations found
themselves in a situation where they were racing to rework traditional
face to face situations and experiences using IS.
While we are all ready for the pandemic to come to an end, some of the
changes and effects of COVID-19 will likely remain. This special call of
papers seeks to explore how IS supports work, life, and learning during
a pandemic. Example topics include, but are not limited to:
* Tools for remote work/education: working from home, meetings with
remote teammates
* New ways of getting work done: techniques or IS artifacts used to
allow for remote work
* Technologies for the future of work/future of education: networking,
augmented reality, virtual reality, wearable devices, and human-robot
collaboration
* Supporting worker well-being: maintaining work-life boundaries,
supporting physical movement, and facilitating work attachment and
detachment - mindfulness, student/worker remote support
* Creating new skills needed for remote work: opportunities to learn new
skills
* Inclusion and accessibility: technology that is built for equality and
technology that supports all abilities
* Security and privacy: protecting work situations from malicious actors
and maintaining Privacy
* Novel ways of measuring outcome: new types of assessment for remote work
* IS applications that support future jobs, work practices, and education
* Software adoption: adoption and continued use new software tools
Research Workshop Extended Abstract Submission
Authors that participate in the research workshop will have their papers
reviewed and considered for acceptance into JSAIS Special Issue on an
expedited schedule. Workshop presentations should focus on the research
proposal for the Special Issue. Extended abstracts should not exceed 2
pages and presentation should not exceed 10-15 minutes.
JSAIS Special Issue Submission
Articles submitted to should not exceed 8 or 12 pages, including all
text, the abstract, keywords, bibliography, biographies, and table text.
An article should have no more than 20 references. The abstract should
be no more than 150 words and should describe the overall focus of your
manuscript. Articles should be accompanied by a short biographical
sketch containing, in the following order: your current position and
affiliation; current research interests; highest academic degree, area
of study, and institution; professional affiliations; and postal and
email addresses.
JSAIS Virtual Research Workshop Schedule
Friday March 26, 2021
900-930am: Guest Speaker
930-940am: Break
940-1040a,: Breakout Sessions (4-5 with 3-4 papers in each session) -
Research Proposal Presentations and Peer Discussion
1040-1050am: Break
1050a-1200pm: Overview of Breakout Sessions, Next Steps for JSAIS
Special Issue Submission
Any questions, concerns, comments can be emailed to
info(a)southernais.org<mailto:info@southernais.org>.
Jignya Patel, Ph. D
Assistant Professor of Information Systems
College of Business
Florida Institute of Technology
2202 S Babcock St, Room 208
Melbourne, Florida 32901
Email: jpatel(a)fit.edu<mailto:jpatel@fit.edu>
Ph: 321.674.7391
_______________________________________________
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-------- Forwarded Message --------
Subject: [AISWorld] CFP: MWAIS 2021 - Submission Deadline: February 26,
2021
Date: Wed, 28 Oct 2020 07:44:00 -0500
From: Jacob Young <jayoung(a)fsmail.bradley.edu>
To: aisworld(a)lists.aisnet.org
MWAIS 2021 Conference
Midwest United States Association for Information Systems
16th Annual Conference
May 20-21, 2021
Foster College of Business
Bradley University
Peoria, Illinois
https://mwais2021.com
***Call for Papers***
The 16th Annual Midwest Association for Information Systems Conference
seeks to provide an intimate environment to facilitate the sharing of ideas
and findings in the area of information systems. We invite submissions of
completed manuscripts, research-in-progress papers, panel proposals,
workshop, and tutorial proposals addressing behavioral, organizational, and
technical aspects of information systems.
***Manuscript Submission Deadlines***
Full-length and Research-in-progress papers: February 26, 2021
Panels, Workshops, and Tutorial Proposals: March 5, 2021
Notification of Acceptance/Rejection: April 2, 2021
Final Submission Deadline for Camera-Ready Copy: April 16, 2021
Author(s) Registration Deadline: April 16, 2021
***Submission Guidelines***
Submissions should be posted electronically in MS Word or PDF at
https://easychair.org/conferences/?conf=mwais2021 by the submission
deadline. The initial blinded submission template is available:
https://mwais2021.files.wordpress.com/2020/10/mwais2021_submission_template…
The camera-ready submission template is available
https://mwais2021.files.wordpress.com/2020/10/mwais2021_final_template.docx
Completed and research-in-progress submissions will undergo a double-blind
review process by at least two reviewers. To facilitate the blind review,
please do not include any author or affiliation identification on any page
(except the separate cover page), in headings/footers, or in the properties
of the submitted file. Previously published work or work under review
elsewhere is not eligible for submission. All submissions should be posted
electronically in either MS Word or PDF using the submission templates.
