The Web is one of the most important socio-technical systems
of our time, mirroring trivia and popular culture, propaganda and
politics, literature and high culture. Yet we have only very limited
capabilities for accessing and exploring the past of the Web, in stark "
contrast to what we could learn from it.
Within ALEXANDRIA, we want to provide at least some of the tools
enabling us to analyze the past, based on what is and what was available
on the Web. Our goal in ALEXANDRIA is to significantly advance semantic
and time-based indexing for Web archives using human-compiled knowledge
available on the Web, to efficiently index, retrieve and explore
information about entities and events from the past. We will further
investigate mixed crowd- and machine-based Web analytics to support
long-running and collaborative retrieval and analysis processes on Web
archives.
In this talk I will focus on our recent research on crowd-based aspects,
and specifically talk about how we can use human input for providing
information about events, as well as about how to better ask for human
help on crowdsourcing platforms.