Gov 2.0: Towards a User Generated State?

New elements associated withWeb 2.0 relating to interactivity and end-user focus have combined with the availability of newlevels of information to encourage the development of what may be termed a Gov 2.0 approach.This, in combination with recent initiatives in the modernising government programme, has emphasised new levels of public participation and engagement with government as well as a re-engineering of public services tomake them more responsive to their end users. Adopting a governmentality perspective, it is argued that this involves a wider process of governing through constructing and reconstructing ideas of the public, community and individual citizen-consumers who take on a role in their own governance. It is argued that this fundamental re-working of the nature of what is public represents a constitutional change that is perhaps more signi¢cant than the constitutional reform programme directed to formal government which attracts more attention

The European Commission’s public consultation on the review of EU copyright rules: a response by the CREATe centre

This article presents the response of the Centre for Copyright and New Business Models in the Creative Economy (CREATe) to the consultation on reform of the EU copyright regime. Reviews the format of the consultation, notes the common problems in reporting data in such a format, and reproduces the consultation questions to which CREATe responded, together with a summary of its conclusions on topics including: (1) terms of copyright protection; (2) libraries and archives; (3) persons with disabilities; (4) remuneration of authors; (5) user-generated content; (6) respect for rights; and (7) data mining.

Web Data Extraction from Query Result Pages Based on Visual and Content Features

A rapidly increasing number of Web databases are now become accessible via
their HTML form-based query interfaces. Query result pages are dynamically generated
in response to user queries, which encode structured data and are displayed for human
use. Query result pages usually contain other types of information in addition to query
results, e.g., advertisements, navigation bar etc. The problem of extracting structured data
from query result pages is critical for web data integration applications, such as comparison
shopping, meta-search engines etc, and has been intensively studied. A number of approaches
have been proposed. As the structures of Web pages become more and more complex, the
existing approaches start to fail, and most of them do not remove irrelevant contents which
may a®ect the accuracy of data record extraction. We propose an automated approach for
Web data extraction. First, it makes use of visual features and query terms to identify data
sections and extracts data records in these sections. We also represent several content and
visual features of visual blocks in a data section, and use them to ¯lter out noisy blocks.
Second, it measures similarity between data items in di®erent data records based on their
visual and content features, and aligns them into di®erent groups so that the data in the
same group have the same semantics. The results of our experiments with a large set of
Web query result pages in di®erent domains show that our proposed approaches are highly
e®ective.

Learning about probability from text and tables: Do color coding and labeling through an interactive-user interface help?

Learning from visual representations is enhanced when learners appropriately integrate corresponding visual and verbal information. This study examined the effects of two methods of promoting integration, color coding and labeling, on learning about probabilistic reasoning from a table and text. Undergraduate students (N = 98) were randomly assigned to learn about probabilistic reasoning from one of 4 computer-based lessons generated from a 2 (color coding/no color coding) by 2 (labeling/no labeling) between-subjects design. Learners added the labels or color coding at their own pace by clicking buttons in a computer-based lesson. Participants' eye movements were recorded while viewing the lesson. Labeling was beneficial for learning, but color coding was not. In addition, labeling, but not color coding, increased attention to important information in the table and time with the lesson. Both labeling and color coding increased looks between the text and corresponding information in the table. The findings provide support for the multimedia principle, and they suggest that providing labeling enhances learning about probabilistic reasoning from text and tables