Education, Research, Information Systems and the North, edited by W. Peter Adams

ARCTIC ◽  
1988 ◽  
Vol 41 (4) ◽  
Author(s):  
Arthur G. McBeath
Keyword(s):  
Education Research ◽  
Information Systems ◽  
Research Information ◽  
The North

Education, Research, Information Systems and the North

1988 ◽  
Vol 20 (1) ◽  
pp. 128
Author(s):  
Martha Andrews ◽  
W. Peter Adams ◽  
Peter Adams
Keyword(s):  
Education Research ◽  
Information Systems ◽  
Research Information ◽  
The North

An Iterative Data Cleansing and Migration Framework for Research Information Systems

2021 ◽  
Author(s):  
Baumgart Matthias ◽  
Romer Lisa ◽  
Luhr Matthias ◽  
Roschke Christian ◽  
Ritter Marc ◽  
...  
Keyword(s):  
Information Systems ◽  
Research Information ◽  
Data Cleansing ◽  
And Migration

scholarly journals Enhanced model for ergonomic evaluation of information systems: application to scientific research information system

2019 ◽  
Vol 9 (1) ◽  
pp. 683
Author(s):  
Khaoula Benmoussa ◽  
Majida Laaziri ◽  
Samira Khoulji ◽  
Kerkeb Mohamed Larbi ◽  
Abir El Yamami
Keyword(s):  
Information System ◽  
Information Systems ◽  
Hybrid Model ◽  
Human Factor ◽  
Scientific Research ◽  
Research Information ◽  
Computing Systems ◽  
Research Information System ◽  
Ergonomic Evaluation

<p><span lang="EN-US">Considering the importance of the ergonomic aspect for information systems in providing an easy use of the computing systems, this paper focuses on the elaboration of a hybrid model for the ergonomic evaluation of information systems that merges a set of inspection dimensions such as accessibility, practicality, emotionality, and technological persuasion. Details on how the model has been constructed and data have been collected are presented. For the evaluation of our model, a situation of an information system for scientific research (SIMArech) in Moroccan Universities has been studied. This model can be used by ergonomist and human factor professionals. It is found that the proposed heuristics can effectively assess the most important dimensions of scientific research information systems.</span></p>

scholarly journals Numerical Modeling for Gully Erosion in the North of Algeria based on Data of Remote Sensing and Geographic Information Systems

2017 ◽  
Vol 25 (1) ◽  
pp. 37-63
Author(s):  
mohammad abbas daoudi mohammad abbas daoudi
Keyword(s):  
Remote Sensing ◽  
Multivariate Analysis ◽  
Information Systems ◽  
Geographical Information Systems ◽  
Univariate Analysis ◽  
Probabilistic Approach ◽  
Geographical Information ◽  
Rainfall Erosivity ◽  
Erosion Risk ◽  
The North

The problems of soil erosion are largely widespread in the countries of the Mediterranean basin. The process of gullying is a complex phenomenon with disastrous consequences. It particularly affects northern Algeria, decreasing the potentialities of the water tanks, reducing cultivable lands availability and degrading infrastructures. Therefore, this work studies the analysis and the prediction of gullying erosion by using a probabilistic approach based on multisource data. The objective of this search is to answer to the three following questions: i) which factors support the process of gullying ? ii) how does a process of gullying develop? iii) which are the zones favourable to gullying ? Works are undertaken on the catchment area of the Isser River. We focused the applications on the upstream part of the basin. In this research, we study a North-South transect which corresponds to three under-basins slopes. The choice of these tests areas answers to four criteria defined in our method: the representativeness, the homogeneity, the availability of former data and, finally, the accessibility. After the completion of the multisource data, modelling and multivariate analysis for the prediction of gullying. The combination factor-process by the univariate analysis allows on the one hand, to highlight the variables controlling the process of gullying, and on the other hand, to analyse the variables on a hierarchical basis and to know their degree of influence. The multivariate analysis, by the logistic regression model (LRM), enabled us to select the significant variables and to locate the most favourable zones for the process of gullying. The validation of the models is evaluated using the curves of lift spin. The results suggest that the factors highlighted by the model to be most influential on gullying erosion are: the lithology, the slope, the morphopedology, the rainfall erosivity and the land cover. The synthesis of this approach is illustrated in the form of charts of gullying erosion risk maps in four classes of probability. The assessment of the study shows the fundamental interest of this approach using geographical information systems and remote sensing, in particular for the watersheds of the southern Mediterranean, with the possibility of extending this methodology to other regions.

