Este estudo analisou as relações entre diretrizes e práticas do repositório institucional universitário de dados de pesquisa Edinburgh DataShare, no contexto do gerenciamento de dados de pesquisa, baseando-se nas seguintes categorias: responsabilidade, conteúdo, aspectos legais, padrões, preservação digital, política de acesso e uso e sustentabilidade e financiamento. A metodologia foi um estudo de caso qualitativo com levantamento de documentos e dados na Internet e observação direta do repositório. Utilizou o software NVivo para registro e análise dos dados. Nas características do Edinburgh DataShare quanto à responsabilidade, há a presença de profissionais de tecnologia da informação (TI) e profissionais da informação (com destaque para bibliotecários) na equipe. Sobre o conteúdo, foram examinados os metadados de 161 itens recuperados em 09 de outubro de 2014. Como o repositório inicialmente foi povoado através de um projeto piloto, a maioria dos itens (103 itens) foi criada por um mesmo pesquisador, Bert Remijsen, da área de assunto de Linguística e Idioma Inglês (Linguistics and English Language). Com relação aos aspectos legais, a adoção de licenças abertas é uma opção que o Edinburgh DataShare oferece, com a licença ODC-BY, mas também há a opção de não escolher essa licença e indicar licenças diferentes ou outras informações relativas a copyright no metadado dc.rights. Sobre os padrões, o software utilizado é o DSpace, que permite a interoperabilidade com outros sistemas internos e externos à Universidade. O uso de um perfil de aplicação do padrão Dublin Core qualificado, específico para conjunto de dados de pesquisa, facilita a recuperação da informação e a interoperabilidade com outros sistemas, por usar um padrão reconhecido mundialmente. O fluxo de depósito documentado e disponível na Internet e a inserção no fluxo de gerenciamento de dados de pesquisa da Universidade trazem segurança e estabilidade para os serviços do repositório. Há uma política de preservação digital do repositório que norteia as ações de preservação. Somente o Handle era utilizado como identificador permanente até o início de novembro de 2014, e a partir desse momento, passou a ser incluído também o DOI. Sobre o acesso e uso, o depósito é efetuado por pessoas vinculadas à Universidade, de dados de pesquisa da Universidade, e o acesso aos metadados e à maioria dos materiais é livre para todos, sem necessidade de identificação. A recuperação da informação está em desenvolvimento e em fevereiro de 2015 uma nova forma de pesquisa foi disponibilizada, ampliando as possibilidades de acesso, compartilhamento e uso dos conjuntos de dados de pesquisa, potencializando o alcance dos objetivos do Edinburgh DataShare. Com relação à sustentabilidade e ao financiamento, poucas informações foram recuperadas, porém ficou evidente, por seu início ter sido por um projeto financiado dentro do Jisc Repositories and Preservation Programme e por ter sido incluído em uma estrutura da Universidade, que é um projeto que exige um grande investimento e que necessita de apoio institucional para assegurar sua continuidade. O Edinburgh DataShare é uma parte essencial do gerenciamento de dados de pesquisa da Universidade, mas não é o único mecanismo de curadoria digital utilizado pela Universidade. O Edinburgh DataShare está cumprindo a tarefa de complementar o ciclo da comunicação científica e proporcionar as condições de criação das chamadas publicações ampliadas ao oferecer os serviços que permitem que os pesquisadores vinculem seus dados de pesquisa às suas publicações através de identificadores permanentes. Apresentando as relações entre as diretrizes e as práticas do Edinburgh DataShare, no contexto do gerenciamento de dados de pesquisa, foi possível perceber uma relação de construção contínua das diretrizes e das práticas. Essa forma de construção traz como conseqüência algumas diferenças observadas entre as diretrizes e as práticas, visto que nem sempre elas estão no mesmo momento de maturidade. / This study examined the relationship between policies and practices of the university research data institutional repository Edinburgh DataShare in the context of the management of research data, based on the following categories: responsibility, content, legal aspects, standards, digital preservation, policy access and use, and sustainability and financing. The methodology was a qualitative case study of survey documents and data on the Internet and direct observation of the repository. It used NVivo software for recording and data analysis. The characteristics of Edinburgh DataShare for accountability, there is the presence of information technology (IT) professionals and information professionals (especially librarians) in the team. On content, metadata 161 items recovered on 09 October 2014 were examined since the repository was initially populated by a pilot project, most of the items (103 items) was created by the same investigator, Bert Remijsen, of subject area of Linguistics and English Language (Linguistics and Language Inglês). Regarding the legal aspects, the adoption of open licenses is an option that Edinburgh DataShare