chemometrics & quality assurance Working Group

Working Group Chemometrics & Quality Assurance

The Working Group Chemometrics & Quality Assurance was founded in 1991 under the name chemometrics & Laboratory Data Processing working group by merging the chemometrics Working Group of the Chemical Society of the GDR and the GDCh Laboratory Automation and Data Processing Working Group. In line with the focus of these two groups, the working group of the GDCh Division of Analytical Chemistry aims to combine the acquisition of data in the laboratory with its statistical evaluation, plausibility checks and corresponding quality assurance as good analytical practice. Therefore, it is particularly aimed at analysts who acquire a lot of data in the laboratory in stationary analysis and in dynamic processes and who also process it further. The working group is also interested in the application of uni- and multivariate methods of data analysis, methods for classification and pattern recognition, and the Management of "big data" and its integration into the analytical process.

The working group is present at national and international Conferences or takes the lead in organizing them. The working group also successfully participates in the analytica conference. Last but not least, aspects of the working group are regularly reflected in presentations at ANAKON . Due to the constantly increasing number and complexity of chemometrics methods, the working group has set itself the goal of developing guidelines for the practical use of chemometric methods.

The working group

promotes interdisciplinary collaboration between chemometricians in all disciplines of analytical chemistry and related fields
analyzes and observes trends and new procedures
supports method development and application
is the contact person for national and international organizations
is committed to and at international conferences and Conferences
provides advice in the areas of data analysis, quality assurance and data management, and in the definition of terms and formulations
develops guidelines for the application of chemometric methods
organizes seminars for training and vocational training.

Shortlink to this page: www.gdch.de/chemometrik

Technical focus

Analytical Quality Assurance
Descriptive and inferential statistics
data management
Expert systems, LIMS
calibration and optimization
Univariate data analysis
Multivariate data analysis (pattern recognition, multi-component analysis)
Neural networks and genetic algorithms
sampling
QSAR
signal handling
Spectra Interpretation
Statistical Design of Experiments
Time series analysis and process control
big data
Documentation and data archiving

The GDCh, the Euro- chemometrics CS network and the knowledge transfer of the University of Tübingen (WIT), the House of Technology in Essen and other organizers (especially Friedrich Schiller University Jena, Bergakademie TU Freiberg) continue to address these questions - and further education courses or lectures are offered.

Board 2024-2027

Dr. Claudia Beleites (Chair), Chemometrix GmbH, Wölfersheim
Prof. Dr. Stephan Seifert (Deputy Chair), University of Hamburg
Joscha Christmann (writing), Mannheim University of Applied Sciences
Dr. Andrea Paul (advisor), Federal Institute for Materials Research and Testing, Berlin

Permanent guest of the board
Marcel Dahms, LightGuard GmbH, Dresden

Contact the Board: ak-chemometrik@go.gdch.de

Recommended reading for self-study on multivariate data analysis

(with a subjective assessment of the content by W. Kessler)

K. Backhaus, B. Erichson et al .: Multivariate Analysis Methods - An Application-Oriented Introduction
(Quite clear but geared towards economics, originally from 1987, but re-released in 2008, still without PLS, but cluster analysis, discriminant analysis and neural networks are included)

K. Beebe, R. Pell, M. Seasholtz: Chemometrics - A Practical Guide
(very clear, without a lot of math, with many examples)

R. Brereton: Chemometrics, Data Analysis for the Laboratory and Chemical Plant
(in detail, well explained, complete mathematics, examples mainly from chemistry)

K. Danzer, H. Hobert et al .: chemometrics- Basics and Applications
(Comprehensive overview also univariate. Statistics, but only briefly explained, mathematically)

Foo-tim Chau, Yi-zeng Liang et al: Chemometrics - From Basics to Wavelet Transform
(Good overview of the various preprocessing algorithms)

B. Flury, H. Riedwyl: Applied multivariate statistics
(quite clear, but dates from 1983)

R. Henrion, G. Henrion: Multivariate data analysis
(important algorithms are explained, but quite a bit of math)

H. Hobert: Computer-aided evaluation of physicochemical measurements
(quite a bit of math)

IT Jolliffe: Principal Component Analysis
(very detailed, but very, very mathematical)

W. Kessler: Multivariate data analysis for pharmaceutical, bio and process analytics
(intended as a textbook, goes into detail on the most important procedures, includes CD with software for multivariate data analysis with exercise examples)

E. Malinowski: Factor Analysis in Chemistry
(very detailed, mathematically complete, especially for chemists, 3rd edition 2002)

H. Martens, T. Naes: Multivariate Calibration
(very detailed with complete mathematics, nevertheless understandable)

H. Martens, M. Martens: Multivariate Analysis of Quality - An Introduction
(very detailed as above, with the aim of improving quality)

M. Otto: chemometrics
(well suited as an overview, the individual procedures are very brief)

B. Vandeginste, D. Massart et al .: Handbook of Chemometrics and Qualimetrics: Part A and B
(the bible of chemometrists, very expensive, detailed, understandable, very good)

Brown et al., Comprehensive Chemometrics, Elsevier
A description of the book can be found under the following link: https://www.elsevier.com/books/comprehensive-chemometrics/brown/978-0-444-52701-1