scholarly journals Data Management of Confidential Data

2013 ◽  
Vol 8 (1) ◽  
pp. 265-278 ◽  
Author(s):  
Carl Lagoze ◽  
William C. Block ◽  
Jeremy Williams ◽  
John Abowd ◽  
Lars Vilhuber
Keyword(s):  
Social Science ◽  
Data Management ◽  
Geospatial Information ◽  
Public And Private ◽  
Genome Data ◽  
External Data ◽  
Use Of Data ◽  
Confidential Data ◽  
Federal Data

Social science researchers increasingly make use of data that is confidential because it contains linkages to the identities of people, corporations, etc. The value of this data lies in the ability to join the identifiable entities with external data, such as genome data, geospatial information, and the like. However, the confidentiality of this data is a barrier to its utility and curation, making it difficult to fulfil US federal data management mandates and interfering with basic scholarly practices, such as validation and reuse of existing results. We describe the complexity of the relationships among data that span a public and private divide. We then describe our work on the CED2AR prototype, a first step in providing researchers with a tool that spans this divide and makes it possible for them to search, access and cite such data.

scholarly journals MANAJEMEN DATA PADA ASEAN YOUTH FRIENDSHIP NETWORK (AYFN): PRAKTEK KERANGKA OPERASIONAL MANAJEMEN DATA DALAM KNOWLEDGE MANAGEMENT

2018 ◽  
Vol 1 (1) ◽  
pp. 16
Author(s):  
Rahmat Fadhli ◽  
Rifqi Zaeni Achmad Syam
Keyword(s):  
Data Management ◽  
Data Storage ◽  
Data Organization ◽  
Friendship Network ◽  
Data Archiving ◽  
Use Of Data ◽  
Confidential Data ◽  
Project Officer ◽  
User Data ◽  
Direct Use

Manajemen Data mencakup semua kegiatan yang berhubungan dengan data selain penggunaan langsung dari data, termasuk organisasi data; back up data; pengarsipan data; berbagi data dan penerbitan; menjamin keamanan data rahasia dan sinkronisasi data. Kegiatan manajemen data adalah suatu kegiatan penting yang dilakukan oleh individu ataupun organisasi terhadap data agar mudah di akses, aman dan tersedia bagi user/ pemakainya. Kegiatan manajemen data di ASEAN Youth Friendship Network dilakukan oleh Project officer karena berkenaan dan berhubungan langsung dalam proses manajerial data, penyimpanan, dan pengolahan data untuk mendapatkan metadata. Proses manajemen data yang dilakukan AYFN terdiri atas lima tahapan yakni perencanaan (planning), pengumpulan (collecting), pengolahan (processing), organisasi data (organizing), penyajian dan penyampaian (presentation). ABSTRACTData Management covers all activities related to data other than direct use of data, including data organization; back up data; data archiving; data sharing and publishing; ensure confidential data security and data synchronization. Data management activities are an important activity carried out by individuals or organizations on data so that they are easy to access, secure and available to the user / user. Data management activities in the ASEAN Youth Friendship Network are carried out by Project officers because they pertain to and relate directly to data managerial processes, data storage and processing to obtain metadata. The data management process carried out by AYFN consists of five stages, namely planning, collecting, processing, data organization, presentation and presentation.

scholarly journals A Multi-Tiered Framework for Insider Threat Prevention

Electronics ◽  
2021 ◽  
Vol 10 (9) ◽  
pp. 1005
Author(s):  
Rakan A. Alsowail ◽  
Taher Al-Shehari
Keyword(s):  
Real World ◽  
Relevant Literature ◽  
Security And Privacy ◽  
Insider Threat ◽  
Unified Framework ◽  
Insider Threats ◽  
Public And Private ◽  
Private Organizations ◽  
Confidential Data ◽  
Real Value

As technologies are rapidly evolving and becoming a crucial part of our lives, security and privacy issues have been increasing significantly. Public and private organizations have highly confidential data, such as bank accounts, military and business secrets, etc. Currently, the competition between organizations is significantly higher than before, which triggers sensitive organizations to spend an excessive volume of their budget to keep their assets secured from potential threats. Insider threats are more dangerous than external ones, as insiders have a legitimate access to their organization’s assets. Thus, previous approaches focused on some individual factors to address insider threat problems (e.g., technical profiling), but a broader integrative perspective is needed. In this paper, we propose a unified framework that incorporates various factors of the insider threat context (technical, psychological, behavioral and cognitive). The framework is based on a multi-tiered approach that encompasses pre, in and post-countermeasures to address insider threats in an all-encompassing perspective. It considers multiple factors that surround the lifespan of insiders’ employment, from the pre-joining of insiders to an organization until after they leave. The framework is utilized on real-world insider threat cases. It is also compared with previous work to highlight how our framework extends and complements the existing frameworks. The real value of our framework is that it brings together the various aspects of insider threat problems based on real-world cases and relevant literature. This can therefore act as a platform for general understanding of insider threat problems, and pave the way to model a holistic insider threat prevention system.

scholarly journals Co-creating value: Student contributions to smart cities

2014 ◽  
pp. 392-409
Keyword(s):  
Action Research ◽  
Disaster Response ◽  
Information Technologies ◽  
Smart Cities ◽  
Participatory Action ◽  
Action Research Project ◽  
Research Project ◽  
Geospatial Information ◽  
Public And Private ◽  
Response And Recovery

Given the interdependence of the public and private sectors and simultaneous and massive impact of widespread disasters on the entire community, this paper investigates the use of information technologies, specifically geospatial information systems, within the multi-organizational community to effectively co-create value during disaster response and recovery efforts. We present and examine in depth a participatory action research project in a disaster-experienced coastal community conducted during the 2006-2014 time period. The results of the action research project and analysis of a survey completed by stakeholders leads to a list of findings, in particular those related to developing a model of next generation learning design where students are co-creators of value to the smart cities.

