Deriving from diverse and vastly growing sources, digital data is emerging as the essential resource to organizations, enabling them to by enlarging their body of knowledge advance in highly demanding business situations and markets. The means enabling holistic reasoning and modeling business constellations including varieties of digital sources of data, and the ranges of different contexts covering those data are therefore a challenge in the modelling community. In this paper, we analyze the use of the core i* language for supporting modeling of context-dependent business environments where the contexts' data is provided by digital actors. We have defined the mappings from the main concepts for the domain of the investigation (such as digital sources, context and capability) to the elements of the i* 2.0. We illustrated our proposal by applying it on the service concerning roads maintenance.
Digitizing business services is becoming a fundamental necessity. In many domains, there are opportunities to derive better decisions by collecting and analyzing data from diverse digital sources, such as web sites, mobile devices, social media and IoT, such as in healthcare for accurate diagnosis, or for weather forecasting, maintenance of industrial tools, energy consumption, transport, etc.
Traditionally, the Requirements Engineering (RE) discipline has been
stakeholderdriven, i.e. existing methods for elicitation of the requirements for embedded or
information systems rely on business organizations and individual stakeholders as the
main sources of information [
In this context, a challenge concerns lack of the methods and tools for supporting
reasoning about system requirements in a way that would enable domain experts and
developers to mutually understand and communicate these requirements for
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improvements of existing software solutions or for development of new ones. One
commonly discussed approach proposes to elicit motivations behind business models
using organizational goals [
In this position paper, we concisely analyze the use of the i* goal modeling technique as a tool to support modeling and visualization of situational business environments encompassing constellations of pervading physical and digital actors, with the aim of elicitation of high-level system requirements capturing the data resources provided by these actors, as well as the desired functionality related to these data. Owing to i*’s ability for modeling the dependency links between different entities, we have found the technique as also applicable for discovering new digital actors (sources) in situations when goals and needed data resources are explicated.
The rest of the paper is organized as follows. Section 2 outlines a brief background to data and context-driven requirements engineering. Section 3 presents the theoretical proposal and illustrates it on the case concerning roads maintenance. A discussion and concluding remarks are given in section 4. 2
Data and Context-driven Requirements Engineering
Today’s organizations operate in dynamically changing situational environments
(contexts). Having a continuous access to relevant, accurate and usable data is
therefore highly important for organizations, but in turn, it leads also to the
requirements to improve their information systems to be able to benefit from new and
often changed and updated data [
Goal-oriented approaches for analyzing contexts related to system development are
well elaborated in [
A Requirements Analysis Framework using i* In this section, we describe a lightweight i* framework for analyzing context-driven requirements were the contexts’ data is obtained from digital sources.
As for the notion, for the purpose of this study, we consider i* 2.0 and its main elements: Actor, Intentional elements and Dependency as the main archetypes. Actors are autonomous entities aiming at achieving their goals in collaboration with other actors; they could be further refined to roles (actors with domain behaviors) or agents (actors with concrete physical manifestations). Goals, qualities, tasks and resources are the intentional elements used for modeling the things wanted by actors. Dependencies represent social relationships between actors in the way that one actor depends on another actor for something that can be a resource, a task, a goal or a quality. The i* language distinguishes two types of model views: Strategic Dependency (SD) model showing the actors and the dependencies between them, and Strategic Relational (SR) Model presenting a detailed view of the intentions of involved actors.
The scope of this paper is to analyze how i* be used for modelling context-based business environments in the presence of digital devices that provide resources to fulfill the context-based goals. Thereby, we consider a business environment where a User obtains the services of a System (IS) to fulfill his/her context-related resource requirements or goals. The System that provides Services, has a set of context-based goals and obtains data (resource) required to fulfill such goals from different types of Digital Sources. As such the analysis would concern the possible mappings between the concepts in the domain as described above and the i* 2.0 elements.
As a brief presentation of the framework usage, the figure below illustrates how User (role) is for the fulfillment of his/her goal “Traffic info provided”, dependent through an online Service (agent) for obtaining “Traffic related data” (resource) from digital sources (actor, which can be refined further to a concrete source, i.e. agent). In Table 1 below, we summarize the mappings from the concepts in the domain of our concern to the i* 2.0 modelling language.
organization types in the need for some contextual data resources.