offers, with the ODC-BY license, but there is also the option of not choosing the license and indicate different licenses or other information concerning copyright metadata in dc .rights. About the standards, the software used is DSpace, which enables interoperability with other internal and external systems to the University. The use of a standard application profile Qualified Dublin Core, for specific set of research data, facilitates the retrieval of information and interoperability with other systems, by using a standard recognized worldwide. The deposit flow documented and available on the Internet and the inclusion in the University's research data management workflow bring security and stability to the services repository. There is a digital preservation policy repository that guides the preservation actions. Only Handle was used as a permanent identifier to the beginning of November 2014, and from that moment, became also included the DOI. On access and use, the deposit is made by people linked to the University, research data from the University, and access to metadata and to most materials is free for all, without identification. Information retrieval is under development; in February 2015 a new form of research was available, expanding the possibilities of access, sharing and use of sets of research data, increasing the scope of the objectives of Edinburgh DataShare. With regard to sustainability and financing, little information was retrieved, but it was evident, by the beginning was a project funded by JISC Repositories and within the Preservation Programme and have been included in a structure of the University, which is a project that requires a big investment and requires institutional support to ensure its continuity. Edinburgh DataShare is an essential part of the University research data management, but is not the only digital curation mechanism used by the University. Edinburgh DataShare is fulfilling additional task the cycle of scientific communication and provide the conditions for the creation of so-called extended publications by providing services that enable researchers to bind your search data to their publications through permanent identifiers. Introducing the relationship between the guidelines and the Edinburgh DataShare practices in the context of research data management, it was possible to see a continuous relationship building guidelines and practices. This form of construction brings as a consequence some differences between the guidelines and practices, as they are not always at the same time of maturity.

Este estudo analisou as relações entre diretrizes e práticas do repositório institucional universitário de dados de pesquisa Edinburgh DataShare, no contexto do gerenciamento de dados de pesquisa, baseando-se nas seguintes categorias: responsabilidade, conteúdo, aspectos legais, padrões, preservação digital, política de acesso e uso e sustentabilidade e financiamento. A metodologia foi um estudo de caso qualitativo com levantamento de documentos e dados na Internet e observação direta do repositório. Utilizou o software NVivo para registro e análise dos dados. Nas características do Edinburgh DataShare quanto à responsabilidade, há a presença de profissionais de tecnologia da informação (TI) e profissionais da informação (com destaque para bibliotecários) na equipe. Sobre o conteúdo, foram examinados os metadados de 161 itens recuperados em 09 de outubro de 2014. Como o repositório inicialmente foi povoado através de um projeto piloto, a maioria dos itens (103 itens) foi criada por um mesmo pesquisador, Bert Remijsen, da área de assunto de Linguística e Idioma Inglês (Linguistics and English Language). Com relação aos aspectos legais, a adoção de licenças abertas é uma opção que o Edinburgh DataShare oferece, com a licença ODC-BY, mas também há a opção de não escolher essa licença e indicar licenças diferentes ou outras informações relativas a copyright no metadado dc.rights. Sobre os padrões, o software utilizado é o DSpace, que permite a interoperabilidade com outros sistemas internos e externos à Universidade. O uso de um perfil de aplicação do padrão Dublin Core qualificado, específico para conjunto de dados de pesquisa, facilita a recuperação da informação e a interoperabilidade com outros sistemas, por usar um padrão reconhecido mundialmente. O fluxo de depósito documentado e disponível na Internet e a inserção no fluxo de gerenciamento de dados de pesquisa da Universidade trazem segurança e estabilidade para os serviços do repositório. Há uma política de preservação digital do repositório que norteia as ações de preservação. Somente o Handle era utilizado como identificador permanente até o início de novembro de 2014, e a partir desse momento, passou a ser incluído também o DOI. Sobre o acesso e uso, o depósito é efetuado por pessoas vinculadas à Universidade, de dados de pesquisa da Universidade, e o acesso aos metadados e à maioria dos materiais é livre para todos, sem necessidade de identificação. A recuperação da informação está em desenvolvimento e em fevereiro de 2015 uma nova forma de pesquisa foi disponibilizada, ampliando as