Using Data Mining for Forecasting Data Management Needs

2008 ◽  
pp. 2088-2104
Author(s):  
Qingyu Zhang ◽  
Richard S. Segall
Keyword(s):  
Data Mining ◽  
Data Management ◽  
Forest Cover ◽  
Human Lung Cancer ◽  
Production Environment ◽  
Data Set ◽  
Biotechnology Research ◽  
Use Of Data ◽  
Using Data ◽  
Tools And Techniques

This chapter illustrates the use of data mining as a computational intelligence methodology for forecasting data management needs. Specifically, this chapter discusses the use of data mining with multidimensional databases for determining data management needs for the selected biotechnology data of forest cover data (63,377 rows and 54 attributes) and human lung cancer data set (12,600 rows of transcript sequences and 156 columns of gene types). The data mining is performed using four selected software of SAS® Enterprise MinerTM, Megaputer PolyAnalyst® 5.0, NeuralWare Predict®, and Bio- Discovery GeneSight®. The analysis and results will be used to enhance the intelligence capabilities of biotechnology research by improving data visualization and forecasting for organizations. The tools and techniques discussed here can be representative of those applicable in a typical manufacturing and production environment. Screen shots of each of the four selected software are presented, as are conclusions and future directions.

What is visual-numeric literacy, and how does it work?

2020 ◽  
Author(s):  
Elise Seip Tønnessen
Keyword(s):  
Social Science ◽  
Upper Secondary School ◽  
Literacy Studies ◽  
Science Classrooms ◽  
New Literacy ◽  
New Literacy Studies ◽  
Use Of Data ◽  
Upper Secondary ◽  
System Variables ◽  
Data Visualizations

This article explores the concept of literacy related to the use of data visualizations. Literacy is here understood as the ability to make sense from semiotic resources in an educational context. Theoretically the discussion is based in social semiotic theory on multimodality in the tradition of New Literacy Studies. Empirical examples are taken from observations in two Social Science classrooms in upper secondary school in Norway, where the students work with publicly available data visualizations to answer tasks designed by their teacher. The discussion sums up factors that affect reading and learning from such complex resources: taking time to explore axis system, variables, and digitally available options; questioning data; and contextualizing results.

scholarly journals Intelligent Data Management and Security in Cloud Computing

Sensors ◽  
2020 ◽  
Vol 20 (12) ◽  
pp. 3458
Author(s):  
Lidia Ogiela ◽  
Marek R. Ogiela ◽  
Hoon Ko
Keyword(s):  
Data Management ◽  
Data Sharing ◽  
Service Management ◽  
Secret Data ◽  
Data Services ◽  
New Class ◽  
Management Processes ◽  
Confidential Data ◽  
Shared Secret ◽  
Linguistic Methods

This paper will present the authors’ own techniques of secret data management and protection, with particular attention paid to techniques securing data services. Among the solutions discussed, there will be information-sharing protocols dedicated to the tasks of secret (confidential) data sharing. Such solutions will be presented in an algorithmic form, aimed at solving the tasks of protecting and securing data against unauthorized acquisition. Data-sharing protocols will execute the tasks of securing a special type of information, i.e., data services. The area of data protection will be defined for various levels, within which will be executed the tasks of data management and protection. The authors’ solution concerning securing data with the use of cryptographic threshold techniques used to split the secret among a specified group of secret trustees, simultaneously enhanced by the application of linguistic methods of description of the shared secret, forms a new class of protocols, i.e., intelligent linguistic threshold schemes. The solutions presented in this paper referring to the service management and securing will be dedicated to various levels of data management. These levels could be differentiated both in the structure of a given entity and in its environment. There is a special example thereof, i.e., the cloud management processes. These will also be subject to the assessment of feasibility of application of the discussed protocols in these areas. Presented solutions will be based on the application of an innovative approach, in which we can use a special formal graph for the creation of a secret representation, which can then be divided and transmitted over a distributed network.

scholarly journals Advancing Post-Genome Data and System Integration through Machine Learning

2002 ◽  
Vol 3 (1) ◽  
pp. 28-31 ◽  
Author(s):  
Francisco Azuaje
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
System Integration ◽  
Intelligent Systems ◽  
Biological Data ◽  
Markup Languages ◽  
Public And Private ◽  
Genome Data ◽  
The Creation ◽  
Biological Data Integration

Research on biological data integration has traditionally focused on the development of systems for the maintenance and interconnection of databases. In the next few years, public and private biotechnology organisations will expand their actions to promote the creation of a post-genome semantic web. It has commonly been accepted that artificial intelligence and data mining techniques may support the interpretation of huge amounts of integrated data. But at the same time, these research disciplines are contributing to the creation of content markup languages and sophisticated programs able to exploit the constraints and preferences of user domains. This paper discusses a number of issues on intelligent systems for the integration of bioinformatic resources.

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