Dati: a feasibility study to validate Dati as an inferencing tool capable of analysing a User’s static and dynamic near-to-me data ambiently to generate personalised and contextualised User Experiences when mobile.

Dati项目旨在利用个人产生的越来越多的个人数据来深入了解用户的需求和行为——并以此为个人用户和他们的服务提供商带来独特的好处。有了Dati，我们的目标是对现有的“找到我附近”应用程序进行逐步改进，这些应用程序不是完全个性化的，也不能适应用户需求和行为的变化。我们的可行性研究旨在确定用户需求和行为的具体要素，这些要素对于提供令人信服的客户主张至关重要。该研究的输出将是Dati的完整设计规范和工作样机。用户推送：在用户允许的情况下，Dati将安全地收集、整理和管理用户的个人、行为和上下文数据。这些数据可能包括“静态”信息，例如他们对旅行、娱乐、食物或健康选择的既定偏好。数据还可能包括用户的“动态”信息，这些信息可能从智能设备（包括用户的智能手机和可穿戴设备）、开放数据筒仓、社交媒体资料和活动、过去的消费数据、与搜索相关的互动或用户的明确评级输入Dati平台。用户提供的数据可以创建用户档案（个人“品牌”身份）。用户拉动：通过用户提供的高度情境化的信息，Dati能够扫描数千种服务和产品（餐馆、休闲、商店、交通等），并向用户提供最匹配的特定情境选项——所有这些都无需输入任何搜索信息。建议的选项将知道用户的地理位置，并可能根据其他维度提供信息，例如一天中的时间、环境和天气条件、社交和专业网络的接近程度、用户的健康状况、情绪和其他属性，这些都代表了用户在任何给定时间和地点的兴趣。建议的选项很可能包括为用户节省价格和时间的好处。Dati技术：作为一项新颖的技术，Dati将通过独特的（可保护的、可利用的）语义和链接数据层提供这种转型的用户体验。为了快速构建和部署Dati服务发现和推荐后端，Dati将使用“COMPOSE”（www.compose-project.eu），这是一种高度可扩展、云就绪和开源的大数据和链接服务技术。为了有效处理从互联网设备（如信标、传感器、智能手机和可穿戴设备）推送的多种个人和行为数据流，Dati将使用强大的“COMPOSE”物联网数据流功能。作为面向客户的演示前端，Dati将改进“Best4Me”移动应用技术，这是一个独特的个性化社交feed聚合渠道，具有基于主题的过滤功能。

Dati project aims to use the increasing amount of personal data generated by individuals to gain insights into user needs and behaviours - and in doing so deliver unique benefits back to individual users and their service providers. With Dati we aim to deliver a step-change improvement on existing ‘find-near-me’ applications, which are not fully personalised or able to adjust to changes in user needs and behaviours. Our feasibility study seeks to identify specific elements of user needs and behaviours that are essential in delivering a compelling customer proposition. The output of the study will be the complete design specification and working prototype of Dati. User Push: With user permission, Dati will collect, collate and manage securely a user’s personal, behavioural and contextual data. Such data may include ‘static’ information – such as their stated preferences about travel, pleasure, food or health-driven choices. Data may also include the user’s ‘dynamic’ information, which may feed into the Dati platform from smart devices – including user’s smartphone and wearables – open data silos, social media profiles and activities, past consumption data, search-related interactions or the user’s explicit ratings. Data provided by the user enables the creation of a user profile (a personal ‘brand’ identity). User Pull: With the highly contextualised information provided by the user, Dati is able to scan perhaps thousands of service and product offerings (restaurants, leisure, shops, transport, etc) and deliver back to the user best-match context-specific options - all done without the need to enter any search information. The suggested options will know the geolocation of a user, and may be informed by additional dimensions, such as the time of the day, environmental and weather conditions, proximity of social and professional networks, user’s health, mood, and other attributes which, collectively, represent the user’s interest at any given time and place. The suggested options may well include price and time-savings benefits to users. Dati Technology: As a new and novel technology, Dati will deliver this transformational user experience via a unique (and protectable, exploitable) semantic and linked data layer. Dati will use ‘COMPOSE’ (www.compose-project.eu), a highly scalable, cloud-ready and open-source big data and linked-service technology in order quickly to build and deploy the Dati service discovery and recommendation back-end. To cope efficiently with multiple streams of personal and behavioural data pushed from Internet enabled devices – such as, beacons, sensors, smartphones and wearables – Dati will use the powerful ‘COMPOSE’ Internet of Things data streaming functionality. As the customer-facing presentation front-end, Dati will improve the ‘Best4Me’ mobile application technology, a unique and personalised social feeds aggregation channel with topic-based filtering features.