The Data-Driven Bio-economy project (DataBio) focuses on developing new technologies and services for agriculture, fishery and forestry by exploiting the huge potential of Big Data technologies. This Lighthouse project includes 27 pilots and 91 technological components provided by 27 of the 48 project partners. It applies a standard Enterprise Architecture modelling language: “ArchiMate 3.0”. ArchiMate models are created with the tool “Modelio” which allows contributors to create ArchiMate diagrams and collaborate on a synchronized version of the models. The DataBio models cover different aspects of the project from the specification phase including requirements, goals and strategies, to the implementation phase by describing the different processes of the tasks included in the work packages and representing the technological components. This paper describes the use of ArchiMate modelling applied in the context of the DataBio research project.
- The agriculture pilots which aim to improve precision farming based on observational data and predictive analysis. - The forestry pilots which aim to improve forest monitoring, predict risks and optimize tree resources. - The fishery pilots which aim to improve vessel energy economy, logistic efficiency and predictive analysis of the fishery market as well as decreasing the environmental impact.
Taking into consideration the complexity of these tasks and the big number of
heterogeneous technological components involved, we chose ArchiMate 3.0 [
The enterprise architecture methods are used for providing organizational structure,
business processes and the IT infrastructure of an enterprise. These methods can be
applied to DataBio context, where we are interested in modelling the case studies
business objectives, processes, requirements, data pipelines and IT components.
ArchiMate language has been proven to be particularly helpful for modelling
organizations having complex IT infrastructures [
DataBio pilots allow to experiment with different technologies on real case studies
with the objective of analyzing the feasibility, the efficiency and the economic
impact. The project’s goal is to have a big data platform that integrates these
technologies at the end of the project. We define this platform as an environment in
which a combination of software components are developed to be deployed in
hardware, virtualized infrastructure, operating system, middleware or a cloud. This
environment provides through the DataBio Hub (http://databiohub.eu) [
The pilot motivation views present the reasons and factors that justify and guide the pilot choices. This step is important for introducing the pilot and for explaining the relevance of the pilot concept. The motivation diagrams contain goals which specify the main objectives of the pilots. In relation to goals, these diagrams contain certain outcomes that realize the specified goals. Moreover, these views contain the stakeholders which are the individuals, teams and organizations involved in the pilot. There are also internal and external factors represented by “driver” elements which motivate an organization to define its goals and implement the changes necessary to achieve them. In addition to these concepts, we use “requirement” elements which are functionalities that need to be implemented and “constraint” elements which are factors that limit the realization of the defined goals.
An example of the motivation view can be found in the published presentation of
the “tuna fisheries planning” pilot [
The pilot strategy views allow decision makers to elaborate a global roadmap to implement the announced objectives by defining course of actions for implementing the tasks at hand considering the capabilities of the organization and the available resources. For example, the strategy view of the fishery pilot mentioned in the previous section demonstrate how strategy elements provide leads for implementing the objective of “Improving the revenue of fish catching” (see Fig. 2). This objective can be realized by providing a decision support system on vessel operations. Given our capabilities in data collection and data analytics, we can develop the specified decision support system by collecting sensor data and extract useful information for decision makers.
DataBio pilots include various technological components with different interfaces,
different data formats (sensors data, satellite imagery, etc) and different deployment
environments. For each component, ArchiMate diagrams were created for modelling
the interface view, the deployment view and the data view. The interface view shows
the external interfaces of the component which are designed for interactions with
users or with other components through various communication protocols. For
example, the component “C07.04: Data Manager” is used for downloading and
preprocessing earth observation data in forestry and fishery pilots. Its identification
code “C07.04” is formed from component (=C), DataBio partner number (=07) and
component number of that partner (=4). This component offers three interfaces for
downloading data via Java API, REST API and command line interface (CLI). It also
offers three interfaces for consuming data from other components (see Fig. 3) [
In addition to components models, more ArchiMate diagrams were created in
order to represent the data pipelines adopted by each pilot. As mentioned before, the
different pilots are working on integrating several components into their workflow
processes. These processes are referred to as “pipelines”, as they integrate different
tasks along the data value chain from data collecting to analysing and visualizing. The
pipelines models represent the pilot lifecycle, the integrated components and the data
flow between components. For example, the component “C07.04: Data Manager”
mentioned previously is integrated in the pipeline of the fishery pilot “Oceanic tuna
fisheries planning” (see Fig. 4) [
Ingestion Engine” consumes the collected data by “Data Manager” via REST API interface.
This work is partially funded by the DataBio project (No. 732064) under European Commission’s Horizon 2020 research and innovative programme.