For accepted research, the MWAIS 2021 proceedings will be available through
the Association for Information Systems Electronic Library (AISeL). At
least one author of each accepted paper must register for the conference no
later than April 16, 2021, for the paper to be included in the conference
proceedings.
***Full Length Submissions***
You may submit a full length (not to exceed six single-spaced pages with
approximately 2,500 words, including all figures, tables, appendices, and
references), original, and previously unpublished manuscript. The research
may be conceptual, empirical or applied. Accepted papers will be published
in the conference proceedings in their entirety. Select papers included in
the MWAIS 2021 conference will be considered for an expedited review
process and possible inclusion in the Journal of the Midwest Association
for Information Systems (JMWAIS) (http://www.jmwais.org).
In addition, the top three conference papers will be awarded best paper
awards sponsored by the Midwest Association for Information Systems.
Authors of these papers who choose to submit their papers to the JMWAIS
will be awarded a monetary prize and these papers will undergo an expedited
review process by the journal.
***Research-in-Progress***
You may submit research-in-progress proposals (abstracts) or a summary of
tentative results of the study to date in a 1,500-2,000 word paper with a
maximum of two figures/tables.
***Panel, Workshop, and Tutorial Submissions***
Individuals interested in conducting a panel, workshop, or tutorial dealing
with technological, managerial, professional, teaching, societal, national
or international issues of information technology management are invited to
submit a 500-1,000 word proposal covering the objectives, issues to be
covered, and the names/addresses of any other panel, workshop, or tutorial
members. The method of presentation is at the submitter's discretion. A
computer lab will be available if needed. However, the submitter has the
responsibility for providing his/her own participants (such as panel
members). All accepted proposals will appear in the conference proceedings.
(Note: All panel, workshop, and tutorial members must register for the
conference.)
***Potential Topics***
Full-length papers, research-in-progress proposals, and panel, workshop, or
tutorial proposals are invited in, but not limited to, the following areas:
* Accounting Information Systems
* Adoption and Diffusion of IS/T
* Big Data Analytics
* Business Intelligence
* Business Process Management
* Bring Your Own Device (BYOD) and its Implications
* Cloud Computing and Services
* Computing and Ethics
* Database Management Technologies
* Decision Support Technologies
* Design Science
* Distance Learning Technologies
* e-Collaboration in Organizations
* Economic Value of IS/T
* Electronic Business Technologies and Management
* Energy Informatics
* Enterprise Resource Planning
* FinTech
* Global IT Management
* Green Computing and Sustainability
* Health Care Informatics
* Human Computer Interaction
* Information Security Management
* InsurTech
* IT and Small Businesses
* IT Business Value
* Information Systems and Sustainability (Green IS)
* IS and Grand Societal Challenges (Inequality, Climate Change, Cyber
Security, etc.)
* Information Technology Education
* Information Technology Standards
* Intelligent Information Systems
* IT Evaluation Methods and Management
* IT Management in Healthcare
* IT Teaching Cases
* Knowledge Management
* Medical Information Technology
* Mobile Computing & Commerce
* Multimedia Information Management
* Object Oriented Technology
* Online and Blended Teaching and Learning
* Open Source Technologies and Systems
* Project Management
* Software Engineering
* Software Process Improvement
* Strategic IT Management
* Telecommunications and Networking Technologies
* Virtualization Technologies and Management
* Virtual Organizations and Society
***Student Support***
MWAIS will waive the registration fee for students whose papers are
accepted and who will be presenting at the conference (one student per
paper).
