Open Knowledge Blocks (OKB) is an innovative software platform that empowers its users with building blocks to quickly create value out of Open Data. Without it, those who wish to use Open Data will have to be highly skilled and they will have to invest an enormous amount of time in developing processes, models and algorithms. Some of these may even already exist. Professionals create algorithms for the tasks they are working on, then toss them aside. OKB can keep that work available for other users, with the ultimate goal to make knowledge more agile and efficient and more truly open.
The OKB platform consists of a framework with a series of modules, added dynamically and related to each other. OKB allows users to build applications using the common characteristics of the different modules. We refer to it as a “circuit board”. The interconnected modules are referred to as “blocks”. Blocks are the minimum calculation or transformation unit.
"No Code", just...
Blocks are algorithms, models, processes and other tools that transform deep and diverse raw datasets into value: processed data, analytics and real knowledge that can provide more immediate insight for their final applications.
(Cf. Section 4 for a description of the different kind of blocks used in the platform)
A block can have several ports through which it communicates externally (data streams) or with another block. Each port can receive or supply one or more values. These are the minimum information units. They can be associated with a fixed value, a user-entered value, or an association with another port. These associations will be referred to as “relationships”.
Open Knowledge Blocks (OKB), is a collaborative platform for the shared use of independently developed blocks of knowledge. Main features include:
Supporting access to diverse data repositories, combining both open and private sources, and both static and time-dependent repositories, ensuring that analytical results of the platform are always up to date and relevant for maximum value (lacking in the current state of the art). A key application of this feature is to better support and accelerate Internet of Things (IoT) applications.
Allows users to easily create processes (algorithms, data models, etc.) in the form of standard blocks to extract value from raw data, by re-using, adapting and combining “blocks” from other disciplines and applications. For example, adapting and re-using valuable numerical models and algorithms originally designed for environmental analysis, and using them for smart city applications.
Enables an open ecosystem marketplace of these blocks in private and public repositories, greatly expanding the availability of re-useable resource-saving models, algorithms, etc. to process data.
No-code. Lowers barrier to entry by providing an accessible and intuitive user interface that allows analysts to rapidly use, create new blocks of processes or combine already existing blocks to form new ones, with no need for any programming skills.