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Gives the highlights of the 2004 annual conference of the American Library Association (ALA) held in Orlando, Florida, in June 2004. These included differing viewpoints on publishing and licencing scholarly work and technology trends.

The purpose of this paper is to explore the task design and assignment of full-text generation on mass Chinese historical archives (CHAs) by crowdsourcing, with special attention paid to how to best divide full-text generation tasks into smaller ones assigned to crowdsourced volunteers and to improve the digitization of mass CHAs and the data-oriented processing of the digital humanities.

This paper starts from the complexities of character recognition of mass CHAs, takes Sheng Xuanhuai archives crowdsourcing project of Shanghai Library as a case study, and makes use of the theories of archival science, including diplomatics of Chinese archival documents, and the historical approach of Chinese archival traditions as the theoretical basis and analysis methods. The results are generated through the comprehensive research.

This paper points out that volunteer tasks of full-text generation include transcription, punctuation, proofreading, metadata description, segmentation, and attribute annotation in digital humanities and provides a metadata element set for volunteers to use in creating or revising metadata descriptions and also provides an attribute tag set. The two sets can be used across the humanities to construct overall observations about texts and the archives of which they are a part. Along these lines, this paper presents significant insights for application in outlining the principles, methods, activities, and procedures of crowdsourced full-text generation for mass CHAs.

This study is the first to explore and identify the effective design and allocation of tasks for crowdsourced volunteers completing full-text generation on CHAs in digital humanities.

The experience of a multi‐site higher education library consortium in purchasing electronic journals and databases is described. The criteria and guidelines developed to assist in the decision‐making process for the purchase of multidisciplinary electronic products and services can be of value to other libraries whether in a single or consortial environment. Factors such as database features, coverage, search features, and delivery options were considered.

The following describes a number of technologies and exemplary service designs that foster better Internet finding tools in libraries and more cooperative and efficient effort in Internet resource collection building. Our library and partner institutions have been involved in this work for over a decade. The open source software and projects discussed represent appropriate technologies and sustainable strategies that will help Internet portals, digital libraries, virtual libraries and library catalogs‐with‐portal‐like‐capabilities (IPDVLCs) to scale better and to anticipate and meet the needs of scholarly and educational users.

This study aims to develop a hierarchical topic analysis tool (HTAT) based on hierarchical Latent Dirichelet allocation (hLDA) to support digital humanities research that is associated with the need of topic exploration on the Digital Humanities Platform for Mr. Lo Chia-Lun’s Writings (DHP-LCLW). HTAT can assist humanities scholars on distant reading with analysis of hierarchical text topics, through classifying time-stamped texts into multiple historical eras, conducting hierarchical topic modeling (HTM) according to the texts from different eras and presenting through visualization. The comparative network diagram is another function provided to assist humanities scholars in comparing the difference in the topics they wish to explore and to track how the concept of a topic changes over time from a particular perspective. In addition, HTAT can also provide humanities scholars with the feature to view source texts, thus having high potential to be applied in promoting the effectiveness of topic exploration due to simultaneously integrating both the topic exploration functions of distant reading and close reading.

This study adopts a counterbalanced experimental design to examine whether there is significant differences in the effectiveness of topic inquiry, the number of relevant topics inquired and the time spent on them when research participants were alternately conducting text exploration using DHP-LCLW with HTAT or DHP-LCLW with Single-layer Topic Analysis Tool (SLTAT). A technology acceptance questionnaire and semi-structured interviews were also conducted to understand the research participants' perception and feelings toward using the two different tools to assist topic inquiry.

The experimental results show that DHP-LCLW with HTAT could better assist the research participants, in comparison with DHP-LCLW with SLTAT, to grasp the topic context of the texts from two particular perspectives assigned by this study within a short period. In addition, the results of the interviews revealed that DHP-LCLW with HTAT, in comparison with SLTAT, was able to provide a topic terms that better met research participnats' expectations and needs, and effectively guided them to the corresponding texts for close reading. In the analysis of technology acceptance and interview data, it can be found that the research participants have a high and positive tendency toward using DHP-LCLW with HTAT to assist topic inquiry.

The Jieba Chinese word segmentation system was used in the Mr. Lo Chia-Lun’s Writings Database in this study, to perform word segmentation on Mr. Lo Chia-Lun’s writing texts for topic modeling based on hLDA. Since Jieba word segmentation system is a lexicon based word segmentation system, it cannot identify new words that have still not been collected in the lexicon well. In this case, the correctness of word segmentation on the target texts will affect the results of hLDA topic modeling, and the effectiveness of HTAT in assisting humanities scholars for topic inquiry.

An HTAT was developed to support digital humanities research in this study. With HTAT, DHP-LCLW provides hmanities scholars with topic clues from different hierarchical perspectives for textual exploration, and with temporal and comparative network diagrams to assist humanities scholars in tracking the evolution of the topics of specific perspectives over time, to gain a more comprehensive understanding of the overall context of the texts.

In recent years, topic analysis technology that can automatically extract key topic information from a large amount of texts has been developed rapidly, but the topics generated from traditional topic analysis models like LDA (Latent Dirichelet allocation) make it difficult for users to understand the differences in the topics of texts with different hierarchical levels. Thus, this study proposes HTAT which uses hLDA to build a hierarchical topic tree with a tree-like structure without the need to define the number of topics in advance, enabling humanities scholars to quickly grasp the concept of textual topics and use different hierarchical perspectives for further textual exploration. At the same time, it also provides a combination function of temporal division and comparative network diagram to assist humanities scholars in exploring topics and their changes in different eras, which helps them discover more useful research clues or findings.

This paper argues that the realisation of the electronic hypermedia of the future depends on integrating the technology of free text retrieval with the classification‐based discipline of content analysis