Keeping the pace with the faster and faster evolution of knowledge is becoming a challenge, especially for researchers and knowledge workers. We propose a vision towards a set of (possibly integrated) publicly available tools that can help on this. To this purpose, we expect tools that can improve e ectiveness of knowledge extraction, storage, analysis, publishing and experimental benchmarking. This could be extremely bene cial for the entire research community across elds and interests. We describe our vision in this direction and we demonstrate its feasibility with some exemplary tools that we developed and that we shared as public resources to be used by the research community.
Nanos gigantum humeris insidentes (Bernard of Chartres, 1115 AD ca.)
Science aims at creating new knowledge upon the existing one, from the observation of physical phenomena, their modeling and empirical validation. This combines the well known motto \standing on the shoulders of giants" (attributed to Bernard of Chartres and subsequently rephrased by Isaac Newton) with the need of trying and validating new experiments.
However, knowledge in the world continuously evolves, at a pace that cannot
be traced even by large crowdsourced bodies of knowledge such as Wikipedia.
A large share of generated data are not currently analysed and consolidated
into exploitable information and knowledge [
This becomes a challenge for practitioners, enterprises and scholars / researchers, which need to be up to date to innovation and emerging facts. The scienti c community also need to make sure there is a structured and formal way to represent, store and access such knowledge, for instance as ontologies or linked data sources.
Our idea is to propose a vision towards a set of (possibly integrated)
publicly available tools that can help scholars keeping the pace with
the evolving knowledge. This implies the capability of integrating informal
sources, such as social networks, blogs, and user-generated content in general.
One can conjecture that somewhere, within the massive content shared by people
online, any low-frequency, emerging concept or fact has left some traces. The
challenge is to detect such traces, assess their relevance and trustworthiness,
and transform them into formalized knowledge [
An appropriate set of tools that can improve e ectiveness of knowledge extraction, storage, analysis, publishing and experimental benchmarking could be extremely bene cial for the entire research community across elds and interests. 2
We foresee a paradigm where knowledge seeds can be planted, and subsequently
grow, nally leading to the generation and collection of new knowledge, as
depicted in the exemplary process in Figure 1 [
We advocate for a set of tools that, when implemented and integrated, enable the following perspective reality: { possibility of selecting any kind of source of raw data, independently of their format, type or semantics (spanning quantitative data, textual content, multimedia content), covering both data streams or pull-based data sources; { possibility of applying di erent data cleaning and data analysis pipelines to the di erent sources, in order to increase data quality and abstraction / aggregation; { possibility of integrating the selected sources; { possibility of running homogeneous knowledge extraction processes of the integrated sources; { possibility of publishing the results of the analysis and semantic enrichment as new and further (richer) data sources and streams, in a coherent, standard and semantic way.
This enables generation of new sources which in turn can be used in subsequent knowledge extraction processes of the same kind. The results of this process must be available at any stage to be shared for building an open, integrated and continuously evolving knowledge for research, innovation, and dissemination purposes. 3
Whilst bene cial and powerful, the vision we propose is far from being achieved
nowadays. However, we are convinced that the vision is not out of reach in the
mid term. To give a hint of this, we report here our experience with the research,
design and implementation of a few tools that point in the proposed direction:
1. Social Knowledge Extractor (SKE) is a publicly available tool for
discovering emerging knowledge by extracting it from social
content. Once instrumented by experts through very simple initialization, the
tool is capable of nding emerging entities by means of a mixed
syntacticsemantic method. The method uses seeds, i.e. prototypes of emerging entities
provided by experts, for generating candidates; then, it associates candidates
to feature vectors, built by using terms occurring in their social content, and
then ranks the candidates by using their distance from the centroid of seeds,
returning the top candidates as result. The tool can run continuously or
with periodic iterations, using the results as new seeds. Our research on this
has been published in [
We believe that knowledge intaking by scholars is going to become more and more time consuming and expensive, due to the amount of knowledge that is being built and shared everyday. We envision a comprehensive approach based on integrated tools that allow data collection, cleaning, integration, analysis and semantic representation that can be run continuously for keeping the formalized knowledge bases aligned with the evolution of knowledge, with limited cost and high recall on the facts and concepts that emerge or decay. These tools do not need to be implemented by the same vendor or provider; we instead advocate for opensource publishing of all the implementations, as well as for the de nition of an agreed-upon integration platform that allows them all to integrate appropriately. 5
As we envisioned an ecosystem that includes, but is not limited to, modules for extraction, sharing and benchmarking, two research questions require investigation in the immediate future.
First, how can we design and publish new resources for such an ecosystem? Do they exist already? It is important to understand what else is available out there. Researchers commonly support their scienti c studies with resources that can bene t the whole community, if released. The release process must comply with a scienti c method that ensures repeatability and reproducibility. However, a standard agreed-upon methodology that guide this process does not exists yet.
Second, how should we combine these resources towards shared research work ows? To investigate this research question, we need a platform that enables researchers to deploy their resources and interact with the ecosystem. Therefore, we call for an open discussion about how this integration should be done. References