An automated service realizing the requirements for the resources through its goals and capabilities.
A mobile device, a website, or IoT that fulfills the goals related to a particular context of the Service agent by its data resource(s).
Information provided by a digital source.
Dependency from Digital source (Agent) to Service (Agent)
agent.
A state (condition) of a business pertinent to User, further referring/associated to goals of Service.
A function of Service utilizing data resources, to be developed and implemented.
To illustrate the guidelines for use of the proposed framework, we consider the case of road maintenance under different weather circumstances (contexts) such as snowy, icy and frosty road conditions, road damages, traffic disturbances, etc. Step 1: Identify people and organizations having needs for the service Driver is dependent on Road Service for a usable road conditions, such as “Snow is cleared”, “Road is not slippery” (goals), as well as for the information regarding traffic disturbances such as road construction details, traffic signal failures, objects disturbing flow of traffic on roads (resource); this is summarized in Fig. 2 below. Step2: Identify contexts for which Service capabilities are required.
Following [
Context Traffic disturbance Icy conditions Snowy conditions Description Depending on different types of traffic disturbances such as road constructions, traffic signal failures, objects on road disturbing the flow of traffic, service agent should be capable of delivering the required capabilities (tasks in Fig. 2)).
Depending on the different temperature levels at the road surface, the service agent should have the ability to carry out the capabilities required to eliminate slippery conditions on roads (Fig. 2) Based on weather forecasts the service agent should be in a position to give precise details to maintain road network free of snow (Fig. 2).
Step3: Based on the required capabilities of the service agent, determine digital sources needed to deliver such capabilities.
Requirements for data resources of the identified capabilities (tasks) are analyzed to determine the desired data resources and further the digital sources able to provide these resources. Here the modeler should consider the required capabilities to link them to the available devices, or introduce new sources by considering the resource requirements. Additionally, the modeler can compose several digital sources to get aggregated information. In table below and in Fig.2, we summarize the analysis of the data resource dependencies of the Service agent (i.e. its tasks/capabilities).
Resource Construction details – construction related work details are often published to inform the disturbances to the normal traffic flow Traffic light failure info – traffic light failure information is published to inform the drivers about failures of automatic traffic management in road networks Weather data, Weather forecast, Road condition and Temperature – Weather data is required to forecast different weather conditions.
The surface level temperature at road networks is useful to determine icy conditions on roads Object data – objects on the road disturbing flow of traffic
Digital Source Handheld construction details reporter source Traffic light with the ability of detecting any possible alterations to its proper functioning and reporting that to the Service agent Composite Traffic camera or Weather and temperature sensor and Weather data analyzer – The traffic cameras can aggregate the functionalities of capturing weather information around road networks. Specialized weather and temperature sensors be used similarly.
Weather data analyzer having the is used to forecast snowy conditions.
Composite Traffic camera
A brief discussion of the presented results, conclusions, and the plans for further work are presented in the next section. 4
Discussion, Conclusions and Future Work In this paper we have analyzed how the i* modeling language can be used to simply and holistically model context-dependent business environments where the contexts’ data required for business capabilities is provided by digital actors. We have defined the mappings from the main concepts for the domain of the investigation (such as digital sources, context, capability) to the elements of the i* 2.0. Further, we have by means of step-wised guidelines illustrated the use of the proposal on the case of the road maintenance.
The motivation behind this study lies in the fact that the success of today’s
organizations highly rely to their ability for gathering different data from their
surroundings, and where the requirements for data accuracy, amount and the pace of
processing are constantly increasing. The i* modeling language provides the ability to
in a single view describe and integrate the relevant domain concepts for enabling
further development of information systems (services) capable to support different
business contexts. An important consideration in this domain of study refers to
system’s behavior at run-time. Using the i* technique, it is possible to define relevant
business contexts, needed data sources and capabilities, however, additional design is
needed to support switching of system’s capabilities for different contexts that are
changing over time. This challenge is for example explored by the CDD
methodology [
For the near future work, we plan to investigate the integration of the emphasized strengths of the i* technique in the domain of system’s requirements analysis with the needed information for system’s run-time management for context adjustments.