CORDIS - Forschungsergebnisse der EU

HUMANE: a typology, method and roadmap for HUman-MAchine NEtworks

Periodic Reporting for period 2 - HUMANE (HUMANE: a typology, method and roadmap for HUman-MAchine NEtworks)

Berichtszeitraum: 2016-04-01 bis 2017-05-31

The overall objective of HUMANE is to improve public and private services by uncovering how new configurations of human-machine networks change patterns of interaction, behaviour, trust and sociability, and how public and private services need to fit the specific networks involved.

To this end, HUMANE has developed a typology, method and online tool to support human-centred design on a strategic level. The starting point of the typology development was an extensive review of the research literature on human-machine networks.

The typology and method have been applied and validated in eight case trials, within domains such as decision support, emergency management, online journalism, citizen science, and open innovation.

The HUMANE typology has also been applied as a basis to support future thinking on human-machine networks.
To establish a baseline for the work in HUMANE, a systematic review of literature was completed in the first phase of the HUMANE project. The analytical approach applied in the review, served as basis for developing the HUMANE typology. Key findings from the review is presented in a paper in ACM Computing Surveys.

The HUMANE typology is a framework for cross-domain characterization and analysis of human-machine networks. The typology is structured according to four analytical layers; each including two dimensions. To make the typology actionable for supporting human-centred design on a strategic level, a five step method compliant with the human-centred design process has been developed. Here, the human-machine network of interest is profiled according to the typology dimensions. Cross-domain transfer of design knowledge and experience is supported through a design pattern approach, where design considerations and solutions are sought from networks with similar profile characteristics. To support the application of the typology and method, and to present findings from the HUMANE cases, an online network profiling tool has been developed, available at

Eight case studies have been completed to explore different aspects of human-machine networks and to validate the HUMANE typology and method and provide input for its iterative development. The HUMANE case studies comprise a broad set of human-machine networks, including networks for open innovation, sharing economy, citizen science, decision support, and emergency management. This set of cases indicates the wide applicability of the typology and method.

An approach for simulation modelling of human-machine networks has been developed to allow for validation of design options for HMNs on the basis of simulations rather than building and testing prototypes. Such an approach has the potential for cost saving, and to enable validation for designs that would otherwise have been infeasible or difficult to test empirically. A Core HMN Model is proposed for describing networks that can be readily extended and used for simulation purposes of specific HMNs.

To support future thinking on human-machine networks, a process for roadmapping of human-machine networks has been developed. The process consist of a series of steps, identifying stakeholders and their goals, as well as actions and strategies leading towards these goal. The roadmapping process has been applied for three selected social domains as part of the HUMANE work on future thinking.

In the roadmapping work, stakeholder involvement has been conducted through an online survey targeting stakeholders in the domains of the sharing economy, eHealth, and citizen participation. Stakeholders in these domains have also been engaged through other activities such as interviews and focus groups.

Three social domains were selected for application of the HUMANE roadmapping process: The sharing economy, eHealth and citizen participation. The domains were chosen as these represent areas where emerging human-machine networks substantially impact the state of the practice. In the roadmaps, the HUMANE typology was applied as a framework for analysis.
The HUMANE method is developed to complement a process for Human-Centred Design (HCD), and is supported by an online tool for HMN profiling and transfer of design knowledge. In this tool, HMNs can be profiled according to the HUMANE typology dimensions, to review similar HMNs and to identify relevant design considerations associated with other HMNs.

The target audience for the HUMANE typology and method include practitioners within ICT development and design, as well as researchers within fields approaching the phenomenon of human-machine networks.

The work on the typology and method has been presented in four scientific conference papers, all included in Springer proceedings. Two at HCI International 2016, one at HCI International 2017, and one at the International Conference of Man-Machine Interaction 2017.

To validate the HUMANE typology and method, and to provide feedback to drive its development, eight case studies have been conducted across the two project iterations. In addition to serving this validation and feedback purpose, the cases have served to generate new knowledge of human-machine networks within and across the case domains. The case study work has also led to a number of scientific publications including papers published in Scientific Reports and PLoS ONE. A full overview of papers based on the case studies are listed on the HUMANE website (

This Core HMN Model has been positioned within the HUMANE methodology to help with the evaluation of HMN designs. The Core HMN Model has been applied to two HMNs as a proof of concept to demonstrate the approach, showing that it is applicable to different HMNs and has generated impact by informing the design decisions for an HMN that is under development.

We have modelled design options for an HMN called Truly Media (under development), to determine how to best help journalists collaboratively verify user-generated content to avoid running stories based on content that consists of hoaxes, rumours or deliberately misleading information (e.g. propaganda, fake news, and other untrue statements).

We have also successfully modelled edit wars in Wikipedia and how increasing the agency of bots may address this emergent behaviour wherein two agents mutually revert each other. The simulation model was able to predict the emergence of edit wars with a 91.5% accuracy on average (as high as 100% for some time periods).

Roadmaps for three social domains have been developed and promoted through HUMANE, for the domains of the sharing economy, eHealth, and citizen participation. All roadmap material is promoted and easily accessible at the HUMANE project website (

The roadmaps present material for future thinking (key challenges, trends, and goals), strategic goals as well as key actions and priorities for achieving these goals. The roadmaps is presented through different channels to best impact policy makers, domain professionals, ICT designers, and researchers.
HUMANE online profiling tool
HUMANE roadmapping process