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The purpose of this paper is to evaluate innovations in intellectual property rights (IPR) databases, techniques and software tools, with an emphasis on selected new developments and their contribution towards achieving advantages for IPR management (IPRM) and wider social benefits. Several industry buzzwords are addressed, such as IPR-linked open data (IPR LOD) databases, blockchain and IPR-related techniques, acknowledged for their contribution in moving towards artificial intelligence (AI) in IPRM.

The evaluation, following an original framework developed by the authors, is based on a literature review, web analysis and interviews carried out with some of the top experts from IPR-savvy multinational companies.

The paper presents the patent databases landscape, classifying patent offices according to the format of data provided and depicting the state-of-art in the IPR LOD. An examination of existing IPR tools shows that they are not yet fully developed, with limited usability for IPRM. After reviewing the techniques, it is clear that the current state-of-the-art is insufficient to fully address AI in IPR. Uses of blockchain in IPR show that they are yet to be fully exploited on a larger scale.

A critical analysis of IPR tools, techniques and blockchain allows for the state-of-art to be assessed, and for their current and potential value with regard to the development of the economy and wider society to be considered. The paper also provides a novel classification of patent offices and an original IPR-linked open data landscape.

In response to its mission of identifying and describing problems of interdisciplinary searching, and of proposing remedies and solutions, the ICSTI Group on Interdisciplinary Searching gathered the relevant information through a questionnaire addressed to the database builders, online system vendors, search intermediaries and end users; analysed and organised the input; and presented a report. The report discusses the problems within six distinct categories: coverage and technical content of the database; bibliographic information; textual content; numeric data; file organisation, and interdisciplinary searching on multiple hosts. Under each category, problems are first listed in a generic way and then described in greater detail. Numerous specific examples are given with explanations, whenever feasible, of the reasons for their occurrence. For each category, possible remedies and solutions are listed. The most essential recommendations that have emerged deal with the need for greater standardisation at every stage in building the databases and in organising access to them. A number of bodies and groups working on international and national standards, and on solving other specific aspects of the problems, have been identified. The needs for close co‐operation, exchange of good documentation, extensive training and mutual understanding are most evident.

The purpose of this paper is to highlight the main Intellectual Property (IP) protection strategies adopted in the R&D phases of a company operating in the bio-pharmaceutical industry, according to an open innovation (OI) approach.

In order to assess how R&D intensive firms adopt IP strategies during OI practices, this research uses a single case-study design. The case has been studied over an extended period of time (from 2008 to 2015), triangulating data and information by means of multiple interviews with different key informants and projects documents. The novelty of the research justifies the use of a single case study.

The study reveals how a mix of formal and informal tools for IP protection are used, with a final attempt to maintain control over different technological solutions during their validation process and profiting from stable R&D collaborations with research partners.

Limitations of the study relate to the single case study methodology as well as to some peculiarities of the analyzed company and of the Bio-Pharmaceutical industry.

Research managers could find some food for thought in the adoption of OI approaches for reducing costs and risks associated with technological uncertainty, with particular attention to the strategic role of IP rights.

Despite knowledge protection being widely recognized to be a critical issue for implementing OI approaches, how IP strategies should be used in the different phases of R&D is still debatable. Moreover, few empirical studies relate to the adoption of optimal combinations of IP tools in relation to the different R&D phases in such technology intensive industries as the bio-pharmaceutical industry.

Defining and validating a map of related technologies is critical for managers, investors and inventors. Because of the increase in the applications of and demand for semiconductor lasers, analyzing the technological position of developers has become increasingly critical. Therefore, the purpose of this study is to adopt the technological position analysis to identify mainstream technologies and developments relevant to semiconductor lasers.

Correspondence analysis and k-means cluster analysis, which are data mining techniques, are used to reveal strategic groups of major competitors in the semiconductor laser market according to their Patent Cooperation Treaty (PCT) patent applications.

The results of this study reveal that PCT patent applications are generally obtained for masers, optical elements, semiconductor devices and methods for measuring and that technology developers have varying technological positions.

Through position analysis, this study identifies the technological focuses of different manufacturers to obtain information that can guide the allocation of research and development resources.

This paper aims to forecast the future of data storage technologies, using the case of two major technologies driving the data storage world; hard disk drive (HDD) or conventional longitudinal recording and flash memory.

Four principal tools of forecasting technology are applied to present the coming future of data storage technologies. These tools consist of bibliometric trend analysis, patent trend analysis, technology cycle time (TCT), and growth curve. Numbers of publications each year and cumulative patents are used to analyze the future of these competitive technologies. The median age of the patents is applied to find the technology lifecycle of both technologies. Finally, areal density of HDD is plotted on the growth curve to forecast the saturation point of researching on conventional longitudinal recording.

The results produced from utilizing these tools indicate that these two technologies are continuously under development. It is found that the growth of improving areal density of conventional recording will be nearing zero by year 2013 and the maximum growth rate of development was in year 2006.

The forecasting is based on principal technologies of conventional longitudinal recording of HDD. Also, NOR and NAND are considered as two main technologies dominating flash memory. Other emerging data storage technologies such as holographic data storage, phase‐change memory (PCM) are not included in this paper. Likewise, the growth curve of flash memory is not analyzed as part of this paper.

This paper forecasts the future of data storage technologies. Integration of scientific indicators and growth curves is demonstrating a powerful tool for forecasting technology futures.

To study the mathematical image coding approaches used in two types of biometric systems, and the physical nature of those biometrics.

Gives details of algorithms used to encode data from images in established and new automatic iris recognition systems. Then examines face recognition techniques based on geometry, texture and three‐dimensional data.

Most commercial iris recognition systems are based on the algorithms developed by one man, John Daugman. Whilst iris systems can be used to check a person's identity against a large database of enrolled people, face recognition systems are currently only capable of use in one‐to‐one recognition mode, or in identification mode against a very small database. The iris is very distinctive and stable over time, but the face is much more variable and therefore difficult to identify with accuracy.

Provides the general scientific reader with some insight into the specialised field of biometric recognition.

Ericsson Information Systems. L. M. Ericsson, the Swedish telecommunications giant, has just formed a new company — Ericsson Information Systems (EIS) — which will compete in the information technology market. The new company has been created out of two Ericsson divisions and Datasaab, a Swedish computer firm, which Ericsson bought a year ago. EIS is expected to continue marketing Datasaab's successful terminal and minicomputer, but in addition will develop and sell products for the private and business markets, particularly integrated information systems, office automation systems and PABXs.