Credibility perceptions of content contributors and consumers in social media

This panel addresses information credibility issues in the context of social media. During this panel, participants will discuss people's credibility perceptions of online content in social media from the perspectives of both content contributors and consumers. Each panelist will bring her own perspective on credibility issues in various social media, including Twitter (Morris), Wikipedia (Metzger; Francke), blogs (Rieh), and social Q&A (Jeon). This panel aims to flesh out multi‐disciplinary approaches to the investigation of credibility and discuss integrated conceptual frameworks and future research directions focusing on assessing and establishing credibility in social media.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/111174/1/meet14505101022.pd

System Function Adoption of an Open Source Digital Repository System: A Global View

This poster reports a project that examines the adoption of system functions of an open source digital repository, DSpace. It also identifies the factors which have influenced the functions\u27 adoption. The data were collected from DSpace user registry from September 2013 to March 2014. A total of 545 repositories in the registry contained system function customizations, representing 533 unique institutions from 95 countries. The preliminary findings indicate that 10 of the 32 available system functions are adopted by over 10% of its members; the majority of repositories are from academia; academic repositories also offer most system functions; and the U.S. and India each comprises over 10% of DSpace repositories that have DSpace system function customizations. Additionally, repositories from India utilize most system functions. About two-thirds of institutions are using DSpace as their institutional repositories and the two major (over 50%) content types are conference publications and technical reports

Searching as learning: Novel measures for information interaction research

There is growing recognition of the importance of learning as a search outcome and of the need to provide support for it. Yet, before we can consider learning as a part of search, we need to know how to assess it. This panel will focus on methods and measures for assessing learning in the context of search tasks and their outcomes. The panel will be interactive as the audience will be encouraged to engage in contributing their own experiences and ideas related to measures and methods to study learning as a part of search processes. Ideas and experiences with explicit and implicit indicators of learning and with evaluating learning outcomes will be shared during a dialogue between the audience and panelists. Outcomes from the panel discussions will contribute to formulating a research agenda for “search as learning.” The outcomes will be shared with the audience (and the wider ASIST community).Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/111136/1/meet14505101021.pd

Enriching Metadata for a University Repository by Modelling and Infrastructure: A New Vocabulary Server for Phaidra

Dieser Beitrag erörtert einen der ersten Schritte im Zusammenhang mit der „semantischen Anreicherung“ des Phaidra-Repositoriums der Universität Wien  Zunächst wird in einem technischen Report auf die in einem lokalen Kontext getroffene Auswahl hingewiesen, d.h. auf die Bereitstellung des Vocabularyservers iQvoc anstelle des zuvor verwendeten SKOSMOS, und erläutert die für die Implementierung erforderlichen Entscheidungen hinsichtlich des Designs des aktuellen Tools sowie zusätzliche Funktionen. Anschließend werden einige Modellierungsmerkmale des lokalen LOD-gesteuerten Vokabulars gemäß der SKOS-Dokumentation und den -Best Practices beschrieben, wobei aufgezeigt wird, welche Ansätze zur Bereitstellung eines LOD-KOS im Web verfolgt werden und welche Probleme dabei möglicherweise auftreten können.This paper illustrates an initial step towards the ‘semantic enrichment’ of University of Vienna’s Phaidra repository as one of the valuable and up-to-date strategies able to enhance its role and usage. Firstly, a technical report points out the choice made in a local context, i.e. the deployment of the vocabulary server iQvoc instead of the formerly used SKOSMOS, explaining design decisions behind the current tool and additional features that the implementation required. Afterwards, some modelling characteristics of the local LOD controlled vocabulary are described according to SKOS documentation and best practices, highlighting which approaches can be pursued for rendering a LOD KOS available in the Web as well as issues that can be possibly encountered

Assessment, Usability, and Sociocultural Impacts of DataONE

DataONE, funded from 2009-2019 by the U.S. National Science Foundation, is an early example of a large-scale project that built both a cyberinfrastructure and culture of data discovery, sharing, and reuse. DataONE used a Working Group model, where a diverse group of participants collaborated on targeted research and development activities to achieve broader project goals. This article summarizes the work carried out by two of DataONE’s working groups: Usability & Assessment (2009-2019) and Sociocultural Issues (2009-2014). The activities of these working groups provide a unique longitudinal look at how scientists, librarians, and other key stakeholders engaged in convergence research to identify and analyze practices around research data management through the development of boundary objects, an iterative assessment program, and reflection. Members of the working groups disseminated their findings widely in papers, presentations, and datasets, reaching international audiences through publications in 25 different journals and presentations to over 5,000 people at interdisciplinary venues. The working groups helped inform the DataONE cyberinfrastructure and influenced the evolving data management landscape. By studying working groups over time, the paper also presents lessons learned about the working group model for global large-scale projects that bring together participants from multiple disciplines and communities in convergence research

Untangling cost, effort, and load in information seeking and retrieval

When performing Information Seeking and Retrieval (ISR) activities, people submit queries, examine results, assess documents and engage with the information to make decisions and complete tasks. All these activities come at a “cost”, but within the field of ISR there is no universally accepted definition of the concepts of Cost, Effort, and Load (CEL). Instead, researchers have used the same terms interchangeably to describe similar but also different concepts. This lack of shared understanding has led to a disconnect between how these concepts are defined and discussed versus how they are interpreted and measured. Thus, the aim of this paper is two-fold: (i) to review the meaning of CEL related concepts used within ISR, and (ii) to create a shared taxonomy of the concepts relating to CEL in ISR. To seed our analysis, we conducted a literature review, where 397 papers were reviewed, and twenty-six papers that explicitly proposed measures or definitions of CEL were selected for analysis. By drawing upon theory from Psychology and other fields, we present the common definitions of CEL in order to ground our discussion of these concepts in ISR. We also highlight the issues associated with CEL measurement in ISR to help researchers reflect on the validity and precision of existing methods. We hope this perspectives paper serves as a basis for a taxonomy of how CEL concepts are used within ISR- where we have provided a series of working definitions that clearly delineate the different concepts being used, investigated and measured in ISR research

Data expertise and service development in geoscience data centers and academic libraries

eScience brings the promise of advancements in scientific knowledge as well as new demands on staff who need to manage large and complex data, design user services, and enable open access. One ramification is that research institutions are extending their services and staffing to address data management concerns. As more organizations extend their operations to research data, an understanding of how to develop and support research data expertise and services is needed. How can an organization build data expertise into their staff? This study examines how organizations develop their own data expertise and services, comparing approaches in geoscience data centers and academic libraries. Case studies of two exemplar sites are presented based on evidence from qualitative interviews and artifact collection. The case studies are extended and further informed through qualitative interviews conducted with personnel at other data centers and libraries. The study addresses how to cultivate research data expertise and staffing to support data management services. Key products include a set of expertise categories, data roles, and learning strategies. The results draw attention to the contributions that data professionals make to research projects and to ways research institutions can support data professionals and data work