146 research outputs found
Expert Finding in Disparate Environments
Providing knowledge workers with access to experts and communities-of-practice is central to expertise sharing, and crucial to effective organizational performance, adaptation, and even survival. However, in complex work environments, it is difficult to know who knows what across heterogeneous groups, disparate locations, and asynchronous work. As such, where expert finding has traditionally been a manual operation there is increasing interest in policy and technical infrastructure that makes work visible and supports automated tools for locating expertise.
Expert finding, is a multidisciplinary problem that cross-cuts knowledge management, organizational analysis, and information retrieval. Recently, a number of expert finders have emerged; however, many tools are limited in that they are extensions of traditional information retrieval systems and exploit artifact information primarily. This thesis explores a new class of expert finders that use organizational context as a basis for assessing expertise and for conferring trust in the system. The hypothesis here is that expertise can be inferred through assessments of work behavior and work derivatives (e.g., artifacts).
The Expert Locator, developed within a live organizational environment, is a model-based prototype that exploits organizational work context. The system associates expertise ratings with expert’s signaling behavior and is extensible so that signaling behavior from multiple activity space contexts can be fused into aggregate retrieval scores. Post-retrieval analysis supports evidence review and personal network browsing, aiding users in both detection and selection. During operational evaluation, the prototype generated high-precision searches across a range of topics, and was sensitive to organizational role; ranking true experts (i.e., authorities) higher than brokers providing referrals. Precision increased with the number of activity spaces used in the model, but varied across queries. The highest performing queries are characterized by high specificity terms, and low organizational diffusion amongst retrieved experts; essentially, the highest rated experts are situated within organizational niches
Software development process mining: discovery, conformance checking and enhancement
Context. Modern software projects require the proper allocation of human, technical and
financial resources. Very often, project managers make decisions supported only by their personal
experience, intuition or simply by mirroring activities performed by others in similar
contexts. Most attempts to avoid such practices use models based on lines of code, cyclomatic
complexity or effort estimators, thus commonly supported by software repositories which are
known to contain several flaws.
Objective. Demonstrate the usefulness of process data and mining methods to enhance the
software development practices, by assessing efficiency and unveil unknown process insights,
thus contributing to the creation of novel models within the software development analytics
realm.
Method. We mined the development process fragments of multiple developers in three
different scenarios by collecting Integrated Development Environment (IDE) events during their
development sessions. Furthermore, we used process and text mining to discovery developers’
workflows and their fingerprints, respectively.
Results. We discovered and modeled with good quality developers’ processes during programming
sessions based on events extracted from their IDEs. We unveiled insights from
coding practices in distinct refactoring tasks, built accurate software complexity forecast models
based only on process metrics and setup a method for characterizing coherently developers’
behaviors. The latter may ultimately lead to the creation of a catalog of software development
process smells.
Conclusions. Our approach is agnostic to programming languages, geographic location or
development practices, making it suitable for challenging contexts such as in modern global
software development projects using either traditional IDEs or sophisticated low/no code platforms.Contexto. Projetos de software modernos requerem a correta alocação de recursos humanos,
técnicos e financeiros. Frequentemente, os gestores de projeto tomam decisões suportadas
apenas na sua própria experiência, intuição ou simplesmente espelhando atividades executadas
por terceiros em contextos similares. As tentativas para evitar tais práticas baseiam-se em
modelos que usam linhas de código, a complexidade ciclomática ou em estimativas de esforço,
sendo estes tradicionalmente suportados por repositórios de software conhecidos por conterem
várias limitações.
Objetivo. Demonstrar a utilidade dos dados de processo e respetivos métodos de análise na
melhoria das práticas de desenvolvimento de software, colocando o foco na análise da eficiência
e revelando aspetos dos processos até então desconhecidos, contribuindo para a criação de
novos modelos no contexto de análises avançadas para o desenvolvimento de software.
Método. Explorámos os fragmentos de processo de vários programadores em três cenários
diferentes, recolhendo eventos durante as suas sessões de desenvolvimento no IDE. Adicionalmente,
usámos métodos de descoberta e análise de processos e texto no sentido de modelar o
fluxo de trabalho dos programadores e as suas caracterÃsticas individuais, respetivamente.
Resultados. Descobrimos e modelámos com boa qualidade os processos dos programadores
durante as suas sessões de trabalho, usando eventos provenientes dos seus IDEs. Revelámos factos
desconhecidos sobre práticas de refabricação, construÃmos modelos de previsão da complexidade
ciclomática usando apenas métricas de processo e criámos um método para caracterizar
coerentemente os comportamentos dos programadores. Este último, pode levar à criação de um
catálogo de boas/más práticas no processo de desenvolvimento de software.
Conclusões. A nossa abordagem é agnóstica em termos de linguagens de programação,
localização geográfica ou prática de desenvolvimento, tornando-a aplicável em contextos complexos
tal como em projetos modernos de desenvolvimento global que utilizam tanto os IDEs
tradicionais como as atuais e sofisticadas plataformas "low/no code"
Geoinformatics in Citizen Science
The book features contributions that report original research in the theoretical, technological, and social aspects of geoinformation methods, as applied to supporting citizen science. Specifically, the book focuses on the technological aspects of the field and their application toward the recruitment of volunteers and the collection, management, and analysis of geotagged information to support volunteer involvement in scientific projects. Internationally renowned research groups share research in three areas: First, the key methods of geoinformatics within citizen science initiatives to support scientists in discovering new knowledge in specific application domains or in performing relevant activities, such as reliable geodata filtering, management, analysis, synthesis, sharing, and visualization; second, the critical aspects of citizen science initiatives that call for emerging or novel approaches of geoinformatics to acquire and handle geoinformation; and third, novel geoinformatics research that could serve in support of citizen science
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B!SON: A Tool for Open Access Journal Recommendation
Finding a suitable open access journal to publish scientific work is a complex task: Researchers have to navigate a constantly growing number of journals, institutional agreements with publishers, funders’ conditions and the risk of Predatory Publishers. To help with these challenges, we introduce a web-based journal recommendation system called B!SON. It is developed based on a systematic requirements analysis, built on open data, gives publisher-independent recommendations and works across domains. It suggests open access journals based on title, abstract and references provided by the user. The recommendation quality has been evaluated using a large test set of 10,000 articles. Development by two German scientific libraries ensures the longevity of the project
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