IASC News September 2022

Upcoming IASC General Assembly (GA)

Title: Upcoming IASC General Assembly (GA)
Summary: The IASC General Assembly will take place on 7 October, 2022. All IASC members are invited to participate. The final agenda is available now.

IASC General Assembly
Friday, October 7, 2022 15:00 – 17:00 CEST (e.g., Berlin, Germany)
[6:00-8:00 Pacific Time (e.g., Los Angeles), 9:00-11:00 Eastern Time (e.g., New York), and 22:00-0:00 JST (e.g., Tokyo)]
Virtual Meeting using GoToMeeting
Please join the meeting from your computer, tablet or smartphone. Further details will be provided via e-mail in early October.
Final Agenda (as of September 9, 2022)
1. Opening
2. Approval of the Agenda
3. IASC Activity Report
a. General
b. Treasurer’s Report
c. Membership Report
d. ERS
e. ARS
g. African Members Group
h. WSC 2023
i. DSSV 2022 Conference & Outlook on DSSV 2023 Conference
k. Vote on the approval of the annual report (including finances)
4. Closing

Additional agenda items or questions can be e-mailed to the IASC President, Christophe Croux (christophe.croux@edhec.edu), or the IASC Scientific Secretary, Gentiane Haesbroeck (g.haesbroeck@uliege.be), until 72 hours before the GA, i.e., until Tuesday, October 4, 2022, 15:00 CEST. Further questions can be asked directly during the GA. All IASC members are invited to attend the GA.
The (closed) IASC Executive Committee (EC) meeting will take place on Monday, October 3, 2022, 15:00-17:00 CEST. This meeting is only open for current and newly elected IASC EC members.



New ISI-Elected Members from IASC (September 2022)

Title: New ISI-Elected Members from IASC (September 2022)
Summary: The IASC-ISI Nomination Committee congratulates a new ISI elected member from IASC as a result of the third ISI election round in 2022: Jaeyong Lee (Korea).



Data Science Career Talk organized by the IASC African Members Group (September 2022)

Title: Data Science Career Talk organized by the IASC African Members Group
Summary: IASC African Members Group presents a 90 minutes Data Science Career Talk on the theme “The importance of Data Science to academics and industry with Nigeria experience” on 23rd September, 2022.

Talk 1: The importance of Data Science to academics with Nigeria experience
Abstract: Conventionally, academic disciplines are divided into humanities, natural science, social science, formal and applied science, all revolves around data. Data is everywhere, like human, it is a living thing, it lives and die. Thus, it is imperative to understand the science behind its existence – Data Science. The important of data science ranges from efficient understanding of gigantic (big) data from multiple sources and deriving valuable insights to make smarter data-driven decisions and solutions. People and systems generate new data at over 7.5 sextillion gigabytes per day, and it is estimated that about 1.145 trillion megabytes of data are produced daily which makes it easier than ever before to collect and warehouse data. Across the globe, about 1400 colleges and universities uses predictive analytics to improve low graduation rates, readdress college experience, and guide students through a direct, data-driven path to graduation with lesser dead ends and erroneous turns. Data science is widely useful in various industry domains, including health, education (academic inclusive), agriculture, marketing, finance, policy work, and more. Harnessing the prowess of data science in academic will bring about numerous benefits such as structured database from which several industries can draw data and make sustainable decisions which in turns serve as revenue for the education sector, as well as the enhancement of a credible and actionable research work. Moreso, most local, national, continental, and global problems can be solved through quality data management culture in the field of academics.
Keywords: Data, Data Science, Academics, Insight generation, big data.

Speaker 1 Bio

Ayobami Adegoke Iyanda has a background in Statistics from the Federal University of Technology, Akure, Nigeria. Passionate about data management, data governance, strategic and evident-based decision making, and sustainable development. He has participated in qualitative and quantitative data management, State’s Census and Survey (Lagos and Kaduna), development projects and programmes, GIS Innovations, data management for individuals and corporate organizations. Currently a Data Science Fellow in Kaduna, Nigeria.