***Submission or Volunteer Inquiries***
For additional information about submissions or helping out as a reviewer
or session chair, please contact the conference chair by e-mail: Jake Young
(jayoung(a)fsmail.bradley.edu)
*Jacob A. Young, D.B.A.*
Director, Center for Cybersecurity
Assistant Professor, Management Information Systems
Department of Entrepreneurship, Technology and Law
Foster College of Business
Bradley University
_______________________________________________
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-------- Forwarded Message --------
Subject: [WI] Special Issue on Explainable AI for Sentiment Analysis in
KBS (impact factor: 5.921)
Date: Wed, 28 Oct 2020 03:04:28 +0000
From: Erik Cambria <cambria(a)ntu.edu.sg>
Reply-To: Erik Cambria <cambria(a)ntu.edu.sg>
To: cfp(a)sentic.net <cfp(a)sentic.net>
TITLE
Explainable Artificial Intelligence for Sentiment Analysis
EDITORS
Erik Cambria, Nanyang Technological University, Singapore
Akshi Kumar, Delhi Technological University, India
Mahmoud Al-Ayyoub, Jordan University of Science and Technology, Jordan
Newton Howard, Oxford University, UK
JOURNAL
Knowledge-Based Systems (impact factor: 5.921)
CFP WEBLINK
sentic.net/xaisa.pdf
BACKGROUND AND MOTIVATION
Artificial-intelligence driven models, especially deep learning models,
have achieved state-of-the-art results for various natural language
processing tasks including sentiment analysis. We get highly accurate
predictions using these in conjunction with large datasets, but with
little understanding of the internal features and representations of the
data that a model uses to classify into sentiment categories. Most
techniques do not disclose how and why decisions are taken. In other
words, these black-box algorithms lack transparency and explainability.
Explainable artificial intelligence (XAI) is an emerging field in
machine learning that aims to address how artificial-intelligence
systems make decisions. It refers to artificial-intelligence methods and
techniques that produce human-comprehensible solutions. XAI solutions
will enable enhanced prediction accuracy with decision understanding and
traceability of actions taken. XAI aims to improve human understanding,
determine the justifiability of decisions made by the machine, introduce
trust and reduce bias.
This special issue aims to stimulate discussion on the design, use and
evaluation of XAI models as the key knowledge-discovery drivers to
recognize, interpret, process and simulate human emotion for various
sentiment analysis tasks. We invite theoretical work and review articles
on practical use-cases of XAI that discuss adding a layer of
interpretability and trust to powerful algorithms such as neural
networks, ensemble methods including random forests for delivering near
real-time intelligence.
Concurrently, works on social computing, emotion recognition and
affective computing research methods which help mediate, understand and
analyze aspects of social behaviors, interactions, and affective states
based on observable actions are also encouraged. Full length, original
and unpublished research papers based on theoretical or experimental
contributions related to understanding, visualizing and interpreting
deep learning models for sentiment analysis and interpretable machine
learning for sentiment analysis are also welcome.
TOPICS OF INTEREST
- XAI for sentiment and emotion analysis in social media
- XAI for aspect-based sentiment analysis
- XAI for multimodal sentiment analysis
- XAI for multilingual sentiment analysis
- XAI for conversational sentiment analysis
- Ante-hoc and post-hoc XAI approaches to sentiment analysis
- Semantic models for sentiment analysis
- Linguistic knowledge of deep neural networks for sentiment analysis
- Explaining sentiment predictions
- Trust and interpretability in classification
- SenticNet 6 and other XAI-based knowledge bases for sentiment analysis
- Sentic LSTM and other XAI-based deep nets for sentiment analysis
- Emotion categorization models for polarity detection
- Paraphrase detection in opinionated text
- Sarcasm and irony detection in online reviews
- Bias propagation and opinion diversity on online forums
- Opinion spam detection and intention mining
TIMEFRAME
Submission Deadline: 25th December 2020
Peer Review Due: 1st April 2021
Revision Due: 15th July 2021
Final Decision: 30th September 2021
________________________________
CONFIDENTIALITY: This email is intended solely for the person(s) named
and may be confidential and/or privileged. If you are not the intended
recipient, please delete it, notify us and do not copy, use, or disclose
its contents.
Towards a sustainable earth: Print only when necessary. Thank you.