possibilidades de acesso, compartilhamento e uso dos conjuntos de dados de pesquisa, potencializando o alcance dos objetivos do Edinburgh DataShare. Com relação à sustentabilidade e ao financiamento, poucas informações foram recuperadas, porém ficou evidente, por seu início ter sido por um projeto financiado dentro do Jisc Repositories and Preservation Programme e por ter sido incluído em uma estrutura da Universidade, que é um projeto que exige um grande investimento e que necessita de apoio institucional para assegurar sua continuidade. O Edinburgh DataShare é uma parte essencial do gerenciamento de dados de pesquisa da Universidade, mas não é o único mecanismo de curadoria digital utilizado pela Universidade. O Edinburgh DataShare está cumprindo a tarefa de complementar o ciclo da comunicação científica e proporcionar as condições de criação das chamadas publicações ampliadas ao oferecer os serviços que permitem que os pesquisadores vinculem seus dados de pesquisa às suas publicações através de identificadores permanentes. Apresentando as relações entre as diretrizes e as práticas do Edinburgh DataShare, no contexto do gerenciamento de dados de pesquisa, foi possível perceber uma relação de construção contínua das diretrizes e das práticas. Essa forma de construção traz como conseqüência algumas diferenças observadas entre as diretrizes e as práticas, visto que nem sempre elas estão no mesmo momento de maturidade. / This study examined the relationship between policies and practices of the university research data institutional repository Edinburgh DataShare in the context of the management of research data, based on the following categories: responsibility, content, legal aspects, standards, digital preservation, policy access and use, and sustainability and financing. The methodology was a qualitative case study of survey documents and data on the Internet and direct observation of the repository. It used NVivo software for recording and data analysis. The characteristics of Edinburgh DataShare for accountability, there is the presence of information technology (IT) professionals and information professionals (especially librarians) in the team. On content, metadata 161 items recovered on 09 October 2014 were examined since the repository was initially populated by a pilot project, most of the items (103 items) was created by the same investigator, Bert Remijsen, of subject area of Linguistics and English Language (Linguistics and Language Inglês). Regarding the legal aspects, the adoption of open licenses is an option that Edinburgh DataShare offers, with the ODC-BY license, but there is also the option of not choosing the license and indicate different licenses or other information concerning copyright metadata in dc .rights. About the standards, the software used is DSpace, which enables interoperability with other internal and external systems to the University. The use of a standard application profile Qualified Dublin Core, for specific set of research data, facilitates the retrieval of information and interoperability with other systems, by using a standard recognized worldwide. The deposit flow documented and available on the Internet and the inclusion in the University's research data management workflow bring security and stability to the services repository. There is a digital preservation policy repository that guides the preservation actions. Only Handle was used as a permanent identifier to the beginning of November 2014, and from that moment, became also included the DOI. On access and use, the deposit is made by people linked to the University, research data from the University, and access to metadata and to most materials is free for all, without identification. Information retrieval is under development; in February 2015 a new form of research was available, expanding the possibilities of access, sharing and use of sets of research data, increasing the scope of the objectives of Edinburgh DataShare. With regard to sustainability and financing, little information was retrieved, but it was evident, by the beginning was a project funded by JISC Repositories and within the Preservation Programme and have been included in a structure of the University, which is a project that requires a big investment and requires institutional support to ensure its continuity. Edinburgh DataShare is an essential part of the University research data management, but is not the only digital curation mechanism used by the University. Edinburgh DataShare is fulfilling additional task the cycle of scientific communication and provide the conditions for the creation of so-called extended publications by providing services that enable researchers to bind your search data to their publications through permanent identifiers. Introducing the relationship between the guidelines and the Edinburgh DataShare practices in the context of research data management, it was possible to see a continuous relationship building guidelines and practices. This form of construction brings as a consequence some differences between the guidelines and practices, as they are not always at the same time of maturity.

