Trend Monitoring for Linking Science and Strategy
Rapid changes in Science & Technology (S&T) along with breakthroughs in products and services concern a great deal of policy and strategy makers and lead to an ever increasing number of Foresight and other types of forward-looking work. At the outset, the purpose of these efforts is to investigate emerging S&T areas, set priorities and inform policies and strategies. However, there is still no clear evidence on the mutual linkage between science and strategy, which may be attributed to Foresight and S&T policy making activities. The present paper attempts to test the hypothesis that both science and strategy affect each other and this linkage can be investigated quantitatively. The evidence for the mutual attribution of science and strategy is built on a quantitative trend monitoring process drawing on semantic analysis of large amount of textual data and text mining tools. Based on the proposed methodology the similarities between science and strategy documents along with the overlaps between them across a certain period of time are calculated using the case of the Agriculture and Food sector, and thus the linkages between science and strategy are investigated.
One of the most important issues for the world society in the XXI century is a task to provide pure water for citizens. As evidenced results of expert survey, made by the Higher School of Economics
significant part of water sources for drinking water in Russia doesn’t meet necessary requirements. And one of the most adequate solutions to meet this challenge is using the nanotechnologies in processes of water purification that can solve the set of problems such as polluted sources, obsolete equipment, increased risk of diseases etc. Roadmap “Applying Nanotechnology to Water Treatment” was launched by summarizing opinions of expert community participants both national and foreign regarding the most significant nanotechnologies and products made with their help which are used or can be used for water treatment and purification purposes. The aim of the research is to make special innovation routes R&D-technologies-products-markets that could be used by federal and regional authorities and Russian companies working in the field of water purification. The roadmap becomes the first largescale national foresight exercise in the area of nanotechnologies for water purification.
This paper reports a Foresight exercise, which was carried out to develop a research strategy and a business model for the science park of Ankara University (AU). Science parks have been crucial elements of innovation systems both in developed and developing countries due to their role in bridging the gap between academia and business through knowledge spill-overs and spin-offs. Although there is a widespread consensus about the usefulness of the science park concept, the actual performance of science parks and how well they meet expectations have been controversial. This paper discusses the success factors for science parks. A three dimensional policy framework, which includes ‘complementarity’, ‘networking’ and ‘strategic scalar positioning’ is suggested to be taken into account during the design and operation of science parks. The paper describes the Foresight process and the policies and strategies developed by using the three dimensional policy framework proposed for the newly established science park at Ankara University.
An important text mining problem is to find, in a large collection of texts, documents related to specific topics and then discern further structure among the found texts. This problem is especially important for social sciences, where the purpose is to find the most representative documents for subsequent qualitative interpretation. To solve this problem, we propose an interval semi-supervised LDA approach, in which certain predefined sets of keywords (that define the topics researchers are interested in) are restricted to specific intervals of topic assignments.
Purpose – This paper aims to depict foresight programmes as extended service encounters between foresight practitioners, sponsors, and other stakeholders. The implications of this perspective for evaluating the outcomes of such programmes are to be explored.
Design/methodology/approach – The range of activities comprising foresight is reviewed, along with the various objectives that may underpin these activities. The more substantial foresight programmes are seen in terms of a series of steps, in each of which various partners can be involved in generating service outcomes and later steps of the process. The arguments are illustrated with insights drawn from various cases.
Findings – A foresight programme is likely to feed into more than one policy process, so that the foresight activities can be linked to various stages of the policy cycles, as well as engaging participants with different degrees of inﬂuence on the policies in question. The outcomes of the foresight activity are also heavily shaped by the degree of involvement of various stakeholders, not least the sponsoring agency and any other groups it seeks to mobilise. Seeing foresight as a service activity brings to the fore the notion of co-production, and the importance of the design of the service encounters involved.
Research limitations/implications – The task of evaluating foresight is a challenging one, and comparison of foresight activities needs to bear in mind the different scale, scope, and ambitions of different programmes. Simple static comparison of formal inputs and outputs will miss much of the value and value-added of the activity.Practical implications – A dynamic approach to evaluation stresses the learning of lessons about the roles of multiple stakeholders – and the responsibilities of sponsors as well as practitioners. Originality/value – Foresight programmes are frequently commissioned, and often have signiﬁcant inﬂuence on decision-making. Attempts to systematically evaluate these efforts have begun, and this essay stresses the need to be aware of the complex interactive nature of foresight, highlighted by viewing it in service terms.
