Dieser Beitrag untersucht, in welchem Umfang Dokumente von Dokumentenservern wissenschaftlicher Institutionen in den allgemeinen Suchmaschinen Google und Yahoo nachgewiesen sind und inwieweit wissenschaftliche Suchmaschinen für die Suche nach solchen Dokumenten besser geeignet sind. Dazu werden die fünf Suchmaschinen BASE, Google Scholar, OAIster, Scientific Commons und Scirus überblickartig beschrieben und miteinander verglichen. Hauptaugenmerk wird dabei auf die unterschiedlichen Inhalte, Suchfunktionen und Ausgabemöglichkeiten gelegt, mit Hilfe eines Retrievaltests wird speziell die Leistungsfähigkeit der Suchmaschinen beim Auffinden von Dokumenten, deren Volltexte im Sinne des Open Access direkt und ohne Beschränkungen aufrufbar sind, untersucht.

Scientists depend on literature search to find prior work that is relevant to their research ideas. We introduce a retrieval model for literature search that incorporates a wide variety of factors important to researchers, and learns the weights of each of these factors by observing citation patterns. We introduce features like topical similarity and author behavioral patterns, and combine these with features from related work like citation count and recency of publication. We present an iterative process for learning weights for these features that alternates between retrieving articles with the current retrieval model, and updating model weights by training a supervised classifier on these articles. We propose a new task for evaluating the resulting retrieval models, where the retrieval system takes only an abstract as its input and must produce as output the list of references at the end of the abstract's article. We evaluate our model on a collection of journal, conference and workshop articles from the ACL Anthology Reference Corpus. Our model achieves a mean average precision of 28.7, a 12.8 point improvement over a term similarity baseline, and a significant improvement both over models using only features from related work and over models without our iterative learning.

Interpreting scholarly contributions solely on the basis of the number, and not nature, of citations is inherently flawed because contradictory as well as confirmatory findings feed into the same metric, capturing popularity at the expense of precision. I propose a citation and indexing procedure that would conveniently integrate information about research trends while imposing minimal burden on the producers and consumers of research. Under the proposed system, citations appearing in the reference list of research reports would be superscripted with letters corresponding to one of the following six categories: references to findings that are Consistent with the current findings, are Replicated by the current findings, are Inconsistent with the current findings, Failed to be replicated by the current findings, were used to build Theory, or were used to cite Methodologies. I explain how the resulting CRIF-TM data could be summarized and perpetually updated by an online indexing service. I provide an example to demonstrate how these superscripts could be conveniently and unobtrusively presented in the reference list of forthcoming articles. Finally, I examine the anticipated benefits, limitations, and implementation challenges of the proposed citation and indexing procedure.

The Internet has been covered by legal deposit legislation in France since 2006, making web archiving one of the missions of the Bibliothèque nationale de France (BnF). Access to the web archives has been provided in the library on an experimental basis since 2008. In the context of increasing interest in many countries in web archiving and how it may best serve the needs of researchers, especially in the expanding field of Internet studies for social sciences, a qualitative study was performed, based on interviews with potential users of the web archives held at the BnF, and particularly researchers working in various areas related to the Internet. The study aimed to explore their needs in terms of both content and services, and also to analyse different ways of representing the archives, in order to identify ways of increasing their use. While the interest of maintaining the "memory" of the web is obvious to the researchers, they are faced with the difficulty of defining, in what is a seemingly limitless space, meaningful collections of documents. Cultural heritage institutions such as national libraries are perceived as trusted third parties capable of creating rationally-constructed and well-documented collections, but such archives raise certain ethical and methodological questions.

The VIVO project is creating an open, Semantic Web-based network of institutional ontology-driven databases to enable national discovery, networking, and collaboration via information sharing about researchers and their activities. The project has been funded by NIH to implement VIVO at the University of Florida, Cornell University, and Indiana University Bloomington together with four other partner institutions. Working with the Semantic Web/Linked Open Data community, the project will pilot the development of common ontologies, integration with institutional information sources and authentication, and national discovery and exploration of networks of researchers. Building on technology developed over the last five years at Cornell University, VIVO supports the flexible description and interrelation of people, organizations, activities, projects, publications, affiliations, and other entities and properties. VIVO itself is an open source Java application built on W3C Semantic Web standards, including RDF, OWL, and SPARQL. To create researcher profiles, VIVO draws on authoritative information from institutional databases, external data sources such as PubMed, and information provided directly by researchers themselves. While the NIH-funded project focuses on biomedical research, the current Cornell implementation of VIVO supports the full range of disciplines across the university, from music to mechanical engineering to management. There are many ways a person?s expertise may be discovered, through grants, presentations, courses and news releases, as well as through research statements or publications listed on their profile--resulting in the creation of implicit groups or networks of people based on a number of pre-identified, shared characteristics. In addition to formal authoritative information and relationships, VIVO can also support the creation of personal work groups and associated properties to represent the informal relationships evolving around collaboration.