Este estudo analisou as relações entre diretrizes e práticas do repositório institucional universitário de dados de pesquisa Edinburgh DataShare, no contexto do gerenciamento de dados de pesquisa, baseando-se nas seguintes categorias: responsabilidade, conteúdo, aspectos legais, padrões, preservação digital, política de acesso e uso e sustentabilidade e financiamento. A metodologia foi um estudo de caso qualitativo com levantamento de documentos e dados na Internet e observação direta do repositório. Utilizou o software NVivo para registro e análise dos dados. Nas características do Edinburgh DataShare quanto à responsabilidade, há a presença de profissionais de tecnologia da informação (TI) e profissionais da informação (com destaque para bibliotecários) na equipe. Sobre o conteúdo, foram examinados os metadados de 161 itens recuperados em 09 de outubro de 2014. Como o repositório inicialmente foi povoado através de um projeto piloto, a maioria dos itens (103 itens) foi criada por um mesmo pesquisador, Bert Remijsen, da área de assunto de Linguística e Idioma Inglês (Linguistics and English Language). Com relação aos aspectos legais, a adoção de licenças abertas é uma opção que o Edinburgh DataShare oferece, com a licença ODC-BY, mas também há a opção de não escolher essa licença e indicar licenças diferentes ou outras informações relativas a copyright no metadado dc.rights. Sobre os padrões, o software utilizado é o DSpace, que permite a interoperabilidade com outros sistemas internos e externos à Universidade. O uso de um perfil de aplicação do padrão Dublin Core qualificado, específico para conjunto de dados de pesquisa, facilita a recuperação da informação e a interoperabilidade com outros sistemas, por usar um padrão reconhecido mundialmente. O fluxo de depósito documentado e disponível na Internet e a inserção no fluxo de gerenciamento de dados de pesquisa da Universidade trazem segurança e estabilidade para os serviços do repositório. Há uma política de preservação digital do repositório que norteia as ações de preservação. Somente o Handle era utilizado como identificador permanente até o início de novembro de 2014, e a partir desse momento, passou a ser incluído também o DOI. Sobre o acesso e uso, o depósito é efetuado por pessoas vinculadas à Universidade, de dados de pesquisa da Universidade, e o acesso aos metadados e à maioria dos materiais é livre para todos, sem necessidade de identificação. A recuperação da informação está em desenvolvimento e em fevereiro de 2015 uma nova forma de pesquisa foi disponibilizada, ampliando as possibilidades de acesso, compartilhamento e uso dos conjuntos de dados de pesquisa, potencializando o alcance dos objetivos do Edinburgh DataShare. Com relação à sustentabilidade e ao financiamento, poucas informações foram recuperadas, porém ficou evidente, por seu início ter sido por um projeto financiado dentro do Jisc Repositories and Preservation Programme e por ter sido incluído em uma estrutura da Universidade, que é um projeto que exige um grande investimento e que necessita de apoio institucional para assegurar sua continuidade. O Edinburgh DataShare é uma parte essencial do gerenciamento de dados de pesquisa da Universidade, mas não é o único mecanismo de curadoria digital utilizado pela Universidade. O Edinburgh DataShare está cumprindo a tarefa de complementar o ciclo da comunicação científica e proporcionar as condições de criação das chamadas publicações ampliadas ao oferecer os serviços que permitem que os pesquisadores vinculem seus dados de pesquisa às suas publicações através de identificadores permanentes. Apresentando as relações entre as diretrizes e as práticas do Edinburgh DataShare, no contexto do gerenciamento de dados de pesquisa, foi possível perceber uma relação de construção contínua das diretrizes e das práticas. Essa forma de construção traz como conseqüência algumas diferenças observadas entre as diretrizes e as práticas, visto que nem sempre elas estão no mesmo momento de maturidade. / This study examined the relationship between policies and practices of the university research data institutional repository Edinburgh DataShare in the context of the management of research data, based on the following categories: responsibility, content, legal aspects, standards, digital preservation, policy access and use, and sustainability and financing. The methodology was a qualitative case study of survey documents and data on the Internet and direct observation of the repository. It used NVivo software for recording and data analysis. The characteristics of Edinburgh DataShare for accountability, there is the presence of information technology (IT) professionals and information professionals (especially librarians) in the team. On content, metadata 161 items recovered on 09 October 2014 were examined since the repository was initially populated by a pilot project, most of the items (103 items) was created by the same investigator, Bert Remijsen, of subject area of Linguistics and English Language (Linguistics and Language Inglês). Regarding the legal aspects, the adoption of open licenses is an option that Edinburgh DataShare offers, with the ODC-BY license, but there is also the option of not choosing the license and indicate different licenses or other information concerning copyright metadata in dc .rights. About the standards, the software used is DSpace, which enables interoperability with other internal and external systems to the University. The use of a standard application