Talk 2: The importance of Data Science to industry with Nigeria experiences
Abstract: While software development remains the most common programming career in the most countries, the popularity of data science in Nigeria has steadily grown over the years as more Nigerians become enthralled by its potential and gainfully engaged in the sector. Data is more prevalent than ever in the world we live in today. According to statistics, Nigeria has the third-most software engineers in Africa. Nigerian developers have become highly sought after locally and globally. Conglomerates like Facebook, Microsoft and Apple have been the main recruiters of Nigerian tech talent in recent years. Nonetheless, there is much to be excited about as the number of people and corporations interested in the science grows.

Speaker 2 Bio

Blessing Bassey Afolayan graduated from the University of Ilorin with a degree in mathematics. She also holds two master’s degrees, one in mathematical sciences from the African Institute for Mathematical Sciences (AIMS), and the other in machine intelligence from the African Masters in Machine Intelligence (AMMI). Her research focuses on computer vision, natural language processing, and application of general machine learning. Additionally, she completed an international internship at CMU in the USA last summer where she worked on a multi-modal learning task (NLP and CV). i.e. how text and visuals are related. She also collaborated with the Smart Agriculture Innovative Center at KNU to create intelligent systems that would enhance resilient and sustainable agricultural production through the use of various AI tools. She is currently employed as a Data Scientist at 54gene, where she hopes to use a data-driven approach in pharmaceutical research and development to close a huge gap in the worldwide genomics market. This could lead to new medical advancements and innovative healthcare solutions.

Date: Friday 23rd September 2022
Time: 400pm – 5:30pm CET (3:00pm-4:30pm WAT)
Duration: 90 minutes

Speaker 1: Ayobami Adegoke Iyanda
Speaker 2: Blessing Bassey Afolayan

Penalist/Co-organizer: Dr Adenomon Monday (adenomonmo@nsuk.edu.ng)
Penalist/Co-organizer: Timothy A. Ogunleye (timothy.ogunleye@uniosun.edu.ng)
Penalist/Co-organizer: Dr Anthony Ekpo (ekpo.anthony@uam.edu.ng)



October Webinar – Data Science Year at the UDP 2022

Title: Data Science Year (DSY) UDP 2022
Summary: October data science seminar focuses on combining adaptive measurement paradigms. The challenge is to integrate both Computerized Adaptive Testing and Artificial Intelligence in one algorithm to fully optimize adaptive testing and to create a double helix of adaptive measurement. Please, mark your calendars and extend this invitation to all students. Registrations and more information at https://www.udp.cl/agenda/data-science-year-at-the-udp-2022-seminars-the-double-helix-of-computerized-adaptive-testing-and-data-science/

The main objective of the DSY-UDP 2022 is to engage and to involve students, researchers, and practitioners in the data science arena by creating a space to learn and discuss multiple topics associated with this discipline and its applications. We have organized a new virtual seminar with a prestigious exponent in the area. We invite you to join us!

Seminar: The double helix of computerized adaptive testing and data science

• Speaker: Prof. Dr. Bernard Veldkamp, University of Twente, The Netherlands
• Date: Wednesday October 5th, 2022, at 11.30 Chilean time
• Registrations at https://forms.gle/oBLCJSZu8K9zAjZy6
• Abstract. In computerized adaptive testing (CAT) the difficulty of the items is adapted to the level of the respondent. In the past twenty years, CAT has become more and more popular in the fields of psychological, health and educational measurement. One of the main reasons why CAT became so popular lies in the reduction in test length without any loss in measurement precision. CAT has made testing much more efficient. In most applications, CAT relies on psychometric models. Unfortunately, this might be quite restrictive, because of the underlying assumptions of the different kinds of psychometric models that can be applied. The question arises whether CAT fully benefits from all the less structured data that is currently available and whether it is ready for the age of big data. In many applications, (big) data coming from multiple sources is used for measurement. Besides responses to test items, underlying traits could be measured using, for example, physiological data, process data, logfile data, video data and/or combinations of them. The process of combining data from all these sources is also referred to as adaptive measurement. Within this context, adaptivity not only refers to adapting to various data sources, but also to adapting the measurement to individual differences in data availability. For some respondents, data might be missing, incomplete or not usable because of data reliability and data quality issues. To handle these kinds of challenges, AI based algorithms have been applied successfully. In this presentation, the focus is on combining both adaptive measurement paradigms, on combining psychometrics and data sciences. What are the benefits, the limitations, the opportunities and the costs? Initial attempts have been made by combining information about response times and item responses in one hierarchical framework. One step further was to apply a Bayes framework for the combination of various sources of information. The ultimate challenge though is to integrate both CAT and AI in one algorithm to fully optimize adaptive testing and to create a double helix of adaptive measurement.
• Prof. Dr. Bernard Veldkamp is Vice-Dean of Research of the Behavioral, Management and Social Sciences faculty at University of Twente. He is an expert in psychometrics, data science, and computerized adaptive testing. His research focuses on methods for data collection and data use for assessment purposes. His mission is to integrate psychometrics and data science in order to optimize measurement in the social sciences. Bernard did his PhD on the topic of automated test assembly and computerized adaptive testing. When more and more data about human behavior became available via the web, via sensors and via social media, he started to look for new methods to benefit from this data in measuring human behavior. He shifted his attention to data mining and the combination of psychometrics and data science. In 2008, he was one of the founders of the Research Center for Examination and Certification (RCEC). Bernard Veldkamp was awarded the title of Fellow of the Association for Evaluation and Assessment Europe. He is one of the authors of the book Theoretical and Practical Advances in Computer-based Educational Measurement and he is editor of the Springer book series Methodology of Educational Measurement and Assessment.

