© 2022 Copyright for this paper by its authors.
Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
CEUR Workshop Proceedings (CEUR-WS.org)
© 2022 Copyright for this paper by its authors.
Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
CEUR Workshop Proceedings (CEUR-WS.org)
Small Data and Data Centric AI: Case Study
from the Master’s Program in Artificial
Intelligence at Sofia University
Maria Nisheva-Pavlova
1, 2
and Bilyana Dobreva
1
1
Faculty of Mathematics and Informatics – Sofia University St. Kliment Ohridski, 5
James Bourchier Blvd., Sofia, 1164, Bulgaria
2
Institute of Mathematics and Informatics – Bulgarian Academy of Sciences, 8 Acad.
Georgi Bonchev Str., Sofia, 1113, Bulgaria
Abstract
Recently, the term “small data” has become essential in the field called
“data centric AI”. While big data is used for different types of correlation
analysis, small data is the real source for finding causal relationships
between the objects studied. The paper discusses the experience in creating
small datasets and transfer learning, gained in the Master’s program in
Artificial Intelligence at the Faculty of Mathematics and Informatics at
Sofia University, focusing on some good examples of student projects.
Keywords
Big data, small data, data centric AI, transfer learning, question answering
system
1. Introduction
After the initial wave of research and technological developments related to
big data, the interest in the so-called small data and especially in the methodolo-
gies for creating appropriate small datasets and their use in the eld of data cen-
tric articial intelligence is constantly growing. Correctly constructed small data
are commonly used by people in decision-making in various areas of particular
public importance. The creation and use of suitable small datasets, along with the
application of proper kinds of transfer learning, is the basis of data centric arti-
cial intelligence. In recent years, a number of successful projects (mostly pre-
diploma and diploma projects) of students from the Master’s program in articial
intelligence at the Faculty of Mathematics and Informatics at Soa University are
addressing this issue.
Information Systems & Grid Technologies: Fifteenth International Conference ISGT’2022, May 27–28, 2022, Sofia, Bulgaria
EMAIL: marian@fmi.uni-sofia.bg (M. Nisheva-Pavlova); bddobreva@uni-sofia.bg (B. Dobreva)
ORCID: 0000-0002-9917-9535 (M. Nisheva-Pavlova)