profile Qualified Dublin Core, for specific set of research data, facilitates the retrieval of information and interoperability with other systems, by using a standard recognized worldwide. The deposit flow documented and available on the Internet and the inclusion in the University's research data management workflow bring security and stability to the services repository. There is a digital preservation policy repository that guides the preservation actions. Only Handle was used as a permanent identifier to the beginning of November 2014, and from that moment, became also included the DOI. On access and use, the deposit is made by people linked to the University, research data from the University, and access to metadata and to most materials is free for all, without identification. Information retrieval is under development; in February 2015 a new form of research was available, expanding the possibilities of access, sharing and use of sets of research data, increasing the scope of the objectives of Edinburgh DataShare. With regard to sustainability and financing, little information was retrieved, but it was evident, by the beginning was a project funded by JISC Repositories and within the Preservation Programme and have been included in a structure of the University, which is a project that requires a big investment and requires institutional support to ensure its continuity. Edinburgh DataShare is an essential part of the University research data management, but is not the only digital curation mechanism used by the University. Edinburgh DataShare is fulfilling additional task the cycle of scientific communication and provide the conditions for the creation of so-called extended publications by providing services that enable researchers to bind your search data to their publications through permanent identifiers. Introducing the relationship between the guidelines and the Edinburgh DataShare practices in the context of research data management, it was possible to see a continuous relationship building guidelines and practices. This form of construction brings as a consequence some differences between the guidelines and practices, as they are not always at the same time of maturity.

Management of research data is globally being seen as part of good research practice. As a result of this, funders are increasingly insisting on proof of good research data management (RDM) practices when funding proposals are submitted. This study aimed at establishing the data management practices of emerging researchers at the Council for Scientific and Industrial Research (CSIR), South Africa. With no official RDM procedures currently being implemented at the CSIR, it was hoped that by gaining information about the RDM practices of emerging CSIR researchers, as well as insight into the RDM challenges experienced by them, this researcher would be able to put forward recommendations enabling the establishing of an RDM regime at the CSIR. The study aimed at answering several research questions. The main research question was: How can an organisation like the CSIR ensure that future researchers apply best practices when managing the CSIR’s research data? Five research sub-questions were identified: 1. What are the international RDM requirements, standards, best practices and expectations that are being developed? 2. What data practices need more formalised support: at CSIR, nationally, internationally? 3. What data are collected and held by emerging researchers in the CSIR? 4. What are the current RDM practices and themes among emerging researchers in the CSIR? 5. What are the RDM-related challenges, issues and concerns facing emerging researchers at the CSIR? A total of 48 emerging researchers from the Council for Scientific and Industrial Research (CSIR), South Africa completed an online survey investigating their RDM practices. RDM practices investigated included the use of data management plans, data storage and backup locations, creation of metadata, metadata standard adherence, and data sharing practices. Challenges faced when managing research data, as well as RDM needs and requirements, also formed part of the survey. Results of the online questionnaire revealed that the RDM practices of the group studied do not show to differ significantly from experienced CSIR researchers, or from researchers studied elsewhere on the globe. Findings enabled this researcher to put forward several recommendations which would assist in the implementing of a formalised RDM structure at the CSIR. Recommendations addressed, but were not limited to: formalization of RDM procedures, RDM marketing, and RDM training. / Dissertation (MIS)--University of Pretoria, 2016. / Information Science / MIS / Unrestricted

Conferencia realizada en el marco de la "III Conferencia Latinoamericana de Analíticas de Aprendizaje LALA2020 Project", del 1 al 2 de Octubre de 2020 en Cuenca, Ecuador. / The aim of this paper is to investigate the perceptions of learning analytics re-searchers in Peru about the barriers to publication of their research data. A review of the relevant legislation was done. Semi-structured interviews were used as a research method, the focus being on the presumed conflict between the publica-tion of research data and the protection of personal data. The results show a range of individual factors that influence the behaviour of scientists in relation to the publication of research data, emphasizing the barriers related to data protection in different disciplines.

