Harvesting Knowledge

{Excerpt} If 80% of knowledge is unwritten and largely unspoken, we first need to elicit that before we can articulate, share, and make wider use of it. Knowledge harvesting is one way to drawout and package tacit knowledge to help others adapt, personalize, and apply it; build organizational capacity; and preserve institutional memory. The so-called know-do gap is one outcome of poor knowledge translation and organizational forgetting. In decreasing order of incidence, that is commonly attributed to (i) shortage of resources, e.g., skills, time, and finance, (ii) lack of buy in at all levels within and across organizations, and (iii) information overload. Shortage of resources affects policymakers, researchers, and practitioners equally. In the 21st century, intra-organizational flows of knowledge have become as important as the resource itself. And so, managing both stocks and flows has become an imperative rather than an alternative for most organizations. Knowledge harvesting is a means to draw out, express, and package tacit knowledge to help others adapt, personalize, and apply it; build organizational capacity; and preserve institutional memory. In addition to context and complexity, the concepts that relate to it are tacit knowledge stocks, tacit knowledge flows, and enablers and inhibitors of tacit knowledge work

Point Cloud in the Air

Acquisition and processing of point clouds (PCs) is a crucial enabler for many emerging applications reliant on 3D spatial data, such as robot navigation, autonomous vehicles, and augmented reality. In most scenarios, PCs acquired by remote sensors must be transmitted to an edge server for fusion, segmentation, or inference. Wireless transmission of PCs not only puts on increased burden on the already congested wireless spectrum, but also confronts a unique set of challenges arising from the irregular and unstructured nature of PCs. In this paper, we meticulously delineate these challenges and offer a comprehensive examination of existing solutions while candidly acknowledging their inherent limitations. In response to these intricacies, we proffer four pragmatic solution frameworks, spanning advanced techniques, hybrid schemes, and distributed data aggregation approaches. In doing so, our goal is to chart a path toward efficient, reliable, and low-latency wireless PC transmission

Challenges and potential of the Semantic Web for tourism

The paper explores tourism challenges and potential of the Semantic Web from a theoretical and industry perspective. It first examines tourism business networks and explores a main theme of network interoperability - data standards- followed by technology deficiencies of Web 1.0 and 2.0 and Semantic Web solutions. It then explicates Semantic opportunities and challenges for tourism, including an industry perspective through a qualitative approach. Industry leaders considered that the new Web era was imminent and heralded benefits for supply and demand side interoperability, although management and technical challenges could impede progress and delay realisation

The Art of collaborative storytelling: arts-based representations of narrative contexts”

Draft for: ISA Research Committee on Biography and Society. The author analyses several theories about science and arts converging in a new point of view. Also talks about the functions of storytelling. He starts his work with these phrases: 'Art and science have a common thread - both are fuelled by creativity. Whether writing a paper based on my data or filling a canvas with paint, both processes tell a story' (Taylor 2001) 'Science and art are complementary expressions of the same collective subconscious of society' (Morton 1997:1

UIMA in the Biocuration Workflow: A coherent framework for cooperation between biologists and computational linguists

As collaborating partners, Barcelona Media Innovation Centre and GRIB (Universitat Pompeu Fabra) seek to combine strengths from Computational Linguistics and Biomedicine to produce a robust Text Mining system to generate data that will help biocurators in their daily work. The first version of this system will focus on the discovery of relationships between genes, SNPs (Single Nucleotide Polymorphisms) and diseases from the literature.

A first challenge that we were faced with during the setup of this project is the fact that most current tools that support the curation workflow are complex, ad-hoc built applications which sometimes make difficult the interoperability and results sharing between research groups from different and unrelated expert fields. Often, biologists (even computer-savvy ones) are hard pressed to use and adapt sophisticated Natural Language Processing systems, and computational linguists are challenged by the intricacies of biology in applying their processing pipelines to elicit knowledge from texts. The flow of knowledge (needed to develop a usable, practical tool) to and from the parties involved in the development of such systems is not always easy or straightforward.

The modular and versatile architecture of UIMA (Unstructed Information Management Architecture) provides a framework to address these challenges. UIMA is a component architecture and software framework implementation (including a UIMA SDK) to develop applications that analyse large volumes of unstructured information, and has been increasingly adopted by a significant part of the BioNLP community that needs industrial-grade and robust applications to exploit the whole bibliome. The use of UIMA to develop Text Mining applications useful for curation purposes allows the combination of diverse expertises which is beyond the individual know-how of biologists, computer scientists or linguists in isolation. A good synergy and circulation of knowledge between these experts is fundamental to the development of a successful curation tool