# From Ethnographic Research to Big Data Analytics--A Case of Maritime Energy-Efficiency Optimization
## 3 An Ethnographic Study on Ferry Vessels
A tool may be functionally powerful but if it does not address the true needs or failed to be integrated into the work practice, it will be risking becoming an ornamental bauble. During the voyage, the ETA-pilot basically only presented two easily readable information sources that the navigators could instantly monitor without much cognitive effort: the consumption rate and total fuel consumption. But according to the navigators, such information can hardly be used for real-time self-evaluation and navigational decision support in an eco-driving manner, which was explicitly mentioned multiple times during the interviews as their \"wish-list\". The tool did not really provide the users a learning space for knowledge and awareness improvement. Several navigators commented that if the ETA-pilot could see some sort of fuel consumption prediction they might be able to be more proactive instead of being reactive in navigation choices. In addition, there could be many traffic situations in which the master mariner felt it was necessary to increase the maneuverability by increasing the speed, which could lead to more fuel consumption. Under these circumstances, they did not really mind the consequence of burning more fuel. To them safety always overrides EE goal. There appeared to be no incentives or information feedback to allow them to make more deliberate efforts to save fuel within their safety boundaries. All these technical configurations and dynamic situations revealed parts of their context of use. The use of the ETA-pilot was opportunistic at best. From the design and use of the tool's perspective, a prominent issue began to surface: the operational choice for navigational strategies have a considerable impact on fuel consumption [8; 13], but there is an absence of efficient monitoring in a real voyage environment because the navigators did not get sufficient analytical support from the existing EE monitoring tool. This gap was not bound to the ship side. According to the supplier of the ETA-pilot system, the recorded real-time data on fuel consumption and weather condition were transferred to the shore-side for possible further analysis and hopefully EE optimization suggestions could be delivered back to the ship. However, the crew members expressed that they never received such feedback from the supplier except the overarching requirement to save fuel or taking the training course of the ETA-pilot on how to undertake eco-driving with its \"decision support functionalities\". Once the vessel had reached her destination, that was the end of the role for this technology. Both the real-time decision support system and evaluating activities were missing. This phenomenon was also noted by [PERSON] who was involved in the ethnographic studies on the same vessels too, concluding that this was a problem of \"underdevelopment of evaluating activities\" or \"inadequate knowledge\" [12]. One of the authors of this paper also had a chance to interview the designer of the ETA-pilot. The designer explained that that there was no universal optimal use of this decision support tool but this depended upon the navigator's own experience and interpretation, as there are many factors that the current algorithm of the tool cannot universally account for, e.g., different routes, different efficiency from different propellers, different potentials to save fuel on different ships; the tool was not developed in a way that it can dynamically \"learn\" from the historical data and provide real-time decision support for eco-driving (although it does have some predictive capability such as adjusting speed based on depth of the water and manually input weather information etc.). The designer admitted that such needs may be considered in its future development.