Concept discovery is a Knowledge Discovery in Databases (KDD) research field that uses human-centered techniques such as Formal Concept Analysis (FCA), Biclustering, Triclustering, Conceptual Graphs etc. for gaining insight into the underlying conceptual structure of the data. Traditional machine learning techniques are mainly focusing on structured data whereas most data available resides in unstructured, often textual, form. Compared to traditional data mining techniques, human-centered instruments actively engage the domain expert in the discovery process. This volume contains the contributions to CDUD 2011, the International Workshop on Concept Discovery in Unstructured Data (CDUD) held in Moscow. The main goal of this workshop was to provide a forum for researchers and developers of data mining instruments working on issues with analyzing unstructured data. We are proud that we could welcome 13 valuable contributions to this volume. The majority of the accepted papers described innovative research on data discovery in unstructured texts. Authors worked on issues such as transforming unstructured into structured information by amongst others extracting keywords and opinion words from texts with Natural Language Processing methods. Multiple authors who participated in the workshop used methods from the conceptual structures field including Formal Concept Analysis and Conceptual Graphs. Applications include but are not limited to text mining police reports, sociological definitions, movie reviews, etc.
In the past decades Foresight has been significantly developed as a tool for long-term forecasting in the field of power generation and energy efficiency. Such research aims at investigation of the most promising innovation strategies in this area, identifying various (including alternative) ways to achieve technological and market goals with the participation of best qualified experts. Such Foresight method as Roadmapping is widespread in the world practice. It helps to shape complex and interrelated views on prospects of innovation development in specific areas of energy efficiency, it links R&D programmes with creation of technologies and products, as well as their subsequent commercialization. The paper provides an overview of the world Foresight experience aimed at creating vision of the future and building innovation strategies related to energy efficiency. Special attention is paid to the Russian research practice, in particular to different types of Foresight projects implemented by the specialists of State University - Higher School of Economics. The authors describe the results of main projects dedicated to shape the future of energy-efficient technologies and to develop of innovation strategies on their application.
Concept Relation Discovery and Innovation Enabling Technology (CORDIET), is a toolbox for gaining new knowledge from unstructured text data. At the core of CORDIET is the C-K theory which captures the essential elements of innovation. The tool uses Formal Concept Analysis (FCA), Emergent Self Organizing Maps (ESOM) and Hidden Markov Models (HMM) as main artifacts in the analysis process. The user can define temporal, text mining and compound attributes. The text mining attributes are used to analyze the unstructured text in documents, the temporal attributes use these document’s timestamps for analysis. The compound attributes are XML rules based on text mining and temporal attributes. The user can cluster objects with object-cluster rules and can chop the data in pieces with segmentation rules. The artifacts are optimized for efficient data analysis; object labels in the FCA lattice and ESOM map contain an URL on which the user can click to open the selected document.
Formal Concept Analysis (FCA) is an unsupervised clustering technique and many scientific papers are devoted to applying FCA in Information Retrieval (IR) research. We collected 103 papers published between 2003-2009 which mention FCA and information retrieval in the abstract, title or keywords. Using a prototype of our FCA-based toolset CORDIET, we converted the pdf-files containing the papers to plain text, indexed them with Lucene using a thesaurus containing terms related to FCA research and then created the concept lattice shown in this paper. We visualized, analyzed and explored the literature with concept lattices and discovered multiple interesting research streams in IR of which we give an extensive overview. The core contributions of this paper are the innovative application of FCA to the text mining of scientific papers and the survey of the FCA-based IR research.
We consider certain spaces of functions on the circle, which naturally appear in harmonic analysis, and superposition operators on these spaces. We study the following question: which functions have the property that each their superposition with a homeomorphism of the circle belongs to a given space? We also study the multidimensional case.
We consider the spaces of functions on the m-dimensional torus, whose Fourier transform is p -summable. We obtain estimates for the norms of the exponential functions deformed by a C1 -smooth phase. The results generalize to the multidimensional case the one-dimensional results obtained by the author earlier in “Quantitative estimates in the Beurling—Helson theorem”, Sbornik: Mathematics, 201:12 (2010), 1811 – 1836.
We consider the spaces of function on the circle whose Fourier transform is p-summable. We obtain estimates for the norms of exponential functions deformed by a C1 -smooth phase.