Anthropocentric Data Systems

Arguably, it all started with Mike Dertouzos’ vision on the Information Marketplace [2]. Then, an explosion occurred. Social networks. Social computing. Social software. Groupware. Shareware. Open-source software. Personalized query answering and personalized information systems. Tagging. Folksonomies. Log and clickstream mining. Recommender systems. Crowdsourcing. Human-in-the loop and humancentered systems. Provably, these buzzwords have dominated the academic landscape within the data systems (and not only) community. There is a fundamental paradigm shift going on here. The old world, where the human was simply a passive user, has given way to a new world where humans contribute data, (storage, communication, and compute) resources, and software. Further, recently, humans take on tasks that actually alleviate and improve the jobs performed by machines and recent research from different domains have started looking into this realm where humans and computers share tasks, collaborating to achieve goals [4, 12, 11, 6, 1]! Example endeavors from big players like that of RedHat Linux and Mozilla (for open-source software) and IBM (for groupware and shareware), have shown how humans can be much more than simple, passive users: they can play an active, key role in the design and implementation of the system itself. The peer-to-peer R&D and related products showed how the ’system’s’ resources can be made-up from users’ actually collectively contributing their own resources. The next wave of web 2.0 and social networking and systems escalated user-contributed data collections and their sharing to unprecedented levels. Ditto for user networks, which became both data-resources to be discovered, and resources to be exploited for discovering other (meta)data of interest. Increasingly, users have been moving closer to the centre of the big picture! Further, lately companies like Innocentive (www.innocentive.com), Prosper (www.prosper.com), and Indifex (www.indifex.com) showed how crowdsourcing tasks requiring intelligence can lead to large value-added services. The Vision (in brief). For the last years we have been