Summarising data as text helps people make sense of it. It also improves data discovery, as search algorithms can match this text against keyword queries. In this paper, we explore the characteristics of text summaries of data in order to understand how meaningful summaries look like. We present two complementary studies: a data-search diary study with 69 students, which offers insight into the information needs of people searching for data; and a summarisation study, with a lab and a crowdsourcing component with overall 80 data-literate participants, who produced summaries for 25 datasets. In each study we carried out a qualitative analysis to identify key themes and commonly mentioned dataset attributes, which people consider when searching and making sense of data. The results helped us design a template to create more meaningful textual representations of data, alongside guidelines for improving data-search experience overall.

Collaborative work with data is increasingly common and spans a broad range of activities - from creating or analysing data in a team, to sharing it with others, to reusing someone else's data in a new context. In this paper, we explore collaboration practices around structured data and how they are supported by current technology. We present the results of an interview study with twenty data practitioners, from which we derive four high-level user needs for tool support. We compare them against the capabilities of twenty systems that are commonly associated with data activities, including data publishing software, wikis, web-based collaboration tools, and online community platforms. Our findings suggest that data-centric collaborative work would benefit from: structured documentation of data and its lifecycle; advanced affordances for conversations among collaborators; better change control; and custom data access. The findings help us formalise practices around data teamwork, and build a better understanding how people's motivations and barriers when working with structured data.

Structured data such as databases, spreadsheets and web tables is becoming critical in every domain and professional role. Yet we still do not know much about how people interact with it. Our research focuses on the information seeking behaviour of people looking for new sources of structured data online, including the task context in which the data will be used, data search, and the identification of relevant datasets from a set of possible candidates. We present a mixed-methods study covering in-depth interviews with 20 participants with various professional backgrounds, supported by the analysis of search logs of a large data portal. Based on this study, we propose a framework for human structured-data interaction and discuss challenges people encounter when trying to find and assess data that helps their daily work. We provide design recommendations for data publishers and developers of online data platforms such as data catalogs and marketplaces. These recommendations highlight important questions for HCI research to improve how people engage and make use of this incredibly useful online resource.

Document engineering has been transformed by the development and adoption of XML as a common form (a 'meta-language') for defining document representations of many types. Recently XSLT has matured significantly as a transformational technology for XML-based documents that could have similar effect in the design of document processing tools. XSLT brings technologies from functional programming to bear on producing robust programs firmly embedded in the context of XML. We have new ideas and emphases on solution design, from very localised techniques, tricks and algorithms right up to large-scale program suites. XSLT's functional programming basis, its ability to mix push- and pull-driven effects, lack of reassignable state and definition within XML, all present challenges and opportunities to those both learning and exploiting its powers.Many of the attendees at DocEng'06 will have some experience of using XSLT in their research and practice. In this working session we aim to share interesting and useful insights and exploitations of XSLT, through an extended panel session and 'audience participation'. The session leaders (John Lumley, Jeni Tennison) have extensive experience of using XSLT within document engineering. The session starts with subjects suggested by the presenters and continues with a variety of topics raised by attendees.

We live in a world where documents do not simply exist in the form we need them. Getting from stored form to final presentation is often a complex process. Documents have to be generated, validated and transformed, queried, split, merged, filtered, annotated, restructured, translated and rendered. We need it to be easy to define the set of processes that the document has to go through. And we need it to be fast, at run time, to do this processing.The XML Processing Model Working Group is developing a markup language for defining pipelines of processes that XML documents may go through. In this talk I shall describe how pipelines can be put together using the XProc language and why even simple processing can benefit from being organised in that way.