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-------- Forwarded Message --------
Subject: [AISWorld] CFP: MENACIS Virtual Free-of-Charge Conference
(December 3-4, 2020), Morocco
Date: Tue, 27 Oct 2020 16:07:59 +0000
From: Ibtissam Zaza <iz13(a)my.fsu.edu>
To: aisworld(a)lists.aisnet.org <aisworld(a)lists.aisnet.org>
CFP: MENACIS Virtual Free-of-Charge Conference (December 3-4, 2020), Morocco
Virtual Free-of-charge Conference
https://menacis2020.now.sh/index.html
Paper submission deadline is November 15th, 2020.
MENACIS welcomes your submissions of completed research and research in
progress to the following conference tracks:
* Track 1. General track on information system on business and society
* Track 2. The open innovation in the industry
* Track 3. Digital transformation to innovation
* Track 4. Organizational development and innovation strategies
* Track 5. Impact of technology and innovation on business
* Track 6. IS and Sustainability
* Track 7. COVID-19 crisis impact on innovation
Potential topics of interests include, but are not limited to:
* Open Innovation for different aspects of development
* Strategies for combining digital models with closed innovation models
in R&D programs (i.e outsourcing, crowdsourcing, etc).
* Introduction, management, and adoption of ICT across organizational
boundaries.
* ICT in identifying new markets and new product development settings.
* Business Models that capitalize on reinforcements from external
knowledge sources.
* Approaches to intellectual property protection and management from
external organizations.
* Public policies aimed at promoting and improving the climate for
information systems.
* Lessons from successful/ failed open innovation implementations.
* Disruptive potential to open innovations.
* Digital transformation and sustainability….
* Decision support system: emerging tools for organization management
* Innovation in government
* Social networking in developing countries (DC)
* Impact of technology and innovation on business
Submission Guidelines:
Paper submission deadline is November 15th, 2020.
All papers must be original and not simultaneously submitted to another
journal or conference.
* Research Papers are full-length papers (up to 12 pages, single-space,
12 Times New Roman, 1-inch margins, excluding references).
* Research-in-Progress papers are promising but incomplete research
projects that will benefit from the feedback of other MENACIS
participants (up to 7 pages, single-space, 12 Times New Roman, 1-inch
margins, excluding references).
Please submit your paper to
https://easychair.org/account/signin?l=CtsZrNNgxnKJlO9SFxFLWk#
Accepted papers can be invited to submit to the special issues in the
following journals:
* Pacific Asia Journal of the Association for Information
Systems<https://aisel.aisnet.org/pajais>
* Information Systems Management and Innovation
(ISMI)<https://revues.imist.ma/?journal=ISMI>
The MENAIS-2020 additionally offers competitive publication outlets in
Scopus indexed journals.
Email questions about submissions to: menacis2020(a)gmail.com
Sam Zaza, PhD
College of Business
Florida State University
126 Rovetta Business Building
821 Academic Way
Tallahassee, FL 32306-1110
_______________________________________________
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-------- Forwarded Message --------
Subject: [AISWorld] Call for Papers: JDIQ - Special Issue on Deep
Learning for Data Quality
Date: Tue, 27 Oct 2020 08:55:42 -0700
From: Donatello Santoro <donatello.santoro(a)unibas.it>
To: aisworld(a)lists.aisnet.org
___________________________________________________________
CALL FOR PAPERS
ACM Journal of Data and Information Quality
Special Issue on Deep Learning for Data Quality
___________________________________________________________
* Guest Editors:
-Paolo Papotti, EURECOM (France)
-Donatello Santoro, Università degli Studi della Basilicata (Italy)
-Saravanan Thirumuruganathan, QCRI (Qatar)
* Context:
Deep learning (DL) has been recently used successfully for monitoring
and improving data quality (DQ). Examples include data integration
tasks such as entity resolution and schema matching, data cleaning
tasks such as error detection and repair, and data curation in general.
The data curation community has successfully leveraged deep learning
techniques spanning from word embeddings to transformers to achieve
state-of-the-art performance on well established data quality benchmarks.
Nevertheless, there is still an open debate on which technical solution
performs best for relational data and under which setting.
Despite a promising start, deep learning for data quality has a long
way to go in achieving the human level performance that it has achieved
in domains such as computer vision, natural language processing, and
speech recognition. While there have been some substantial improvements
in specific tasks such as entity resolution and data repair/imputation,
many of the other data quality tasks (such as data discovery, data
profiling, data integration, record fusion) are yet to fully benefit from
the DL revolution. Also, it is not clear how to push DL techniques to
get the same level of adaptation achieved by more traditional logic-based
methods. For example, interpretability of the models is a key stumbling
block.