Please, mark your calendars and extend this invitation to all students. The seminar will be held virtually using the platform Zoom. Further information at https://www.udp.cl/agenda/data-science-year-at-the-udp-2022-seminars-the-double-helix-of-computerized-adaptive-testing-and-data-science/

Local Organizing Committee: Alba Martinez-Ruiz, Paula Fariña, Raúl Pezoa-Zamorano, Francisco Jara-Moroni. Supporting institutions: International Association for Statistical Computing, International Statistical Institute, and Chilean Statistical Society.


7th Latin American Conference on Statistical Computing (LACSC 2023)

Title: 7th Latin American Conference on Statistical Computing (LACSC 2023), April 3-5 2023, in Pontificia Universidad Católica del Perú.
Summary: The 7th Latin American Conference on Statistical Computing will be held in Lima (Peru), from April 3 to April 5 2023, on the theme “Statistical Learning and Spatial Data”. Information on https://sites.google.com/pucp.edu.pe/lacsc-2023/inicio

The 7th Latin American Conference on Statistical Computing (LACSC 2023) will be held in Lima, Perú, from April 3 to April 5, 2023. LACSC 2023 is jointly organized by the Department of Science and the Postgraduate School at the Pontificia Universidad Católica del Perú, the Latin American Regional Section (LARS) of the International Association for Statistical Computing (IASC), and the International Statistical Institute (ISI).

The theme of the conference is “Statistical Learning and Spatial Data”. The aim of LACSC is to foster the progress of the theory, methods and practice of statistical computing, and to become the main meeting point of the statistical computing scientific community in Latin America. This year the call for papers at the conference gives an account of the interest of academics, scientists, and professionals in methodological aspects of statistical computing and relevant applications for the community.

LACSC 2023 invites to submit papers, contributed paper sessions, and invited paper sessions before February 5, 2023. The call for papers and event information is provisionally available at https://sites.google.com/pucp.edu.pe/lacsc-2023/inicio



Call for nominations for some positions of IASC-LARS

Title: Call for nominations for some positions of IASC-LARS
Summary: The Latin American Regional Section (LARS) of the International Association for Statistical Computing (IASC) invites nominations for several positions on the Board of Directors (term 2023-2026).

The Latin American Regional Section (LARS) of the International Association for Statistical Computing (IASC) is pleased to invite nominations to fill 1 position for President-Elect (2023-2024) and between 4 and 7 positions on the Board of Directors (BoD) of the IASC-LARS), term 2023-2026.
Submissions deadline: 11 of November of 2022
Information required:
1. Position for the candidate to be considered.
2. The name of the proposed candidate.
3. A short curriculum vitae (no more than half a page) of the candidate.
See also https://iasc-isi.org/lars-board-of-directors/ and https://iasc-isi.org/lars-statute/ For more information, about the nominations (and also self-nominations) process, please write to lacsc.lars.iasc@gmail.com, with the subject: Call for nominations for some positions of IASC-LARS, 2022.



