-------- Forwarded Message --------
Call for Papers – Special Session on
“Agile Development Practices for Big Data Analytics systems
used in Small and Medium-sized Business)”
in SEKE 2022
http://ksiresearch.org/seke/seke22.html
The Thirty Fourth International Conference on Software Engineering
and Knowledge Engineering
Virtual conference at the KSIR Virtual Conference Center,
Pittsburgh, PA, USA,
from July 1 to July 10, 2022.
The conference aims at bringing together experts in software
engineering and knowledge engineering to discuss on relevant
results in either software engineering or knowledge engineering or
both. Special emphasis will be put on the transference of methods
between both domains. Submission of papers and demos are both
welcome.
Paper submission deadline: March 31, 2022
AIM
This special session in SEKE 2022 pursues to advance on the study
of emergent development practices based on the agile -such as
Scrum (Sutherland, 2010) and XP (Beck, 1999)- and lightweight
-such as the ISO/IEC 29110 standard series (ISO/IEC, 2011)-
software development paradigms that provides a valuable
alternative to the plan-driven paradigm (Boehm & Turner, 2003;
Martinez-Plumed et al., 2019) for developing Big Data Analytics
systems used in small and medium-sized business (SMBs).
RATIONALITY
Big Data Analytics (BDA) systems are software systems developed to
provide valuable insights to decision-makers exploiting Big Data
sources (Laney, 2001; Davoudian & Liu, 2020). Successful BDA
systems have been reported in the literature (Davenport, 2006) in
diverse domains such as Healthcare, Logistics, Finance, Marketing,
Retail, and Education in the last decade.
However, it was recently identified that the systematic
development of BDA systems is not usually pursued by
organizations, and despite the adaptation of a few comprehensive
development methodologies for Data Analytics systems (Martinez et
al; 2021) such as CRISP-DM, SEMMA, and KDD, many failed BDA system
development projects are frequent (Davenport & Malone, 2021).
Consequently, systematic development methodologies for BDA systems
have been demanded (Davenport & Bean, 2022).
Given that agile and lightweight development practices use small
development teams – between 3 to 10 people-, and mainly address
projects of short-term scope – between 1 to 6 months-, and thus of
small costs, these plausible practices are highly suitable to be
used for small and medium-sized business (SMBs), and ultimately to
take advantage of their available Big Data sources for SMBs
contexts (Maroufkhani et al., 2020).
TOPICS
This special session invites researchers from the disciplines of
Data Science and Software Engineering to submit high-quality
conceptual or empirical research manuscripts on agile and
lightweight development practices for BDA systems suitable to be
used in SMBs. Topics of interest for the special issue include but
are not limited to the following ones:
* Conceptual studies on frameworks of agile and lightweight tenets
and practices for BDA systems.
* Conceptual comparative studies between plan-driven development
methodologies and agile and lightweight practices for BDA systems.
* Statistical survey comparative studies on the implementation of
plan-driven development methodologies and agile and lightweight
practices for BDA systems.
* Statistical survey studies on successful implementation models
of agile and lightweight practices for BDA systems.
* Case studies on successful and failed BDA systems using agile
and lightweight practices for BDA systems.
* Simulation studies – system dynamics, discrete event,
agent-based or hybrid- on project development models of agile and
lightweight practices for BDA systems.
* Design research studies on project development models of agile
and lightweight practices for BDA systems.
* Experimental studies on project development models of agile and
lightweight practices for BDA systems.
Conceptual studies on open source platforms and tools for
developing BDA systems with agile and lightweight practices.
All previous topics are expected to be studied in the context of
SMBs.
REFERENCES
Beck, K. (1999). Embracing change with extreme programming.
Computer, 32(10), 70-77.
Boehm, B., & Turner, R. (2003). Using risk to balance agile
and plan-driven methods. Computer, 36(6), 57-66.
Davenport, T. H. (2006). Competing on analytics. Harvard Business
Review, 84(1), 98-107.
Davenport, T., & Malone, K. (2021). Deployment as a Critical
Business Data Science Discipline. Harvard Data Science Review.
https://doi.org/10.1162/99608f92.90814c32
Davenport, T. & Bean, R. (2022). The Quest to Achieve
Data-Driven Leadership: A Progress Report on the State of
Corporate Data Initiatives – Foreword. Special Report, New
Advantage Partners.