How can one develop DQ explanations that are consumed by non-experts?
Should the explanation be generated individually for each error?
Or can it be summarized so that the user gets a high level overview?
Finally, DL data quality tools need novel explanation algorithms which
are not a priority for DL researchers as the architecture is quite specific.
This special issue focuses on deep learning used for assessing and
improving
the quality of data. Thus, the issue is addressed to those members from the
data science community proposing novel methods, architectures and
algorithms
capable of integrating, cleaning and profiling relational data sources
with supervised and unsupervised approaches.
* Topics:
The goal of this special issue is to collect recent advances, innovations,
and practices in ML, data and software engineering for building techniques,
solutions, and systems that support users in assessing and improving
relational data quality. The topics of interest are inspired from the
themes above and include, but are not limited to:
- Deep learning methods for data integration and data cleaning
- Deep learning methods for metadata discovering/profiling, including
constraint discovery
- Making deep learning methods for data quality interpretable
- Experimental studies of deep learning methods for data quality
- Deep learning methods for curating data in domain specific applications
- Scalability of deep learning methods for data quality (speeding up DL
for DQ using GPU)
- Characterization of data quality tasks that are more amenable to deep
learning
- Reducing the need of large amount of training data in supervised
approaches
(weak- and self-supervision for data quality)
- Combination of logic based and DL based methods for data quality
* Expected contributions:
We welcome three types of research contributions:
- Full research papers describing a novel contribution to the field (up to
25 pages)
- Experience papers discussing important lessons learned (up to 20 pages)
- Vision and Challenge papers (up to 7 pages)
- Survey papers (up to 30 pages)
* Submission Format:
JDIQ welcomes manuscripts that extend prior published work, provided they
contain at least 30% new material, and that the significant new
contributions
are clearly identified in the introduction.
Submission guidelines with Latex (preferred) or Word templates are
available at:
http://jdiq.acm.org/authors.cfm#subm
To submit, select the paper type
"SI: Deep Learning for Data Quality"
* Important Dates:
- Submission deadline: March 1, 2021
- First notification: May 15, 2021
- Revised manuscripts deadline: July 15, 2021
- Final notification: September 15, 2021
- Camera-ready manuscripts: October 15, 2021
- Estimated publication date: January 2022
_______________________________________________
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-------- Forwarded Message --------
Subject: [AISWorld] CFP: Special Issue on Cybersecurity Incident
Response in Organizations - Computers & Security
Date: Sun, 25 Oct 2020 21:11:32 +0000
From: Sean Maynard <sean.maynard(a)unimelb.edu.au>
To: aisworld(a)lists.aisnet.org <aisworld(a)lists.aisnet.org>
Special Issue on Cybersecurity Incident Response in Organizations
https://www.journals.elsevier.com/computers-and-security/call-for-papers/sp…
Submission Deadline: May 1, 2021
Guest Editors
Atif Ahmad, University of Melbourne, Australia atif(a)unimelb.edu.au
Sean Maynard, University of Melbourne, Australia seanbm(a)unimelb.edu.au.
Richard Baskerville, Georgia State University, USA baskerville(a)acm.org
Special Issue Details
The evolving cyber-threat landscape has given rise to new and
increasingly potent attacks against organizations. Human attackers use
sophisticated tools and techniques to disrupt and destroy cyber
infrastructures, deny organizations access to IT services, and steal
sensitive information including Intellectual Property, trade secrets and
customer data.
Incident response takes place under considerable time pressure in a
dynamic and rapidly changing environment with high levels of information
load, information diversity and task uncertainty. Effective response
requires command, control and coordination of diverse teams of
organizational stakeholders as they develop situation awareness, adapt
to the rapidly evolving situation, raise the necessary resources, and
respond to threats.
The practice of incident response is a relatively under-studied area of
research. The purpose of this special issue is to collect and
disseminate the latest advances in this area for a broad audience. We
seek submissions that study the real-world problem of incident response
and contribute sound practical advice to industry. Papers could employ
qualitative, quantitative, mixed-methods and design science techniques.