JDSSV – Fifth issue of 2022

Title: Fifth issue in current volume of Journal of Data Science, Statistics and Visualization
Summary: JDSSV has published its fifth issue of the second volume. JDSSV is completely open access. The papers can be accessed at https://jdssv.org/index.php/jdssv/issue/archive

Journal of Data Science, Statistics, and Visualization (JDSSV) has recently published its fifth issue of 2022. JDSSV is completely open access. The published papers can be accessed at

Feel free to send this announcement to all your colleagues with an interest in data science, statistics and/or visualisation.
JDSSV is an international refereed journal which creates a forum to present recent progress and ideas in the different disciplines of data science, statistics, and visualisation. JDSSV welcomes submissions to data science, statistics, and visualisation and, in particular, papers which link and integrate these subject areas.
Articles should be oriented towards a wide scientific audience, and can cover topics such as machine learning and statistical learning, the visualisation and verbalisation of data, visual analytics, big data infrastructures and analytics, interactive learning, and advanced computing. Scientific contributions should be of a high standard.
The journal explicitly welcomes contributions that include software with the aim of reproducibility of the results and application of the proposed methodology to other data by the reader. It is expected that data used in a paper are provided.
Initial submissions only require a pdf version of the manuscript with accompanying software code and necessary supplementary material. Manuscripts can be submitted online at https://jdssv.org.

Supported by
• The International Association for Statistical Computing (IASC, owner)
• International Statistical Institute (ISI)
Editorial Board
• Patrick J.F. Groenen (Editor, Erasmus University Rotterdam, The Netherlands)
• Stefan van Aelst (Editor, KU Leuven, Belgium)
• Ann Maharaj (Copy Editor, Monash University, Australia)
• Alexandre Francisco (Web Editor, Técnico Lisboa, Portugal)
Advisory Board
• Jan de Leeuw (UCLA, USA)
• David Hand (Imperial College, UK)
• Trevor Hastie (Stanford University, USA)
• Peter Rousseeuw (KU Leuven, Belgium)



JDSSV – Special issue on Statistical learning, Visual Analysis and Beyond

Title: JDSSV special issue on Statistical learning, Visual Analysis and Beyond: Call for papers
Summary: JDSSV launches a special issue on Statistical learning, visual analysis and beyond. Submission deadline is 1 December 2022.

Call for Papers for JDSSV Special Issue on Statistical Learning, Visual Analytics, and Beyond

Statistical learning and visual analytics are increasingly important topics in the era of big data and artificial intelligence. With the rapid development of information technologies, modern statistical models and visualization tools are necessary for prediction and inference.

Following the successful DSSV conference in Tainan, June 27-29, 2022, the Journal of Data Science, Statistics and Visualization launches a special issue on Statistical Learning, Visual Analytics, and Beyond with guest editors

Ray-Bing Chen (Department of Statistics, National Cheng Kung University)
Ying Chen (Department of Mathematics, National University of Singapore)
Anne Ruiz-Gazen (Toulouse School of Economics, University Toulouse 1 Capitole)

Papers should be aimed at a broad scientific audience. They can cover machine learning and statistical learning, visualization and verbalization of data, big data infrastructure and analytics, interactive learning, advanced computing, and other important topics. We welcome novel contributions from all aspects of research, including theoretical and practical modeling, learning, and/or visualization of data, providing insights into the development and application of the field. Papers that provide a comprehensive review and comparison of existing approaches and have the potential to provide new insights are also welcome.

Submissions to this special issue should be done at jdssv.org following the standard requirements of the journal and by selecting “Special Issue on Statistical Learning, Visual Analytics, and Beyond.” Submissions will follow the standard JDSSV peer review process. The deadline for submission is December 1, 2022.

We offer dual submissions, that is, papers that do not fit into the Special Issue will automatically be transferred to the regular submission channel unless the author specifies to submit only to the Special Issue. Papers will enter the review process immediately upon receipt (i.e., guest editors will not wait until the end of the submission window to start the review process). We intend to publish all accepted papers as a single special issue in 2023 after finalization of the review process.