Journalists\u27 Views of the Environment: Issues and Challenges

In advocating the use of an environmental handbook for journalists, the authors report on a survey of reporters and editors regarding salient environmental issues in different regions of the United States and e emphasis placed on environmental reporting in newsrooms

Metadata and ontologies for organizing students’ memories and learning: standards and convergence models for context awareness

Este artículo trata de las ontologías que sirven para la comprensión en contexto y la Gestión de la Información Personal (PIM)y su aplicabilidad al proyecto Memex Metadata(M2). M2 es un proyecto de investigación de la Universidad de Carolina del Norte en Chapel Hill para mejorar la memoria digital de los alumnos utilizando tablet PC, la tecnología SenseCam de Microsoft y otras tecnologías móviles(p.ej. un dispositivo de GPS) para capturar el contexto del aprendizaje. Este artículo presenta el proyecto M2, dicute el concepto de los portafolios digitales en las actuales tendencias educativas, relacionándolos con las tecnologías emergentes, revisa las ontologías relevantes y su relación con el proyecto CAF (Context Awareness Framework), y concluye identificando las líneas de investigación futuras.This paper focuses on ontologies supporting context awareness and Personal Information Management (PIM) and their applicability in Memex Metadata (M2) project. M2 is a research project of the University of North Carolina at Chapel Hill to improve student digital memories using the tablet PC, Microsoft’s SenseCam technology, and other mobile technologies (e.g., a GPS device) to capture context. The M2 project offers new opportunities studying students’ learning with digital technologies. This paper introduces the M2 project; discusses E-portfolios and current educational trends related to pervasive computing; reviews relevant ontologies and their relationship to the projects’ CAF (context awareness framework), and concludes by identifying future research directions

Metadata Capital via a linked data HIVE

This paper explores medatada capital via linked open metadata vocabularies, specifically via the HIVE (Helping Interdisciplinary Vocabulary Engineering) initiative in the U.S. DataNet Federation Consortium (DFC). Formulas representing 'Capital-sigma notation' and 'Succesive growth rates' are introduced as potential means for quanitifying metadata capital. A conclusion summarizes this paper and identitifies next steps

The Landscape of Rights and Licensing Initiatives for Data Sharing

Over the last twenty years, a wide variety of resources have been developed to address the rights and licensing problems inherent with contemporary data sharing practices. The landscape of developments is this area is increasingly confusing and difficult to navigate, due to the complexity of intellectual property and ethics issues associated with sharing sensitive data. This paper seeks to address this challenge, examining the landscape and presenting a Version 1.0 directory of resources. A multi-method study was pursued, with an environmental scan examining 20 resources, resulting in three high-level categories: standards, tools, and community initiatives; and a content analysis revealing the subcategories of rights, licensing, metadata & ontologies. A timeline confirms a shift in licensing standardization priorities from open data to more nuanced and technologically robust solutions, over time, to accommodate for more sensitive data types. This paper reports on the research undertaking, and comments on the potential for using license-specific metadata supplements and developing data-centric rights and licensing ontologies

Representing Aboutness: Automatically Indexing 19th- Century Encyclopedia Britannica Entries

Representing aboutness is a challenge for humanities documents, given the linguistic indeterminacy of the text. The challenge is even greater when applying automatic indexing to historical documents for a multidisciplinary collection, such as encyclopedias. The research presented in this paper explores this challenge with an automatic indexing comparative study examining topic relevance. The setting is the NEH-funded 19th-Century Knowledge Project, where researchers in the Digital Scholarship Center, Temple University, and the Metadata Research Center, Drexel University, are investigating the best way to index entries across four historical editions of the Encyclopedia Britannica (3rd, 7th, 9th, and 11th editions). Individual encyclopedia entry entries were processed using the Helping Interdisciplinary Vocabulary Engineering (HIVE) system, a linked-data, automatic indexing terminology application that uses controlled vocabularies. Comparative topic relevance evaluation was performed for three separate keyword extraction algorithms: RAKE, Maui, and Kea++. Results show that RAKE performed the best, with an average of 67% precision for RAKE, and 28% precision for both Maui and Kea++. Additionally, the highest-ranked HIVE results with both RAKE and Kea++ demonstrated relevance across all sample entries, while Maui’s highest-ranked results returned zero relevant terms. This paper reports on background information, research objectives and methods, results, and future research prospects for further optimization of RAKE’s algorithm parameters to accommodate for encyclopedia entries of different lengths, and evaluating the indexing impact of correcting the historical Long S

Modeling Ephraim Chambers' Knowledge Structure from a Naïve Standpoint

In the preface to his Cyclopaedia published in 1728 Ephraim Chambers offers readers a systematized structure of his attempt to produce a universal repository of human knowledge. Divided into an interconnected taxonomic tree and domain vocabulary, this structure forms the basis of one effort from the Metadata Research Center to study historical ontologies. The knowledge structure is being encoded into a Simple Knowledge Organization System (SKOS) form as well as a Web Ontology Language (OWL) version. This paper explores the expressive and functional differences between these SKOS and OWL versions of Chambers’ knowledge structure. As part of this goal, the paper research focused on the construction and application of rules in each system to produce a more computationally ready representation of Chambers’ structure in SKOS, which is more thesaurus-like, and OWL, which represents additional ontological nuances. First, studying the various textual aspects at the semantic, syntactic, and typographic levels allowed for the relationships between terms to manifest from which rules governing expression of the connections between elements developed. Second, because each language, SKOS and OWL, functionally expresses different logical relationships, their possibilities and limitations offer a ground for further analyzing the resultant knowledge structures; although, each stemmed from the same basic source of Chambers’ text. Lastly this paper will examine rule making and expression in light of Paul Grice’s theory of conversational implicature to understand how a naïve agent formulates and applies these rules to a knowledge structure

Introduction: Toward a More Library-Like Web via Semantic Knitting

The Editors would like to acknowledge all of the authors for their contributions to this volume. The Editors would also like to thank Sandy Roe, Teri Devoe, and the CCQ’s Editorial Board for their support of this special volume. The Editors would also like to thank the Fulbright Program for support that allowed Eva Méndez to work as EU Research Scholar at the SILS Metadata Research Center, University of North Carolina at Chapel Hill, over the last year to complete this book

The DRIADE Project: Phased Application Profile Development in Support of Open Science

DRIADE (Digital Repository of Information and Data for Evolution) is a project being developed for the acquisition, preservation, sharing and re-use of heterogeneous data in support of published research in the field of evolutionary biology. Metadata is a fundamental part of DRIADE’s information architecture. This paper reports on DRIADE’s overarching goals. We describe our phased approach to developing an application profile, which supports three phases of DRIADE's development. We present a multi-method approach to developing the application profile. Our methods included a requirements assessment, content analysis, and crosswalk analysis. The paper concludes by identifying next steps and discussing the applicability of DRIADE’s work to other initiatives seeking to tightly couple published research and data