Davoudian, A., & Liu, M. (2020). Big data systems: A software
engineering perspective. ACM Computing Surveys (CSUR), 53(5),
1-39.
ISO/IEC (2011). ISO/IEC TR 29110-5-1-2:2011 Software Engineering -
Lifecycle Profiles for Very Small Entities (VSES) - Part 5-1-2:
Management and Engineering Guide: Generic Profile Group: Basic
Profile. ISO - International Organization for Standardization.
Laney, D. (2001). 3-D Data Management: Controlling Data Volume,
Velocity and Variety. META Group Research File 94m9.
Maroufkhani, P., Ismail, W. K. W., & Ghobakhloo, M. (2020).
Big data analytics adoption model for small and medium
enterprises. Journal of Science and Technology Policy Management,
11(4), 483-513.
Martínez-Plumed, F., Contreras-Ochando, L., Ferri, C., Orallo, J.
H., Kull, M., Lachiche, N., ... & Flach, P. A. (2019).
CRISP-DM twenty years later: From data mining processes to data
science trajectories. IEEE Transactions on Knowledge and Data
Engineering, 33(8), 3048-3061.
Martinez, I., Viles, E., & Olaizola, I. G. (2021). Data
science methodologies: Current challenges and future approaches.
Big Data Research, 24, 100183.
Sutherland, J. (2010). Jeff Sutherland’s Scrum Handbook. Boston:
Scrum Training Institute.
IMPORTANT DATES
Paper submission due: Midnight EST, March 31, 2022 (Extended Hard
Deadline)
Notification of acceptance: April 20, 2022
Early registration deadline: May 10, 2022
Camera-ready copy: May 10, 2022
INFORMATION FOR AUTHORS
All submissions must not be published or under consideration for
publication in a journal or in a conference with proceedings.
Papers will be evaluated based on originality, significance,
technical soundness and clarify of exposition. Depending upon the
results of evaluation a paper may be accepted as regular paper (6
pages) or short paper (4 pages) in this special session. Papers
must be written in English. An electronic version (Postscript,
pdf, or MS Word format) of the full paper should be submitted
using the following URL:
https://www.easychair.org/conferences/?conf=seke22. Please use
Internet Explorer as the browser. Manuscript must include a
200-word abstract and to have and extension either 4 or 6 pages of
double column formatted Manuscript for Conference Proceedings
(include figures and references but exclude copyright form). All
papers submitted to this special session must be named with the
prefix ADPBD_. Detailed instructions for manuscript preparation
can be consulted at:
http://ksiresearch.org/seke/seke22author.html
*
REGISTRATION INFORMATION FOR ACCEPTED PAPERS:
* Registration fee per accepted paper is 505 USD
* Please consult SEKE22 Conference Registration left tab at
http://ksiresearch.org/seke/seke22.html
PROCEEDINGS AND JOURNAL PUBLICATIONS:
Accepted papers will be published in the SEKE22 Proceedings
(online and printed versions). SEKE22 Proceedings are indexed at:
*
DBLP
<http://www.informatik.uni-trier.de/~ley/db/conf/seke/index.html>
* SCOPUS
<http://www.scopus.com/search/form/authorFreeLookup.url>
* INSPEC
<http://www.theiet.org/publishing/inspec/about/>
*
Compendex
<http://www.library.pitt.edu/articles/database_info/ei_comp.html>
* Library of Congress
<http://www.loc.gov/index.html>
ISSN for SEKE series: 2325-9000 (print)
ISSN for SEKE series: 2325-9086 (online)
Best ranked papers from the full SEKE22 conference will be
selected for a super-sized special issue of the International
Journal of Software Engineering and Knowledge Engineering (IJSEKE,
JCR with IF 1.47) to be published in November/December 2022 for
early dissemination.
CO-CHAIRS
* Prof. Manuel Mora, Autonomous University of Aguascalientes,
Mexico
* Prof. Jorge Marx Gómez, University of Oldenburg, Germany
* Prof. Hector Duran-Limon, University of Guadalajara, Mexico
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