Library Resources: Procurement, Innovation and Exploitation in a Digital World

The possibilities of the digital future require new models for procurement, innovation and exploitation. Emma Crowley and Chris Spencer describe the skills staff need to deliver resources in hybrid and digital environments. The chapter demonstrates the innovative ways that librarians use to procure and exploit the wealth of resources available in a digital world. They also describe the technological developments that can be adopted to improve workflow processes and they highlight the challenges faced on this fascinating journey

You can't always sketch what you want: Understanding Sensemaking in Visual Query Systems

Visual query systems (VQSs) empower users to interactively search for line charts with desired visual patterns, typically specified using intuitive sketch-based interfaces. Despite decades of past work on VQSs, these efforts have not translated to adoption in practice, possibly because VQSs are largely evaluated in unrealistic lab-based settings. To remedy this gap in adoption, we collaborated with experts from three diverse domains---astronomy, genetics, and material science---via a year-long user-centered design process to develop a VQS that supports their workflow and analytical needs, and evaluate how VQSs can be used in practice. Our study results reveal that ad-hoc sketch-only querying is not as commonly used as prior work suggests, since analysts are often unable to precisely express their patterns of interest. In addition, we characterize three essential sensemaking processes supported by our enhanced VQS. We discover that participants employ all three processes, but in different proportions, depending on the analytical needs in each domain. Our findings suggest that all three sensemaking processes must be integrated in order to make future VQSs useful for a wide range of analytical inquiries.Comment: Accepted for presentation at IEEE VAST 2019, to be held October 20-25 in Vancouver, Canada. Paper will also be published in a special issue of IEEE Transactions on Visualization and Computer Graphics (TVCG) IEEE VIS (InfoVis/VAST/SciVis) 2019 ACM 2012 CCS - Human-centered computing, Visualization, Visualization design and evaluation method

Relation Discovery from Web Data for Competency Management

This paper describes a technique for automatically discovering associations between people and expertise from an analysis of very large data sources (including web pages, blogs and emails), using a family of algorithms that perform accurate named-entity recognition, assign different weights to terms according to an analysis of document structure, and access distances between terms in a document. My contribution is to add a social networking approach called BuddyFinder which relies on associations within a large enterprise-wide "buddy list" to help delimit the search space and also to provide a form of 'social triangulation' whereby the system can discover documents from your colleagues that contain pertinent information about you. This work has been influential in the information retrieval community generally, as it is the basis of a landmark system that achieved overall first place in every category in the Enterprise Search Track of TREC2006

Searching Data: A Review of Observational Data Retrieval Practices in Selected Disciplines

A cross-disciplinary examination of the user behaviours involved in seeking and evaluating data is surprisingly absent from the research data discussion. This review explores the data retrieval literature to identify commonalities in how users search for and evaluate observational research data. Two analytical frameworks rooted in information retrieval and science technology studies are used to identify key similarities in practices as a first step toward developing a model describing data retrieval

Using Google Analytics Data to Expand Discovery and Use of Digital Archival Content

This article presents opportunities for the use of Google Analytics, a popular and freely available web analytics tool, to inform decision making for digital archivists managing online digital archives content. Emphasis is placed on the analysis of Google Analytics data to increase the visibility and discoverability of content. The article describes the use of Google Analytics to support fruitful digital outreach programs, to guide metadata creation for enhancing access, and to measure user demand to aid selection for digitization. Valuable reports, features, and tools in Google Analytics are identified and the use of these tools to gather meaningful data is explained

Language Preference in a Bi-language Digital Library

This paper examines user choice of interface language in a bi-language digital library(English and Maori, the language of the indigenous people of New Zealand)/ the majority of collection documents are in Maori, and the interface is available in both Maori and English. Log analysis shows three categories of preference for interface language: primarily English, primarily Maori and bilingual(switching back and forth between the two)

Report of the Stanford Linked Data Workshop

The Stanford University Libraries and Academic Information Resources (SULAIR) with the Council on Library and Information Resources (CLIR) conducted at week-long workshop on the prospects for a large scale, multi-national, multi-institutional prototype of a Linked Data environment for discovery of and navigation among the rapidly, chaotically expanding array of academic information resources. As preparation for the workshop, CLIR sponsored a survey by Jerry Persons, Chief Information Architect emeritus of SULAIR that was published originally for workshop participants as background to the workshop and is now publicly available. The original intention of the workshop was to devise a plan for such a prototype. However, such was the diversity of knowledge, experience, and views of the potential of Linked Data approaches that the workshop participants turned to two more fundamental goals: building common understanding and enthusiasm on the one hand and identifying opportunities and challenges to be confronted in the preparation of the intended prototype and its operation on the other. In pursuit of those objectives, the workshop participants produced:1. a value statement addressing the question of why a Linked Data approach is worth prototyping;2. a manifesto for Linked Libraries (and Museums and Archives and …);3. an outline of the phases in a life cycle of Linked Data approaches;4. a prioritized list of known issues in generating, harvesting & using Linked Data;5. a workflow with notes for converting library bibliographic records and other academic metadata to URIs;6. examples of potential “killer apps” using Linked Data: and7. a list of next steps and potential projects.This report includes a summary of the workshop agenda, a chart showing the use of Linked Data in cultural heritage venues, and short biographies and statements from each of the participants

Automated user modeling for personalized digital libraries

Digital libraries (DL) have become one of the most typical ways of accessing any kind of digitalized information. Due to this key role, users welcome any improvements on the services they receive from digital libraries. One trend used to improve digital services is through personalization. Up to now, the most common approach for personalization in digital libraries has been user-driven. Nevertheless, the design of efficient personalized services has to be done, at least in part, in an automatic way. In this context, machine learning techniques automate the process of constructing user models. This paper proposes a new approach to construct digital libraries that satisfy user’s necessity for information: Adaptive Digital Libraries, libraries that automatically learn user preferences and goals and personalize their interaction using this information

What makes re-finding information difficult? A study of email re-finding

Re-nding information that has been seen or accessed before is a task which can be relatively straight-forward, but often it can be extremely challenging, time-consuming and frustrating. Little is known, however, about what makes one re-finding task harder or easier than another. We performed a user study to learn about the contextual factors that influence users' perception of task diculty in the context of re-finding email messages. 21 participants were issued re-nding tasks to perform on their own personal collections. The participants' responses to questions about the tasks combined with demographic data and collection statistics for the experimental population provide a rich basis to investigate the variables that can influence the perception of diculty. A logistic regression model was developed to examine the relationships be- tween variables and determine whether any factors were associated with perceived task diculty. The model reveals strong relationships between diculty and the time lapsed since a message was read, remembering when the sought-after email was sent, remembering other recipients of the email, the experience of the user and the user's ling strategy. We discuss what these findings mean for the design of re-nding interfaces and future re-finding research