Collaborative classification of growing collections with evolving facets

There is a lack of tools for exploring large non-textual collections. One challenge is the manual effort required to add metadata to these collections. In this paper, we propose an architecture that enables users to collaboratively build a faceted classification for a large, growing collection. Besides a novel wiki-like classification interface, the proposed architecture includes automated document classification and facet schema enrichment techniques. We have implemented a prototype for the American Political History multimedia collection from usa.gov. Categories and Subject Descriptor

Crowd-Sourcing Fuzzy and Faceted Classification for Concept Search

Searching for concepts in science and technology is often a difficult task. To facilitate concept search, different types of human-generated metadata have been created to define the content of scientific and technical disclosures. Classification schemes such as the International Patent Classification (IPC) and MEDLINE's MeSH are structured and controlled, but require trained experts and central management to restrict ambiguity (Mork, 2013). While unstructured tags of folksonomies can be processed to produce a degree of structure (Kalendar, 2010; Karampinas, 2012; Sarasua, 2012; Bragg, 2013) the freedom enjoyed by the crowd typically results in less precision (Stock 2007). Existing classification schemes suffer from inflexibility and ambiguity. Since humans understand language, inference, implication, abstraction and hence concepts better than computers, we propose to harness the collective wisdom of the crowd. To do so, we propose a novel classification scheme that is sufficiently intuitive for the crowd to use, yet powerful enough to facilitate search by analogy, and flexible enough to deal with ambiguity. The system will enhance existing classification information. Linking up with the semantic web and computer intelligence, a Citizen Science effort (Good, 2013) would support innovation by improving the quality of granted patents, reducing duplicitous research, and stimulating problem-oriented solution design. A prototype of our design is in preparation. A crowd-sourced fuzzy and faceted classification scheme will allow for better concept search and improved access to prior art in science and technology

User Experiments of a Social, Faceted Multimedia Classification System

Internet document sharing systems such as Flickr store billions of user-contributed images. Many collections on the Web contain large numbers of multimedia objects such as images. While such systems are designed to encourage user contributions and sharing, they are not well-organized collections on any given subject and are not easy to browse for specific subject matters. We have built a system that systematically organizes a large multimedia collection into an evolving faceted classification. This paper discusses the evaluation of such a system through a number of usage studies in a university setting

Growing a Tree in the Forest: Constructing Folksonomies by Integrating Structured Metadata

Many social Web sites allow users to annotate the content with descriptive metadata, such as tags, and more recently to organize content hierarchically. These types of structured metadata provide valuable evidence for learning how a community organizes knowledge. For instance, we can aggregate many personal hierarchies into a common taxonomy, also known as a folksonomy, that will aid users in visualizing and browsing social content, and also to help them in organizing their own content. However, learning from social metadata presents several challenges, since it is sparse, shallow, ambiguous, noisy, and inconsistent. We describe an approach to folksonomy learning based on relational clustering, which exploits structured metadata contained in personal hierarchies. Our approach clusters similar hierarchies using their structure and tag statistics, then incrementally weaves them into a deeper, bushier tree. We study folksonomy learning using social metadata extracted from the photo-sharing site Flickr, and demonstrate that the proposed approach addresses the challenges. Moreover, comparing to previous work, the approach produces larger, more accurate folksonomies, and in addition, scales better.Comment: 10 pages, To appear in the Proceedings of ACM SIGKDD Conference on Knowledge Discovery and Data Mining(KDD) 201

Shifting to Data Savvy: The Future of Data Science In Libraries

The Data Science in Libraries Project is funded by the Institute for Museum and Library Services (IMLS) and led by Matt Burton and Liz Lyon, School of Computing & Information, University of Pittsburgh; Chris Erdmann, North Carolina State University; and Bonnie Tijerina, Data & Society. The project explores the challenges associated with implementing data science within diverse library environments by examining two specific perspectives framed as ‘the skills gap,’ i.e. where librarians are perceived to lack the technical skills to be effective in a data-rich research environment; and ‘the management gap,’ i.e. the ability of library managers to understand and value the benefits of in-house data science skills and to provide organizational and managerial support. This report primarily presents a synthesis of the discussions, findings, and reflections from an international, two-day workshop held in May 2017 in Pittsburgh, where community members participated in a program with speakers, group discussions, and activities to drill down into the challenges of successfully implementing data science in libraries. Participants came from funding organizations, academic and public libraries, nonprofits, and commercial organizations with most of the discussions focusing on academic libraries and library schools

CHORUS Deliverable 2.2: Second report - identification of multi-disciplinary key issues for gap analysis toward EU multimedia search engines roadmap

After addressing the state-of-the-art during the first year of Chorus and establishing the existing landscape in multimedia search engines, we have identified and analyzed gaps within European research effort during our second year. In this period we focused on three directions, notably technological issues, user-centred issues and use-cases and socio- economic and legal aspects. These were assessed by two central studies: firstly, a concerted vision of functional breakdown of generic multimedia search engine, and secondly, a representative use-cases descriptions with the related discussion on requirement for technological challenges. Both studies have been carried out in cooperation and consultation with the community at large through EC concertation meetings (multimedia search engines cluster), several meetings with our Think-Tank, presentations in international conferences, and surveys addressed to EU projects coordinators as well as National initiatives coordinators. Based on the obtained feedback we identified two types of gaps, namely core technological gaps that involve research challenges, and “enablers”, which are not necessarily technical research challenges, but have impact on innovation progress. New socio-economic trends are presented as well as emerging legal challenges

Design Tools

This book aims at encompassing the panorama of design tools being developed, tested and adopted by researchers and professors at the Department of Design of Politecnico di Milano. The tools are organized in a taxonomy that reflects the path of choice of a possible user in need for the right tool for a task to be performed. The taxonomy is based on a formalization of the design process proposed by the authors, which characterizes the Design System at Politecnico di Milano. The book essentially offers two main contributions: an original taxonomy that guides towards the organization of design tools and their usage with different actors; a representative collection of design tools developed within the Department of Design of Politecnico di Milano with specific instructions on how to use them. Design Tools is addressed both to practitioners and academics in the field of design that are interested in getting to know more about the discourse around design tools in general and in particular how this discourse takes a shape within Politecnico di Milano and resolves in usable and shareable tools

Flexibility Relative to What? Change to Research Infrastructure

It is often said that, in the face of an ever-changing world, infrastructure must remain flexible. Yet, what is meant by change remains glib and, consequently, so too do our studies on flexibility. In this paper, we develop three sensitizing concepts to investigate change to research infrastructure: 1) technoscientific: changes in research objects, scientific methods, and instruments; 2) sociotechnical: changes in social organization, coordination and, collaboration tools; and data sharing techniques; and 3) institutional: changes in funding and regulatory regimes. The majority of studies of “information infrastructure” have focused on the sociotechnical facet, and so we offer the two additional facets of change to help sensitize researchers to empirical instances of these encountered in the field, and to broaden the research agenda. To elaborate these concepts, we focus on a long-term research infrastructure that has been investigating HIV disease for nearly thirty years: The Multicenter AIDS Cohort Study (MACS). Over time, the MACS has faced tremendous changes in its science, collaboration and communication tools, its data and specimen repositories, its institutional environment, and the disease itself. Before we can begin to characterize flexibility, we must understand the nature of change research infrastructures face. We conclude by outlining a research agenda that will match forms of flexibility to the heterogeneity of changes an infrastructure may encounter