e-infrastructure Roadmap for Open Science in Agriculture

A bibliometric study

The e-ROSA project seeks to build a shared vision of a future sustainable e-infrastructure for research and education in agriculture in order to promote Open Science in this field and as such contribute to addressing related societal challenges. In order to achieve this goal, e-ROSA’s first objective is to bring together the relevant scientific communities and stakeholders and engage them in the process of coelaboration of an ambitious, practical roadmap that provides the basis for the design and implementation of such an e-infrastructure in the years to come.

This website highlights the results of a bibliometric analysis conducted at a global scale in order to identify key scientists and associated research performing organisations (e.g. public research institutes, universities, Research & Development departments of private companies) that work in the field of agricultural data sources and services. If you have any comment or feedback on the bibliometric study, please use the online form.

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On characterizing and computing the diversity of hyperlinks for anti-spamming page ranking


With the advent of big data era, efficiently and effectively querying useful information on the Web, the largest heterogeneous data source in the world, is becoming increasingly challenging. Page ranking is an essential component of search engines because it determines the presentation sequence of the tens of millions of returned pages associated with a single query. It therefore plays a significant role in regulating the search quality and user experience for information retrieval. When measuring the authority of a web page, most methods focus on the quantity and the quality of the neighborhood pages that direct to it using inbound hyperlinks. However, these methods ignore the diversity of such neighborhood pages, which we believe is an important metric for objectively evaluating web page authority. In comparison with true authority pages that usually contain a large number of inbound hyperlinks from a wide variety of sources, it is difficult for fake authorities, which boost their page rank using techniques such as link farms, to occupy the high diversity of inbound hyperlinks due to prohibitively high costs. We propose a probabilistic counting-based method to quantitatively and efficiently compute the diversity of inbound hyperlinks. We then propose a novel link-based ranking algorithm, named Drank, to rank pages by simultaneously analyzing the quantity, quality and diversity of their inbound hyperlinks. The validations on both synthetic and real-world data show that Drank outperforms other state-of-the-art methods in terms of both finding high-quality pages and suppressing web spams. (C) 2015 Elsevier B.V. All rights reserved.

  • CN
  • Jilin_Univ (CN)
  • Minist_Educ (CN)
Data keywords
  • big data
Agriculture keywords
  • farm
Data topic
  • big data
  • information systems
Document type

Inappropriate format for Document type, expected simple value but got array, please use list format

Institutions 10 co-publis
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    e-ROSA - e-infrastructure Roadmap for Open Science in Agriculture has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 730988.
    Disclaimer: The sole responsibility of the material published in this website lies with the authors. The European Union is not responsible for any use that may be made of the information contained therein.