Enterprise Search in the European Union: A Techno-economic Analysis

This Report contributes to the work being carried out by IPTS on the potential of Search, discussing, in particular, the prospects of Enterprise search as well as the main challenges and opportunities. It is part of CHORUS+, an initiative supported by the Directorate General Information Society and Media. Information about CHORUS+ is available at http://avmediasearch.euJRC.J.3-Information Societ

Finding Health & Safety Buried Treasure with AI

PresentationThe challenge to glean understanding and insight from an array of historical safety-related reports and observations has existed since the dawn of the HSE discipline. While most organizations today use traditional methods to analyze past events and activities along structured elements (time, place, risk rating and so on), a vast amount of wisdom around hazard identification, root causes and risk control measures remains buried in textual descriptions and reports, and teachable moments become lessons lost. The hands and minds that developed these textual artifacts may be among the most seasoned in the organization, bringing years of experience to bear on the issues and opportunities involved. Such artifacts are then clearly buried treasure. Exploring and surfacing the insights contained in artifact repositories calls for new tools. Using these, a new type of H&S performance indicator could emerge: latent indicators, lying concealed within the written record, offering as much or more value as the leading and lagging indicators used today. This paper describes leveraging the power of artificial intelligence (AI) to absorb large amounts of safety-related textual information, find common themes and identify similar events, which are then analyzed for patterns in causes and controls. This solution, used in concert with traditional analytics, offers unprecedented power to comprehend and visualize collective safety knowledge from historical record. Transforming words to wisdom in this manner not only illuminates the past but also provides a basis for actioning improvements in operational excellence

Big data-driven investigation into the maturity of library research data services (RDS)

Research data management (RDM) poses a significant challenge for academic organizations. The creation of library research data services (RDS) requires assessment of their maturity, i.e., the primary objective of this study. Its authors have set out to probe the nationwide level of library RDS maturity, based on the RDS maturity model, as proposed by Cox et al. (2019), while making use of natural language processing (NLP) tools, typical for big data analysis. The secondary objective consisted in determining the actual suitability of the above-referenced tools for this particular type of assessment. Web scraping, based on 72 keywords, and completed twice, allowed the authors to select from the list of 320 libraries that run RDS, i.e., 38 (2021) and 42 (2022), respectively. The content of the websites run by the academic libraries offering a scope of RDM services was then appraised in some depth. The findings allowed the authors to identify the geographical distribution of RDS (academic centers of various sizes), a scope of activities undertaken in the area of research data (divided into three clusters, i.e., compliance, stewardship, and transformation), and overall potential for their prospective enhancement. Although the present study was carried within a single country only (Poland), its protocol may easily be adapted for use in any other countries, with a view to making a viable comparison of pertinent findings

Exploring Knowledge Transfer and Knowledge Building at Offshore Technical Support Centers

This is an exploratory investigation into knowledge transfer and knowledge building processes observed at offshore Technical Support Centers (TSCs) in China. Utilizing a multiple case study approach, the study examines how knowledge was transferred from the US-based support center to the China-based offshore support center, and how individuals and the organization built and expanded knowledge in a dynamic changing business context. The field cases were three Technical Support Centers in China. Three models were developed from the qualitative analysis of the field data to explain how knowledge is transferred and built in offshore TSCs. The knowledge transfer type adoption model identifies the relationships amongst the levels of knowledge (novice, advanced beginner, competency, and proficiency), the types of knowledge and the knowledge transfer approaches (structured transfer stages, unstructured copy, unstructured adaptation, and unstructured fusion). The basic individual tacit knowledge building model shows that tacit knowledge is acquired and built through two continuous knowledge building loops, an explicit learning loop and an implicit learning loop. The organizational knowledge building model demonstrates the interaction amongst knowledge flow, absorptive capacity, knowledge stock and knowledge intermediary in offshore knowledge transfer and building within the three levels (individual, group and organization levels) of the SECI spiral (socialization, externalization, combination and internalization). The three models provide new insights into the knowledge transfer process for different levels of knowledge acquisition, individual tacit knowledge building processes and organizational knowledge building processes in an offshore outsourcing business context. By applying these models to appropriate field situations, both practitioners and academics may be able to gain a deeper understanding of knowledge transfer approaches, be able to better guide new employees’ expertise and confidence building through controlled and monitored experiential learning process, and be able to improve understanding of how knowledge is built and evolves within organizations

Using Cyber-enabled Transaction Data to Study Productivity and Innovation in Organizations

