Information-rich metrology (IRM) is a term that we introduce to refer to an approach where the conventional paradigm of measurement is enhanced, thanks to the introduction and active role of multiple novel sources of information. The overarching goal of IRM is to encompass and homogenise all those measurement scenarios where information available from heterogeneous sources, e.g. from the product being measured, the manufacturing process that was used to fabricate it, the internals of the measurement instrument itself, as well as from any previous measurement carried with any other instrument, is gathered and somehow incorporated with an active role into the measurement pipeline, in order to ultimately achieve a higher-quality measurement result (e.g. better metrological performance, shorter measurement times, smaller consumption of resources). A comprehensive investigation into the aspects, issues and opportunities of IRM requires a large number of test cases, and a research effort involving hardware (sensors, instrument architectures, communication networks, etc.) and software (data communication, instrument control and synchronisation, data analysis and processing), as well as significant research into mathematical and statistical modelling. As part of such an undertaking, we present here the design of an original, flexible and open-architecture, all-optical dimensional measuring system (AODMS) for measuring the geometry and surface topography of micro-scale components. The system is designed to operate in a cube of 100 mm sides, with micrometre or sub-micrometre measurement uncertainties. The key aspects of AODMS are a flexibility and open-architecture. The system is designed to accommodate a wide array of heterogeneous optical sensors, ranging from 3D measurement to 2D imaging, from prototype to commercial sensors, and is being designed to be particularly suitable to support the investigation of multi-sensor data fusion solutions [1]. The open nature of the architecture allows full flexibility in the design and configuration of the instrument control and communication software, as well as of the data analysis and processing software, thus presenting itself as an ideal platform to investigate IRM through the support to the development of solutions to enable knowledge-driven measurement, e.g. through the interaction with CAD/CAM systems, product data-management systems and any other IT-based knowledge-management solutions. The schema of the prototype AODMS are shown in Figure 1. The AODMS prototype includes a moving stage, a support and interface to a photogrammetric system dedicated to