Masao Takaku

サーチエンジン検索結果ページにおける視線情報の分析( 第17回(2009年度)年次大会(研究報告会&総会))

*1 物質・材料研究機構科学情報室 National Institute for Materials Science E-mail: TAKAKU.Masao@nims.go.jp 2 国立教育政策研究所教育研究情報センター National Institute for Educational Policy Research E-mail: yuka@nier.go.jp 3 東京電機大学情報環境学部情報環境学科 Tokyo Denki University E-mail: terai@sie.dendai.ac.jp 4 愛知教育大学教育学部 Aichi University of Education E-mail: hsaito@auecc.aichi-edu.ac.jp 5 放送大学 ICT活用・遠隔教育センター The Open University of Japan E-mail: miwamaki@code.u-air.ac.jp 6 国立情報学研究所情報社会相関研究系 /総合研究大学院大学 National Institute of Informatics / Graduate University for Advanced Studies E-mail: kando@nii.ac.jp

Researcher Name Resolver: identifier management system for Japanese researchers

We built a researcher identifier management system called the Researcher Name Resolver (RNR) to assist with the name disambiguation of authors in digital libraries on the Web. RNR, which is designed to cover all researchers in Japan, is a Web-oriented service that can be openly connected with external scholastic systems. We expect it to be widely used for enriched scholarly communications. In this paper, we first outline the conceptual framework of RNR, which is jointly focused on researcher identifier management and Web resource linking. We based our researcher identifier scheme on the reuse of multiple sets of existing researcher identifiers belonging to the Japanese grant database KAKEN and the researcher directory ReaD & Researchmap. Researcher identifiers are associated by direct links to related resources on the Web through a combination of methods, including descriptive mapping, focused crawling on campus directories and researcher identification by matching names and affiliations. Second, we discuss our implementation of RNR based on this framework. Researcher identifiers construct uniform resource identifiers to show Web pages that describe researcher profiles and provide links to related external resources. We have adapted Web-friendly technologies—e.g., OpenSearch and the RDFs of Linked Data technology—in this implementation to provide Web-friendly services. Third, we discuss our application of RNR to a name disambiguation task for the search portal of the Japanese Institutional Repositories Online to determine how well the researcher identifier management system cooperates with external systems. Finally, we discuss lessons learned from the entire project as well as the future development directions we intend to take.

DOI Links on Wikipedia

In this paper, we analyzed Digital Object Identifier (DOI) links among English, Japanese, and Chinese Wikipedias (hereafter, enwiki, jawiki, and zhwiki, respectively), which possibly work as a bridge between the Web users and scholarly information. Most of the DOI links in these Wikipedias were revealed to be CrossRef DOIs. The second most-referenced in jawiki were JaLC DOIs, whereas those in zhwiki were ISTIC DOIs. JaLC DOIs were uniquely referenced in jawiki, and ISTIC DOIs tend to be referenced in zhwiki. In terms of DOI prefixes, Elsevier BV was the largest registrant in all languages. Nature Publishing Group and Wiley-Blackwell were also commonly referenced. The content hosted by these registrants was shared among the Wikipedia communities. Moreover, overlapping analysis showed that jawiki and zhwiki share the DOI links with enwiki at a similar high rate. The analysis of revision histories showed that the DOI links had been added to enwiki before they were included in jawiki and zhwiki — indicating that the majority of DOI links in jawiki and zhwiki were added by translating from enwiki. These findings imply that the DOI links in Wikipedia may result in multiple counts of altmetrics.

How concept maps change if a user does search or not

Previous studies have shown that a concept map can capture changes in the user knowledge structure during a search. However, these studies could not exclude the possibility of the influence of instructions or time-dependent changes. In this study, we have compared differences between concept maps created before and after a search condition and a non-search condition to reveal whether these changes are due to searching. In the experiment, participants were required to gather information on the Web in preparation for a group discussion. The participants were divided into two groups representing two tasks, convergent and divergent tasks. The convergent task required gathering web pages for a specific and detailed discussion, and the divergent task required gathering web pages for a wide-ranging discussion. Participants performed each task under search and filler conditions. In the search condition, they searched the Web. In the filler condition, they played a typing game on a PC. We compared pre- and post-task concept maps. Analysis of the number of nodes in the concept maps indicated that changes in the search condition are significant, whereas changes in the filler condition are insignificant. The analysis of the number of nodes at each distance from the center nodes in the concept maps showed that tasks had a greater effect in the search condition than in the filler condition. Finally, we consider whether the experimental results support our hypotheses.

Overlaps between Education Paper Index and CiNii

教育分野の研究論文や雑誌記事を対象とした論文データベースである教育研究論文索引は，国立教育政策研究所教育研究情報センター教育図書館によって作成されている．この教育研究論文索引のレコードがCiNii データベースとどれくらい重複しているかについて調査し，その分析結果を報告する．調査の結果，EPI データベースの収録論文のうち59～63% はCiNii にも収録されていることが分かった．これらの調査結果は，教育研究論文索引のサービス向上のための基礎データとするとともに，実サービスにおける論文リンクとして提供している．