Understanding Cloud Computing in a Higher Education Context

2018 ◽  
pp. 1153-1163
Author(s):  
Lucy Self ◽  
Petros Chamakiotis
Keyword(s):  
Higher Education ◽  
Cloud Computing ◽  
Education Research ◽  
Information Systems ◽  
Thematic Analysis ◽  
Methodological Approach ◽  
Higher Education Research ◽  
Qualitative Thematic Analysis ◽  
It Department ◽  
Fortune 100

Cloud computing has become prevalent in many sectors today, including higher-education. The study is premised on the assumption that despite the popularity of cloud computing in higher education, research within this context remains limited. The study, which is qualitative and exploratory in nature, involved an innovative methodological approach, drawing on interviews with three groups of participants: (a) members of a global, Fortune 100 technology company supplying cloud solutions; (b) members of a selected UK university's IT department implementing cloud solutions; and (c) students from the same UK university using cloud solutions. The findings improve understanding around cloud solutions in the higher education context by unpacking—through a qualitative thematic analysis approach—relevant themes that inform the extant information systems literature. Finally, the study provides recommendations for future researchers, cloud suppliers, universities, and students.

scholarly journals Enabling decisions that make a difference: guidance for improving access to and analysis of invasive species information

2019 ◽  
Vol 22 (1) ◽  
pp. 37-45 ◽  
Author(s):  
Rebekah D. Wallace ◽  
Charles T. Bargeron ◽  
Jamie K. Reaser
Keyword(s):  
Invasive Species ◽  
Information Systems ◽  
Information Sharing ◽  
Data Sharing ◽  
Relevant Information ◽  
Global Biodiversity Information Facility ◽  
Management Options ◽  
The North ◽  
Socio Economic Impact ◽  
Taxonomic Groups

AbstractThe issue of how to detect and rapidly respond to invasive species before it is economically infeasible to control them is one of urgency and importance at international, national, and subnational scales. Barriers to sharing invasive species data—whether in the form of policy, culture, technology, or operational logistics—need to be addressed and overcome at all levels. We propose guiding principles for following standards, formats, and protocols to improve information sharing among US invasive species information systems and conclude that existing invasive species information standards are adequate for the facilitation of data sharing among all sectors. Rather than creating a single information-sharing system, there is a need to promote interfaces among existing information systems that will enable them to become inter-operable, to foster simultaneous access, and to deliver any and all relevant information to a particular user or application in a seamless fashion. The actions we propose include implementing a national campaign to mobilize invasive species occurrence data into publicly available information systems; maintaining a current list of invasive species data integrators/clearinghouses; establishing an agreement for sharing data among the primary US invasive species information systems; enhancing the Integrated Taxonomic Information System to fully cover taxonomic groups not yet complete; further developing and hosting data standards for critical aspects of invasive species biology; supporting and maintaining the North American Invasive Species Management Association’s mapping standards; identifying standard metrics for capturing the environmental and socio-economic impact of invasive species, including impacts and management options; continuing to support US engagement in international invasive species data sharing platforms; and continuing US membership in the Global Biodiversity Information Facility.

scholarly journals Influence of Information Quality via Implemented German RCD Standard in Research Information Systems

Data ◽  
2020 ◽  
Vol 5 (2) ◽  
pp. 30
Author(s):  
Otmane Azeroual ◽  
Joachim Schöpfel ◽  
Dragan Ivanovic
Keyword(s):  
Information Systems ◽  
Data Quality ◽  
Information Quality ◽  
Research Performance ◽  
Data Sources ◽  
Steady Increase ◽  
Research Information ◽  
External Data ◽  
Core Dataset ◽  
The Impact

With the steady increase in the number of data sources to be stored and processed by higher education and research institutions, it has become necessary to develop Research Information Systems, which will store this research information in the long term and make it accessible for further use, such as reporting and evaluation processes, institutional decision making and the presentation of research performance. In order to retain control while integrating research information from heterogeneous internal and external data sources and disparate interfaces into RIS and to maximize the benefits of the research information, ensuring data quality in RIS is critical. To facilitate a common understanding of the research information collected and to harmonize data collection processes, various standardization initiatives have emerged in recent decades. These standards support the use of research information in RIS and enable compatibility and interoperability between different information systems. This paper examines the process of securing data quality in RIS and the impact of research information standards on data quality in RIS. We focus on the recently developed German Research Core Dataset standard as a case of application.

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