AK chemometrics & quality control

Working Group Chemometrics & Quality Control

Tasks & Objectives

The Working Group Chemometrics & Quality Control was founded in 1991 under the name working group chemometrics & laboratory data processing by merging the Working Group chemometrics of the chemical society of the GDR and the GDCh working group laboratory automation and data processing. In accordance with the focus of these two groups, the working group of the GDCh Division of Analytical Chemistry wants to combine the acquisition of data in the laboratory with their statistical evaluation, plausibility control and corresponding quality control as good analytical practice. Therefore, analysts who collect a lot of data in the laboratory in stationary analysis and in dynamic processes and also process it further should feel particularly addressed. The working group is also interested in the application of univariate and multivariate methods of data analysis, methods for classification and pattern recognition as well as the Management of "big data" and their integration into the analytical process.

The working group is present at national and international Conferences or is responsible for organizing them. In addition, the working group successfully participates in the analytica conference. Last but not least, aspects of the working group are regularly reflected in lectures 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 the interdisciplinary cooperation of chemometricians in all disciplines of analytical chemistry and related fields
  • analyzes and observes trends and new processes
  • supports method development and application
  • is the contact for national and international organizations
  • is committed to and at international conferences and Conferences
  • works in an advisory capacity in the areas of data analysis, quality control and data management, in the definition of terms and formulations
  • develops guidelines for the application of chemometric methods
  • organizes seminars for training and vocational training.

Short link 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

Doktorandenseminar AK Chemometrik & Qualitätssicherung

Hochschule Mannheim


International Congress Center
Munich (ICM)


Working Guidelines

Data mining ...

... with multi-variable methods and support vector machines

Video tutorials


GDCh Office
Dr. Carina S. Kniep
Tel.: +49 69 7917-499

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last modified: 17.04.2024 10:59 H from Translator