Design and Development of a Compound DSS for Laboratory Research - Efficient Decision Support Systems: Practice and Challenges from Current to Future - page 476

2. Types of DSS suitable for laboratory research
There are several classifications and taxonomies of DSS applications. A brief overview of
DSS classifications brings French (French et al., 2009). For this work, the AIS SIGDSS 1
classification is used. It is today the most common and widespread DSS classification,
popular with many authors, such as Power (Power, 2000) or Turban (Turban et al., 2008).
This classification divided DSS into five main categories as follows:
 Data-driven DSS , which are primarily based on the data and their transformation into
information,
 Model-driven DSS , which puts the main emphasis on the use of simulation and
optimization models,
 Knowledge-driven DSS , characterized by the use of knowledge technologies to meet
the specific needs of decision-making process,
 Document-driven DSS , that helps users acquire and process unstructured documents
and web pages, and
 Communications-driven and group DSS , which includes all systems using
communication technologies to support collaboration of user groups.
Of course, all listed categories can be combined to create compound or hybrid systems. For
laboratory research purposes, the combination of data- and knowledge-driven DSS seem to
be the best solution. Laboratory research is based on diagnostics. Important attributes with
which the diagnostic processes work are data, information and knowledge. Knowledge
transforms data into information and information (diagnosis) is the output of diagnostic
process (Tupa, 2008). The diagnostic process is schematically illustrated in Figure 1.
Fig. 1. Process view of diagnostics (Tupa, 2008)
As already mentioned, Data- and Knowledge-driven decision support systems are the most
appropriate types of DSS for laboratory research. The next two subchapters are focused on
definition, characteristics, and the key features of these two types.
2.1 Data-driven DSS
A Data-driven decision support system is defined as an interactive computer-based system
that helps decision-makers use large database. Data-driven DSS primarily rely on data and
their processing into information, along with the presentation of this information to a
decision maker (Turban et al., 2008). The main goal of such systems is to help users
transform data into information and knowledge. Users of these systems can perform
1 Association for Information Systems Special Interest Group on Decision Support System