Knowledge Dissemination in the Web Era
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In this presentation I’m going to introduce you the problems, opportunities and challenges posed by the Web to the current knowledge dissemination scenario. Of course, this is a rather general area, so in this project I focus on the implications on the scientific domain, where even a small change can really make the difference.
![Knowledge Dissemination in the Web Era Marcos Baez [email_address] Marcos Baez [email_address] dbTrento– Feb 26th, 2010](https://image.slidesharecdn.com/2010-02-26-dbtrento-towardsaknowledgedisseminationmodel-100226102850-phpapp01/85/Knowledge-Dissemination-in-the-Web-Era-1-320.jpg)
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Knowledge Dissemination in the Web Era
- 1. Knowledge Dissemination in the Web Era Marcos Baez [email_address] Marcos Baez [email_address] dbTrento– Feb 26th, 2010
- 8. Hints for the Solution: Liquid journals Towards a Knowledge Dissemination Model in the Web Era
- 9. Liquid journal: Conceptual model Towards a Knowledge Dissemination Model in the Web Era
- 10. Let’s watch a video.. Towards a Knowledge Dissemination Model in the Web Era http://www.youtube.com/watch?v=iPmG1iQjjh0 [part1] http://www.youtube.com/watch?v=OfAFpw0NaLU [part2]
- 11. Liquid journals model Towards a Knowledge Dissemination Model in the Web Era Liquid journal Scientific contributions Process Editors Community Journal definition language Internet
- 12. Liquid journals: Evolution Towards a Knowledge Dissemination Model in the Web Era Liquid journal Liquid journal Issues Temporal links Structural links Structural, Temporal, Semantic links Scientific contributions
- 16. Liquid journals: Infrastructure Towards a Knowledge Dissemination Model in the Web Era Accessing and Querying scientific resources Implementation of the overall journal model Usage = human (key)
- 20. Marcos Baez [email_address] Marcos Baez [email_address] Thanks for your attention!
Hinweis der Redaktion
- In this presentation I’m going to introduce you the problems, opportunities and challenges posed by the Web to the current knowledge dissemination scenario. Of course, this is a rather general area, so in this project I focus on the implications on the scientific domain, where even a small change can really make the difference.
- The Web has changed the way we get, share, produce and consume scientific content. Publishing is almost free. Just consider journals: They provide content of certain quality on certain topics. They’re useful to find content, to evaluate people(?). But if we look at what’s under the hood, we can see that most of their features are there because of historical reasons, because we had only printed materials, and so printing and shipping costs associated. But now, we have not only the digital versions of these printed materials, but also new types of scientific content: We have blogs, papers, datasets.. provided by a variety of services on the Internet.
- We have not only digital libraries and other conventional sources
- These, along with social changes, has also increased the number of people and thus scientific artifacts that are disseminated in increasing shorter periods of time. The problem has become, for the readers. How do I get interesting an relevant content? For the authors, how do I make my work visible?
- The reasons for the current dissemination model based on papers, peer-review and is gone..
- The goal of this research project is to identify a model for ``scientific journals" in the Web era and develop the infrastructure for creating and filling them with content. We aim at introducing a fundamental change in the scientific dissemination model with the specific goals of i) making it significantly more *efficient* and *effective* but also flexible, with the meanings described above, ii) facilitating and encouraging behaviors that are good for science, and iii) evaluating others aspects of research activity by going beyond traditional citation-based metrics that well have shown to have flaws [krapivin2008exploring] [haque2009positional] [simkin2005stochastic].
- With liquid journals we are trying to explore how new ways of creating content, the social web and what has made of the web a success can be used to overcome existing problems and exploit the benefits posed by the Web.
- Liquid or evolving journals, as opposed to the “solid” traditional journals. The journal is defined as a query over the Web The editor specifies the type and properties of the content. The editor can also select the process
- Define conceptual models for scientific contributions and journals, in a way they are extensible and flexible enough to deal with the range of possibilities the Web offer and the preferences of editors. The lesson learned from existing journal models is that there is not only one possible model for everyone, and different communities may work with different models. A journal model for the age of the Web should be able to play with these possibilities and accommodate to the needs of editors and communities. Implement the abstractions for accessing and querying the Web. This is a very complex task. We need to look at the Web as the emerging source of scientific content . Nowadays, new types of scientific content, interesting from the research perspective, fall outside the boundaries of traditional libraries and journals, and are dispersed among non conventional sources and services on the Web (e.g., blogs, dataset and experiment sharing sites). A new model of journal should be able to go beyond traditional sources. This implies i) Accessing distributed and heterogeneous repositories of scientific contributions (with the broad meaning described in this paper); ii) Querying information in these repositories. This requires a query language and a query engine. The language is conceptually analogous to SQL but we select (part of) contributions, from various repositories where - and this is the most challenging part - contributions have certain characteristics of similarity and interestingness. In other words, we need to both filter and join not only on traditional attributes (author, conference) but most interestingly on aspects such as relevance, quality, and so on. iii) Raising events in a push fashion in addition to allowing query, to enable real-time results. Scalability. Providing a machinery like the one described above implies special considerations in terms terms of scalability (e.g., distributing load, efficient algorithms). Provide mechanisms to deal with the noise, involving automatic and manual strategies. Design reputation metrics in a way we can minimize the risks in terms of people misusing the metrics trying to tweak the system. These risks occur often on the web (e.g., fake amazon reviews, or mainly wikipedia) yet somehow it seems to work. This requires a careful design. Identify how to evaluate interestingness, diversity, similarity and quality (for contributions, but also for contributors) with minimal or no explicit user involvement (similarity and quality can be deduced by looking at users' queries and user interactions with the query results, such as forwarding and bookmarking). Explicit involvement (e.g., rating, or definition of keywords on papers, or ontologies) may be used if available, but they are by no means a requirement. This also requires designing and architecting the part of the system that collects user interaction data, query execution data, and journal content to support computation of interestingness and similarity. Design the user interaction so that the system is sufficiently simple to be used by the average scientist.
- It allows researchers to have a tailored journal to read what they care about. It allows real-time dissemination, that is, it exposes new ideas and brainstorming-like thoughts besides validated/reviewed research. It also exposes papers as soon as they ``appear" on the Web. It combines breadth and depth: It combines personalization with awareness to diversity as the journal selection model allows combining relevance, novelty, and interest as search criteria.. It exploits the filtering power of the community to help select interesting contributions. .. It rewards creativity, early sharing of ideas, and collaboration: by considering (and therefore rewarding) blogs and in general non-reviewed thoughts as contributions, it encourages scientist to share their ideas. .. Look into other aspects of researchers’ productivity and not only “paper writing” it will naturally allow the community to select a dissemination model preferred by the community, and this will happens by looking at which journal models among the many variations available to editors (combinations of selection process, kind of contributions, reputation metrics) are eventually successful.