LiquidPub

Liquidpub is an EU project within the "future and emerging technologies" category whose goal is to capture the lessons learned and opportunities provided by the Web and open source, agile software development to develop concepts, models, metrics, and science support services for an efficient (for people), effective (for science), and sustainable (for publishers and the community) way of creating, disseminating, evaluating, and consuming scientific knowledge. Novel services for science are a hot topic these days. From social bookmarking sites to online ranking of scientists, these services try to assist scientists in sharing content and assessing people and their scientific contributions. These services are however still very much anchored to a traditional notion of publication and are only scratching the surface of what can be done to help scientists collaborate for the greater good.

In this paper we redefine the notion of “scientific journal” to update it to the age of the Web. We explore the historical reasons behind the current journal model, and we show that this model is essentially the same today, even if the Web has made dissemination essentially free. We propose a notion of liquid and personal journals that evolve continuously in time and that are targeted to serve individuals or communities of arbitrarily small or large scales. The liquid journals provide “interesting” content, in the form of “scientific contributions” that are “related” to a certain paper, topic, or area, and that are posted (on their web site, repositories, traditional jour- nals) by “inspiring” researchers. As such, the liquid journal separates the notion of “publishing” (which can be achieved by submitting to traditional peer review journals or just by posting content on the Web) from the appearance of con- tributions into the journals, which are essentially collections of content. In this paper we introduce the liquid journal model, and demonstrate through some examples its value to individuals and communities. Finally, we describe an architecture and a working prototype that implements the proposed model.

The authors present Liquid Journal, a dissemination model and website that extends from the notion of a traditional scientific journal to overcome the problem of information overload in the scientific community. They detail Liquid Journal’s concepts, methods, and supporting platform. They also focus on the issues related to having access to relevant scientific content, such as narrowing down the discovery process to reliable sources (venues and authors) when dealing with vast amounts of information.

As the web continues to change the way we produce and disseminate scientific knowledge, traditional digital libraries are confronted with the challenge of transcending their boundaries to remain compatible with a world where the whole Web in itself is the source of scientific knowledge. This paper discusses a resource-oriented approach for the management and interaction of scientific services as a way to face this challenge. Our approach consists in building a general-purpose, extensible layer for accessing any resource that has an URI and is accessible on the Web, along with appropriate extensions specific to the scientific domain. We name the class of systems that have this functionality Scientific Resource Space Management Systems, since they are the resource analogous of data space management systems known in literature. In this paper, we describe the motivations, concepts, architecture, and implementation of the platform and one validating usage scenario.

Last years, aside the proliferation of Web 2.0, we assisted to the drastic growth of the mashup market. An increasing number of different mashup solutions and platforms emerged, some focusing on data integration (a la Yahoo! Pipes), others on user interface (UI) integration and some trying to integrate both UI and data. Most of proposed solutions have a common characteristic: they aim at providing non-programmers with a flexible and intuitive general-purpose development environment. While these generic environments could be useful for web users to develop simple applications, they are often too generic to address domain-specific needs and to allow users to develop real-life complex applications. In particular, proposed mashup mechanisms do not reflect those specific concepts that are proper of a given domain, which domain-experts are familiar with and could autonomously manage. We argue the need for domain-specific mashup architectures, also going beyond today’s enterprise platforms, in which standard mashup mechanisms and components are driven by an underlying domain-specific layer. This layer will provide a service and component ecosystem built upon a shared and uniform conceptual model specific for the given domain. This way, domain experts will be provided with mashup components and mechanisms, following those well-known concepts and rules proper of the domain they belong to, that they are able to understand, use and, finally, profitably compose. In this paper, we will show the necessity of such an architecture through a real-life use case in the context of scientific publications and journals.

Liquid Course Artifacts Software Platform aims to improve social productivity and enhance interactive experience for teaching and collaborating by using suppliment materials such as slides, exercises, audios, videos and books.

This paper presents a set of models and an extensible social web platform (namely, Knowledge Spaces) that supports novel and agile social scientific dissemination processes. Knowledge Spaces is based on a model for structured, evolving, and multi-facet scientific resources that allows the representation of structured, evolving, and multi-facet scientific knowledge and meta-knowledge, of effective “viral” algorithms for helping scientists find the knowledge they need, and of interaction metaphors that facilitate its usage.

This paper presents a set of models and an extensible social web platform (namely, Knowledge spaces) that supports novel and agile social scientific dissemination processes. Knowledge spaces is based on a model for scientific resources that allows the representation of scientific knowledge and meta-knowledge, of effective “viral” algorithms for helping scientists find the knowledge they need, and of interaction metaphors that facilitate its usage. The concept and a preliminary implementation of Knowledge spaces, in their various forms and designs, are being exploited in several different pilots.

In this demo we introduce a platform and a model of journal in the age of the Web called liquid journal. The goal of the model (and of the supporting platform) is to disseminate knowledge in the best possible way while also supporting scientists in the credit attribution. In a nutshell, liquid journals are collections of "interesting" links to scientific contributions, such as papers, blogs, datasets, that are related to certain topics. The content gets to the journal either by querying both conventional and non conventional sources on the Web or manually by the group of editors. Liquid journals combines depth and breath in bringing a wider spectrum of scientific contributions from different communities, while also focusing editors’ and readers’ attention on the things they care about. The demo illustrates the features and benefits of the proposed platform.

This paper presents a platform that facilitates building scientific ser- vices on top. We describe the problems in building such services and derive a general-purpose, extensible layer for accessing any resource that has a URI and is accessible on the Web. The platform, and more in general the classes of sys- tems that have this functionality, is referred to as Resource Space Management System and is the (scientific) resource analogous of a data space management system. In this paper we describe the model and conceptual architecture of the platform, discuss its benefits and outline the research plan for its realization.

In this research work, we address the limitations of the current scientific knowledge dissemination model to face the new scenario posed by the Web. We explore the historical reasons behind the current model, and we show that it is essentially the same today, even if the Web has made dissemination nearly real time and free. We show how this misalignment between the current model and Web capabilities brings not only missed opportunities but also a serious overload problem, creating difficulties for authors to gain visibility, and for readers to find interesting content. Our approach has been to build from the ground up, by i) understanding how the very core concepts of scientific publishing such as "scientific contribution," "scientific journal," and even "reputation" should adapt to the new scenario; ii) studying the dissemination and sharing practices that are inherently present in the scientific community, to understand how technology can empower those practices to reduce information overload. The outcome is novel models, tools, and a platform for knowledge dissemination that takes full advantage of the Web while addressing the overload problem.

In the last decade, scholarly communication have been greatly transformed by the web, moving research dissemination away from printed papers in journals to digital content that can be easily posted on the Internet. This technical factor along with a larger scientific community makes it really hard to find relevant content for research in the ever growing sea of publications. With the goal of gaining insights on how researchers find relevant knowledge, we have interviewed a small group of researchers and then opened an online survey to a larger group, asking them to explain how they had found references for one of their papers. The results of this study suggest that finding scientific knowledge has a strong social component, with the different researchers’ social networks (e.g., coauthors, people met at conferences) accounting for a important percentage of the source of the references. In this paper we report on this study and compare our results with the evidence found in a dataset of 5 x 106 authors with their publications and references. We take these results and analyze different approaches for incorporating the social component into search and recommendation of scientific publications.