Enhancing an Incremental Clustering Algorithm for Web Page Collections

With the size and state of the Internet today, a good quality approach to organizing this mass of information is of great importance. Clustering web pages into groups of similar documents is one approach, but relies heavily on good feature extraction and document representation as well as a good clustering approach and algorithm. Due to the changing nature of the Internet, resulting in a dynamic dataset, an incremental approach is preferred. In this work we propose an enhanced incremental clustering approach to develop a better clustering algorithm that can help to better organize the information available on the Internet in an incremental fashion. Experiments show that the enhanced algorithm outperforms the original histogram based algorithm by up to 7.5%.

A story worth telling : putting oral history and digital collections online in cultural institutions

Digital platforms in cultural institutions offer exciting opportunities for oral history and digital storytelling that can augment and enrich traditional collections. The way in which cultural institutions allow access to the public is changing dramatically, prompting substantial expansions of their oral history and digital story holdings. In Queensland, Australia, public libraries and museums are becoming innovative hubs of a wide assortment of collections that represent a cross-section of community groups and organisations through the integration of oral history and digital storytelling. The State Library of Queensland (SLQ) features digital stories online to encourage users to explore what the institution has in the catalogue through their website. Now SLQ also offers oral history interviews online, to introduce users to oral history and other components of their collections,- such as photographs and documents to current, as well as new users. This includes the various departments, Indigenous centres and regional libraries affiliated with SLQ statewide, who are often unable to access the materials held within, or even full information about, the collections available within the institution. There has been a growing demand for resources and services that help to satisfy community enthusiasm and promote engagement. Demand increases as public access to affordable digital media technologies increases, and as community or marginalised groups become interested in do it yourself (DIY) history; and SLQ encourages this. This paper draws on the oral history and digital story-based research undertaken by the Queensland University of Technology (QUT) for the State Library of Queensland including: the Apology Collection: The Prime Minister’s apology to Australia’s Indigenous Stolen Generation; Five Senses: regional Queensland artists; Gay history of Brisbane; and The Queensland Business Leaders Hall of Fame.

Managing process model collections with AProMoRe

As organizations reach higher levels of Business Process Management maturity, they tend to collect numerous business process models. Such models may be linked with each other or mutually overlap, supersede one another and evolve over time. Moreover, they may be represented at different abstraction levels depending on the target audience and modeling purpose, and may be available in multiple languages (e.g. due to company mergers). Thus, it is common that organizations struggle with keeping track of their process models. This demonstration introduces AProMoRe (Advanced Process Model Repository) which aims to facilitate the management of (large) process model collections.

QUT Digital Repository: Integrating the University’s IR with other digital collections

Queensland University of Technology’s Institutional Repository, QUT ePrints (http://eprints.qut.edu.au/), was established in 2003. With the help of an institutional mandate (endorsed in 2004) the repository now holds over 11,000 open access publications. The repository’s success is celebrated within the University and acknowledged nationally and internationally. QUT ePrints was built on GNU EPrints open source repository software (currently running v.3.1.3) and was originally configured to accommodate open access versions of the traditional range of research publications (journal articles, conference papers, books, book chapters and working papers). However, in 2009, the repository’s scope, content and systems were broadened and the ‘QUT Digital repository’ is now a service encompassing a range of digital collections, services and systems. For a work to be accepted in to the institutional repository, at least one of the authors/creators must have a current affiliation with QUT. However, the success of QUT ePrints in terms of its capacity to increase the visibility and accessibility of our researchers' scholarly works resulted in requests to accept digital collections of works which were out of scope. To address this need, a number of parallel digital collections have been developed. These collections include, OZcase, a collection of legal research materials and ‘The Sugar Industry Collection’; a digitsed collection of books and articles on sugar cane production and processing. Additionally, the Library has responded to requests from academics for a service to support the publication of new, and existing, peer reviewed open access journals. A project is currently underway to help a group of senior QUT academics publish a new international peer reviewed journal. The QUT Digital Repository website will be a portal for access to a range of resources to support copyright management. It is likely that it will provide an access point for the institution’s data repository. The data repository, provisionally named the ‘QUT Data Commons’, is currently a work-in-progress. The metadata for some QUT datasets will also be harvested by and discoverable via ‘Research Data Australia’, the dataset discovery service managed by the Australian National Data Service (ANDS). QUT Digital repository will integrate a range of technologies and services related to scholarly communication. This paper will discuss the development of the QUT Digital Repository, its strategic functions, the stakeholders involved and lessons learned.

Discovering characteristics of stochastic collections of process models

Process models in organizational collections are typically modeled by the same team and using the same conventions. As such, these models share many characteristic features like size range, type and frequency of errors. In most cases merely small samples of these collections are available due to e.g. the sensitive information they contain. Because of their sizes, these samples may not provide an accurate representation of the characteristics of the originating collection. This paper deals with the problem of constructing collections of process models, in the form of Petri nets, from small samples of a collection for accurate estimations of the characteristics of this collection. Given a small sample of process models drawn from a real-life collection, we mine a set of generation parameters that we use to generate arbitrary-large collections that feature the same characteristics of the original collection. In this way we can estimate the characteristics of the original collection on the generated collections.We extensively evaluate the quality of our technique on various sample datasets drawn from both research and industry.

Managing large collections of business process models - Current techniques and challenges

Nowadays, business process management is an important approach for managing organizations from an operational perspective. As a consequence, it is common to see organizations develop collections of hundreds or even thousands of business process models. Such large collections of process models bring new challenges and provide new opportunities, as the knowledge that they encapsulate requires to be properly managed. Therefore, a variety of techniques for managing large collections of business process models is being developed. The goal of this paper is to provide an overview of the management techniques that currently exist, as well as the open research challenges that they pose.