Keywords in the ACM Digital Library and IEEE Xplore digital library and in NSF grants anticipate future CS research.

We describe the design and performance of WebBase, a tool for Web research. The system includes a highly customizable crawler, a repository for collected Web pages, an indexer for both text and link-related page features, and a high-speed content distribution facility. The distribution module enables researchers world-wide to retrieve pages from WebBase, and stream them across the Internet at high speed. The advantage for the researchers is that they need not all crawl the Web before beginning their research. WebBase has been used by scores of research and teaching organizations world-wide, mostly for investigations into Web topology and linguistic content analysis. After describing the system's architecture, we explain our engineering decisions for each of the WebBase components, and present respective performance measurements.

To purchase or authenticate to the full-text of this article, please visit this link: http://onlinelibrary.wiley.com/doi/10.1002/trtr.1548/abstract Byline: Emily Rodgers Keywords: Sight words; word recognition < Decoding; Instructional strategies; teaching strategies < Strategies, methods, and materials; 2-Childhood Abstract For many teachers, the term scaffolding has come to mean providing just the right amount of help when a student encounters difficulty. However, there is another facet of scaffolding that has been largely ignored, and that is making decisions about what to focus on to help the student. In this article, new research findings are shared about both types of scaffolding and the role they play in helping beginning readers solve new words while reading connected text. Suggestions are provided for how teachers can use these findings to more effectively scaffold young students' word solving attempts as they read a new book with teacher help.

"Research in Information Systems helps supervisors and their students get the most out of the PhD experience. It can be used as a basis of courses for supervisors and their research students."--BOOK JACKET.

We approach the problem of academic literature search by considering an unpublished manuscript as a query to a search system. We use the text of previous literature as well as the citation graph that connects it to find relevant related material. We evaluate our technique with manual and automatic evaluation methods, and find an order of magnitude improvement in mean average precision as compared to a text similarity baseline.

<par>The web has greatly improved access to scientific literature. However, scientific articles on the web are largely disorganized, with research articles being spread across archive sites, institution sites, journal sites, and researcher homepages. No index covers all of the available literature, and the major web search engines typically do not index the content of Postscript/PDF documents at all. This paper discusses the creation of digital libraries of scientific literature on the web, including the efficient location of articles, full-text indexing of the articles, autonomous citation indexing, information extraction, display of query-sensitive summaries and citation context, hubs and authorities computation, similar document detection, user profiling, distributed error correction, graph analysis, and detection of overlapping documents. The software for the system is available at no cost for non-commercial use.</par>

The Handbook of Research Methods on Trust provides an authoritative in-depth consideration of quantitative and qualitative methods for empirical study of trust in the social sciences. As this topic has matured, a growing number of practical approaches and techniques have been utilised across the broad, multidisciplinary community of trust research, providing both insights and challenges. This unique Handbook draws together a wealth of research methods knowledge gained by trust researchers into one essential volume. The contributors examine different methodological issues and particular methods.

Classical papers are of great help for beginners to get familiar with a new research area. However, digging them out is a difficult problem. This paper proposes Claper, a novel academic recommendation system based on two proven principles: the Principle of Download Persistence and the Principle of Citation Approaching (we prove them based on real-world datasets). The principle of download persistence indicates that classical papers have few decreasing download frequencies since they were published. The principle of citation approaching indicates that a paper which cites a classical paper is likely to cite citations of that classical paper. Our experimental results based on large-scale real-world datasets illustrate Claper can effectively recommend classical papers of high quality to beginners and thus help them enter their research areas.

Automatic recommendation of citations for a manuscript is highly valuable for scholarly activities since it can substantially improve the efficiency and quality of literature search. The prior techniques placed a considerable burden on users, who were required to provide a representative bibliography or to mark passages where citations are needed. In this paper we present a system that considerably reduces this burden: a user simply inputs a query manuscript (<i>without</i> a bibliography) and our system automatically finds locations where citations are needed. We show that na&#239;ve approaches do not work well due to massive noise in the document corpus. We produce a successful approach by carefully examining the relevance between segments in a query manuscript and the representative segments extracted from a document corpus. An extensive empirical evaluation using the CiteSeerX data set shows that our approach is effective.

Scientists spend an increasing amount of time building and using software. However, most scientists are never taught how to do this efficiently. As a result, many are unaware of tools and practices that would allow them to write more reliable and maintainable code with less effort. We describe a set of best practices for scientific software development that have solid foundations in research and experience, and that improve scientists' productivity and the reliability of their software.

Scientists spend an increasing amount of time building and using software. However, most scientists are never taught how to do this efficiently. As a result, many are unaware of tools and practices that would allow them to write more reliable and maintainable code with less effort. We describe a set of best practices for scientific software development that have solid foundations in research and experience, and that improve scientists' productivity and the reliability of their software.