This paper draws on recent research in a wide variety of disciplines to identify the key elements necessary to build an empirical infrastructure that will advance research on one of the key building blocks of science and innovation policy: organizations. We argue that cyber-tools and new data will permit researchers to examine the innovation process |both successes and failures| and explore business performance and business dynamics at the level of the appropriate economic entity. We develop a roadmap that outlines how the new data can be developed, from harvesting the web to direct observation from deep within companies. The paper identifies a set of research questions and an approach whose pursuit could be used to develop a national research data infrastructure for the study of innovation and organizational performance. One key element of the approach is to identify and study innovation processes within organizations by collecting data on inputs and outcomes of innovation projects (or initiatives) within organizations. Another is the collection of representative data by business function/processes across firms, a proven statistical and economic approach (Sturgeon et al. 2006, Brown 2008, Lewin et al 2008). Finally, we argue that the work to develop new data from deep within firms should involve the participation of computer and information scientists. Opportunities for quasi experimental approaches to data collection, and noninvasive techniques to harvest data from within firms (i.e., auto-populating of researcher databases) need to be explored. More generally, the bringing together of scientists to consider business microdata privacy/access and data collection from organizations is itself significant, with potential for creating opportunities in a broad range of applications.

The Next Wave of CRM Innovation: Implications for Research, Teaching, and Practice

Globalization and customers’ ever-changing needs have created a hyper-competitive market. As a result, customer relationship management (CRM) has become a core topic of interest among both practitioners and academics. Further, over the years, with the advancements in the technology landscape, such as digital technologies, CRM has improved in myriad ways. This paper summarizes a panel discussion on CRM innovations held at the 2016 Pacific Asia Conference on Information Systems (PACIS 2016) in Chiyai, Taiwan. The panel discussed CRM fundamentals and how traditional CRM systems work in organizations. Then, the panel focused on the advancement in technology landscape such as big data, analytics, Internet of things, and artificial intelligence and how such technologies have transformed innovations in the CRM landscape. Finally, the panel highlighted the limitations in the current CRM curricula in the universities and how the curriculum today needs to reflect such advancements to enhance the union between the CRM curricula and the industry needs. Further, this paper provides future research ideas for academia and contributes to research interests on CRM in general

Преглед на технологични решения за управление на знания

The present paper focuses on a new managerial discipline emerging in the last few years of the 20th century. At the beginning are introduced some basic concepts used in the theory and practice of Knowledge Management, and are presented the benefits for utilization of Knowledge management. The main emphasis of the paper is on the technological solutions applied in the organizations at different stages of the knowledge management life cycle, whereas a summary is made of the types of technologies described in the theory and practice. Finally, are presented survey data on the real application of various knowledge management technologies in the organization

CHORUS Deliverable 2.2: Second report - identification of multi-disciplinary key issues for gap analysis toward EU multimedia search engines roadmap

After addressing the state-of-the-art during the first year of Chorus and establishing the existing landscape in multimedia search engines, we have identified and analyzed gaps within European research effort during our second year. In this period we focused on three directions, notably technological issues, user-centred issues and use-cases and socio- economic and legal aspects. These were assessed by two central studies: firstly, a concerted vision of functional breakdown of generic multimedia search engine, and secondly, a representative use-cases descriptions with the related discussion on requirement for technological challenges. Both studies have been carried out in cooperation and consultation with the community at large through EC concertation meetings (multimedia search engines cluster), several meetings with our Think-Tank, presentations in international conferences, and surveys addressed to EU projects coordinators as well as National initiatives coordinators. Based on the obtained feedback we identified two types of gaps, namely core technological gaps that involve research challenges, and “enablers”, which are not necessarily technical research challenges, but have impact on innovation progress. New socio-economic trends are presented as well as emerging legal challenges

Managing digital forensic knowledge an applied approach

The science of digital forensics is continually changing as technological advances are made and new digital devices are developed. This environment forces analysts to regularly extend their skills with training and frequent research to develop new and admissible techniques. Unfortunately, the same and similar methods are re-discovered by other analysts who are unaware of earlier peer efforts. The situation is aggravated by a nearly universal backlog in qualified digital forensics facilities. This leaves little time for communication between analysts even within a single agency. To address these issues and facilitate an increase in efficiency across all law enforcement agencies, we apply the lessons of knowledge management to digital forensics and extend them with special characteristics required by the law enforcement profession. The result is the development of the National Repository of Digital Forensic Intelligence. This system has been implemented in the largest accredited digital forensics lab in the world and is currently being extended to many other local, state, and federal agencies to increase effectiveness and efficiency among analysts