Exploratory case studies and action research are welcome.
Topics of interest include (but are not limited to):
- In-depth and revelatory case studies of incident response practice in
organizations
- Maturity models of incident response
- Novel conceptualizations of the practice of incident response (e.g.
response agility, communication and coordination, organizational
learning, knowledge sharing, sense-making, situation awareness, process
improvement)
- Management of the incident response function (e.g. strategy, policy,
risk, training)
- Adoption of novel technologies for incident response (e.g. data-fusion
and real-time analytics)
Important Dates
Submission Deadline: May 1, 2021
First Round of Reviews: Aug 1, 2021
Second Round of Reviews: Feb 1, 2022
Final Decision: May 1, 2022
_______________________________________________
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-------- Forwarded Message --------
Subject: [AISWorld] Publication of Special Series on "COVID-19 and IT
Education" in Journal of Information Technology: Research
Date: Sun, 25 Oct 2020 22:47:32 +0000
From: Christopher Cheong <christopher.cheong(a)rmit.edu.au>
To: aisworld(a)lists.aisnet.org <aisworld(a)lists.aisnet.org>
RMIT Classification: Trusted
Dear colleagues,
We are pleased to announce the publication of the "COVID-19 and IT
Education" Special Series in the Journal of IT Education: Research.
Table of contents
COVID-19 and IT Education: Introduction to the Special
Series<https://www.informingscience.org/Publications/4654?Source=%2FJournals%2FJIT…>
Christopher Cheong, Jo Coldwell-Neilson, Tian Luo, Kathryn MacCallum
Factors Affecting the Quality of E-Learning During the COVID-19 Pandemic
from the Perspective of Higher Education
Students<https://www.informingscience.org/Publications/4628?Source=%2FJournals%2FJIT…>
Kesavan Vadakalu Elumalai, Jayendira P Sankar, Kalaichelvi R, Jeena Ann
John, Nidhi Menon, Mufleh Salem M Alqahtani, May Abdulaziz Abumelha
Preparedness of Institutions of Higher Education for Assessment in
Virtual Learning Environments During the COVID-19 Lockdown: Evidence of
Bona Fide Challenges and Pragmatic
Solutions<https://www.informingscience.org/Publications/4615?Source=%2FJournals%2FJIT…>
Talha Abdullah Sharadgah, Rami Abdulatif Sa'di
Business (Teaching) as Usual Amid the COVID-19 Pandemic: A Case Study of
Online Teaching Practice in Hong
Kong<https://www.informingscience.org/Publications/4620?Source=%2FJournals%2FJIT…>
Tsz Kit Ng, Rebecca Reynolds, Man Yi (Helen) Chan, Xiu Han Li, Samuel
Kai Wah Chu
Secondary School Language Teachers’ Online Learning Engagement during
the Covid-19 Pandemic in
Indonesia<https://www.informingscience.org/Publications/4626?Source=%2FJournals%2FJIT…>
Anita - Lie, Siti Mina Tamah, Imelda - Gozali, Katarina Retno
Triwidayati, Tresiana Sari Diah Utami, Fransiskus - Jemadi
Regards,
Chris
Associate Professor Christopher Cheong, FHEA
Chair, Business College Human Ethics Advisory Network (BCHEAN)
Department of Information Systems and Business Analytics
School of Accounting, Information Systems and Supply Chain
RMIT University
Melbourne, Australia
Tel.: +61 3 9925 5793
URL:
www.rmit.edu.au/contact/staff-contacts/academic-staff/c/cheong-associate-pr…<http://www.rmit.edu.au/contact/staff-contacts/academic-staff/c/cheong-assoc…>
CRICOS Provider Number: 00122A
Editor-in-Chief, Journal of Information Technology Education: Research
(JITE:Research)<https://www.informingscience.org/Journals/JITEResearch>
Editor-in-Chief, Journal of Information Technology Education:
Innovations in Practice
(JITE:IIP)<https://www.informingscience.org/Journals/JITEIIP>
Governor, Informing Science Institute<https://www.informingscience.org/>
Chair, Informing Science Institute<https://www.informingscience.org/>
(ISI) Ethics Policy Committee
Chair, Informing Science Institute<https://www.informingscience.org/>
(ISI) Ethics Investigation Committee
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