ChemConnect2019 is a smart cloud-based repository of experimental, theoretical and computational data. ChemConnect2019 goes beyond traditional data repositories in that the data is parsed and analysed with respect to an extensive chemical and combustion knowledge base. The parsed data is then linked allowing for efficient searching and comparison of combustion data. The goal is to have all data associated with experiments, from a device description, to the intermediate data (both computed and measured) and to their associated interpretations and the procedures and methodologies to the final published results and references to be available. Having published data linked to its dependent measurements and constants, devices, subsystems, sensors and even people and laboratories provides an effective accountability and more confidence in the data. Data entry and availability can range from private user, to user defined consortia to general public.
The linking and interconnection of data is the implementation of the concept that no data point is isolated. For a single set of published data there is a large interconnected network of interdependencies that went into producing this final result. The first raw measurement is connected to the sensor making the measurement, the calibrations associated with that sensor, the device where the sensor is found and even the person or group which made the measurement. That raw measurement is rarely the final published result, so the data is connected to other measurements and this set of measurements is connected to methodologies to interpret the results. The main utility of this interconnection is the analysis and comparison of data points for analysing uncertainties, errors and differences between the ‘same’ measurements made with the ‘same’ device by different laboratories. The technology behind the linked data is the resource description framework (RDF) that is used to analyse and search links in the world wide web.
The extent of ‘knowledge’ in a traditional repository is limited to keywords and their human interpretation. A simple example of concept relationships is units of measurements. A temperature measurement is related to the different units of temperature, Kelvin, Celsius, Fahrenheit, etc. and conversions between them. Furthermore, the concept of temperature can be related to the general concept of thermodynamics, or even how it is used, for example, as a parameter in experimental conditions. There is also a knowledge base of devices and their subsystems and sensors. Having more complete knowledge of the experimental device through descriptions and relationships between the parts of the device can help investigate sources of uncertainties within a measurement and differences in measurements between different laboratories. The technology behind the knowledge base is the ontology, a formalized description of knowledge into types, properties, and interrelationships.