You are provided with the abstract of a scientific paper and the abstracts of the papers it references. Your task is to write a Related Work section for the main paper. This section should concisely summarize and integrate the key points from the cited abstracts, reflecting how they relate to the main paper's contributions and context. In your summary, use numerical citation markers like [1], [2], etc., to refer to the corresponding papers.

Main Abstract:
Curated web archive collections contain focused digital content which is collected by archiving organizations, groups, and individuals to provide a representative sample covering specific topics and events to preserve them for future exploration and analysis. In this paper, we discuss how to best support collaborative construction and exploration of these collections through the ArchiveWeb system. ArchiveWeb has been developed using an iterative evaluation-driven design-based research approach, with considerable user feedback at all stages. The first part of this paper describes the important insights we gained from our initial requirements engineering phase during the first year of the project and the main functionalities of the current ArchiveWeb system for searching, constructing, exploring, and discussing web archive collections. The second part summarizes the feedback we received on this version from archiving organizations and libraries, as well as our corresponding plans for improving and extending the system for the next release.

Cited Abstract(s):
[1]: The World Wide Web is becoming a source of information for researchers, who are more aware of the possibilities for collections of Internet content as resources. Some have begun creating archives of web content for social science and humanities research. However, there is a growing gulf between policies shared between global and national institutions creating web archives and the practices of researchers making use of the archives. Each set of stakeholders finds the others’ web archiving contributions less applicable to their own field. Institutions find the contributions of researchers to be too narrow to meet the needs of the institution’s audience, and researchers find the contributions of institutions to be too broad to meet the needs of their research methods. Resources are extended to advance both institutional and researcher tools, but the gulf between the two is persistent. Institutions generally produce web archives that are broad in scope but with limited access and enrichment tools. The design of common access interfaces, such as the Internet Archive’s Wayback Machine, limit access points to archives to only URL and date. This narrow access limits the ways in which web archives can be valuable for exploring research questions in the humanities and social sciences. Individual scholars, in catering to their own disciplinary and methodological needs, produce web archives that are narrow in scope, and whose access and enrichment tools are personalized to work within the boundaries of the project for which the web archive was built. There is no way to explore a subset of an archive by topic, event, or idea. The current search paradigm in web archiving access tools is built primarily on retrieval, not discovery. We suggest that there is a need for extensible tools to enhance access to and enrichment of web archives to make them more readily reusable and so, more valuable for both institutions and researchers, and that annotation activities can serve as one potential guide for development of such tools to bridge the divide.

[2]: Organizations like the Internet Archive have been capturing Web contents over decades, building up huge repositories of time-versioned pages. The timestamp annotations and the sheer volume of multi-modal content constitutes a gold mine for analysts of all sorts, across different application areas, from political analysts and marketing agencies to academic researchers and product developers. In contrast to traditional data analytics on click logs, the focus is on longitudinal studies over very long horizons. This longitudinal aspect affects and concerns all data and metadata, from the content itself, to the indices and the statistical metadata maintained for it. Moreover, advanced analysts prefer to deal with semantically rich entities like people, places, organizations, and ideally relationships such as company acquisitions, instead of, say, Web pages containing such references. For example, tracking and analyzing a politician’s public appearances over a decade is much harder than mining frequently used query words or frequently clicked URLs for the last month. The huge size of Web archives adds to the complexity of this daunting task. This paper discusses key challenges, that we intend to take up, which are posed by this kind of longitudinal analytics: time-travel indexing and querying, entity detection and tracking along the time axis, algorithms for advanced analyses and knowledge discovery, and scalability and platform issues.

[3]: The objective of the 1st Temporal Web Analytics Workshop (TWAW) is to provide a venue for researchers of all domains (IE IR, Web mining etc.) where the temporal dimension opens up an entirely new range of challenges and possibilities. The workshop's ambition is to help shaping a community of interest on the research challenges and possibilities resulting from the introduction of the time dimension in Web analysis. The maturity of the Web, the emergence of large scale repositories of Web material, makes this very timely and a growing sets of research and services (recorded future1, truthy2 launched just in the last months) are emerging that have this focus in common. Having a dedicated workshop will help, we believe, to take a rich and cross-domain approach to this new research challenge with a strong focus on the temporal dimension.
Information retrieval (IR) models and algorithms have been extremely successful during the last 20 years in providing everybody with easy access to the vast amount of information available on and through the web. Web and IR conferences connect a large number of researchers working on problems related to web search, the Social Web and data mining, and related topics. Surprisingly little work has been spent, however, on issues related to temporal retrieval, or exploration and analysis of large temporal collections like web archives [1] , even though the need for focusing research on these issues has been recognized [3] [2] .