Alternative primary sources for studying Australian television history : an annotated list of online private collections

It is possible to write many different histories of Australian television, and these different histories draw on different primary sources. The ABC of Drama, for example, draws on the ABC Document Archives (Jacka 1991). Most of the information for Images and Industry: television drama production in Australia is taken from original interviews with television production staff (Moran 1985). Ending the Affair, as well as archival work, draws on ‘over ten years of watching … Australian television current affairs’ (Turner 2005, xiii). Moran’s Guide to Australian TV Series draws exhaustively on extant archives: the ABC Document Archives, material sourced through the ABC Drama department, the Australian Film Commission, the library of the Australian Film, Television and Radio School, and the Australian Film Institute (Moran 1993, xi)...

User participation in the categorisation of the State Library of Queensland digital image collections: characteristics, motivations and experiences

In 2010, the State Library of Queensland (SLQ) donated their out-of-copyright Queensland images to Wikimedia Commons. One direct effect of publishing the collections at Wikimedia Commons is the ability of general audiences to participate and help the library in processing the images in the collection. This paper will discuss a project that explored user participation in the categorisation of the State Library of Queensland digital image collections. The outcomes of this project can be used to gain a better understanding of user participation that lead to improving access to library digital collections. Two techniques for data collection were used: documents analysis and interview. Document analysis was performed on the Wikimedia Commons monthly reports. Meanwhile, interview was used as the main data collection technique in this research. The data collected from document analysis was used to help the researchers to devise appropriate questions for interviews. The interviews were undertaken with participants who were divided into two groups: SLQ staff members and Wikimedians (users who participate in Wikimedia). The two sets of data collected from participants were analysed independently and compared. This method was useful for the researchers to understand the differences between the experiences of categorisation from both the librarians’ and the users’ perspectives. This paper will provide a discussion on the preliminary findings that have emerged from each group participant. This research provides preliminary information about the extent of user participation in the categorisation of SLQ collections in Wikimedia Commons that can be used by SLQ and other interested libraries in describing their digital content by their categorisations to improve user access to the collection in the future.

An English-translated parallel corpus for the CJK Wikipedia collections

In this paper, we describe a machine-translated parallel English corpus for the NTCIR Chinese, Japanese and Korean (CJK) Wikipedia collections. This document collection is named CJK2E Wikipedia XML corpus. The corpus could be used by the information retrieval research community and knowledge sharing in Wikipedia in many ways; for example, this corpus could be used for experimentations in cross-lingual information retrieval, cross-lingual link discovery, or omni-lingual information retrieval research. Furthermore, the translated CJK articles could be used to further expand the current coverage of the English Wikipedia.

Collaborating to develop research data management services and collections

The Queensland University of Technology (QUT) Library, like many other academic and research institution libraries in Australia, has been collaborating with a range of academic and service provider partners to develop a range of research data management services and collections. Three main strategies are being employed and an overview of process, infrastructure, usage and benefits is provided of each of these service aspects. The development of processes and infrastructure to facilitate the strategic identification and management of QUT developed datasets has been a major focus. A number of Australian National Data Service (ANDS) sponsored projects - including Seeding the Commons; Metadata Hub / Store; Data Capture and Gold Standard Record Exemplars have / will provide QUT with a data registry system, linkages to storage, processes for identifying and describing datasets, and a degree of academic awareness. QUT supports open access and has established a culture for making its research outputs available via the QUT ePrints institutional repository. Incorporating open access research datasets into the library collections is an equally important aspect of facilitating the adoption of data-centric eresearch methods. Some datasets are available commercially, and the library has collaborated with QUT researchers, in the QUT Business School especially strongly, to identify and procure a rapidly growing range of financial datasets to support research. The library undertakes licensing and uses the Library Resource Allocation to pay for the subscriptions. It is a new area of collection development for with much to be learned. The final strategy discussed is the library acting as “data broker”. QUT Library has been working with researchers to identify these datasets and undertake the licensing, payment and access as a centrally supported service on behalf of researchers.

Stratospheric dust collections : valuable resources for space and atmospheric scientists

Collections of solid particles from the Earths' stratosphere have been a significant part of atmospheric research programs since 1965 [1], but it has only been in the past decade that space-related disciplines have provided the impetus for a continued interest in these collections. Early research on specific particle types collected from the stratosphere established that interplanetary dust particles (IDP's) can be collected efficiently and in reasonable abundance using flat-plate collectors [2-4]. The tenacity of Brownlee and co-workers in this subfield of cosmochemistry has led to the establishment of a successful IDP collection and analysis program (using flat-plate collectors on high-flying aircraft) based on samples available for distribution from Johnson Space Center [5]. Other stratospheric collections are made, but the program at JSC offers a unique opportunity to study well-documented, individual particles (or groups of particles) from a wide variety of sources [6]. The nature of the collection and curation process, as well as the timeliness of some sampling periods [7], ensures that all data obtained from stratospheric particles is a valuable resource for scientists from a wide range of disciplines. A few examples of the uses of these stratospheric dust collections are outlined below.

Consolidation of business process model collections

This thesis presents novel techniques for addressing the problems of continuous change and inconsistencies in large process model collections. The developed techniques treat process models as a collection of fragments and facilitate version control, standardization and automated process model discovery using fragment-based concepts. Experimental results show that the presented techniques are beneficial in consolidating large process model collections, specifically when there is a high degree of redundancy.