This dissertation addresses data manipulation in collaborative research systems, including what data should be stored, the operations to be performed on that data, and a programming interface to effect this manipulation. Collaborative research systems are discussed, and requirements for next-generation systems are specified, incorporating a range of emerging technologies including multimedia storage and presentation, expert systems, and object-oriented database management systems. A detailed description of a generic query processor constructed specifically for one collaborative research system is given, and its applicability to next-generation systems and emerging technologies is examined. Chapter 1 discusses the Arizona Analyst Information System (AAIS), a successful collaborative research system being used at the University of Arizona and elsewhere. Chapter 2 describes the generic query processing approach used in the AAIS, as an efficient, nonprocedural, high-level programmer interface to databases. Chapter 3 specifies requirements for next-generation collaborative research systems that encompass the entire research cycle for groups of individuals working on related topics over time. These requirements are being used to build a next-generation collaborative research system at the University of Arizona called CARAT, for Computer Assisted Research and Analysis Tool. Chapter 4 addresses the underlying data management systems in terms of the requirements specified in Chapter 3. Chapter 5 revisits the generic query processing approach used in the AAIS, in light of the requirements of Chapter 3, and the range of data management solutions described in Chapter 4. Chapter 5 demonstrates the generic query processing approach as a viable one, for both the requirements of Chapter 3 and the DBMSs of Chapter 4. The significance of this research takes several forms. First, Chapters 1 and 3 provide detailed views of a current collaborative research system, and of a set of requirements for next-generation systems based on years of experience both using and building the AAIS. Second, the generic query processor described in Chapters 2 and 5 is shown to be an effective, portable programming language to database interface, ranging across the set of requirements for collaborative research systems as well as a number of underlying data management solutions.

Wu Yuen-Ting. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2005. / Includes bibliographical references (leaves 88-90). / Abstracts in English and Chinese. / Chapter 1. --- Introduction --- p.1 / Chapter 1.1 --- Background --- p.1 / Chapter 1.2 --- Research Objective --- p.4 / Chapter 1.3 --- Contribution --- p.5 / Chapter 1.4 --- Structure of this thesis --- p.6 / Chapter 2. --- Literature Review --- p.7 / Chapter 2.1 --- Genetic Algorithms --- p.7 / Chapter 2.1.1 --- Pre-processing step --- p.8 / Chapter 2.1.2 --- Generation of initial population --- p.10 / Chapter 2.1.3 --- Crossover --- p.11 / Chapter 2.1.4 --- Mutation --- p.12 / Chapter 2.1.5 --- Selection --- p.12 / Chapter 2.1.6 --- Results of GA on Container Loading Algorithm --- p.13 / Chapter 2.2 --- Layering Approach --- p.13 / Chapter 2.3 --- Mixed Integer Programming --- p.14 / Chapter 2.4 --- Tabu Search Algorithm --- p.15 / Chapter 2.5 --- Other approaches --- p.16 / Chapter 2.5.1 --- Block arrangement --- p.17 / Chapter 2.5.2 --- Multi-Directional Building Growing algorithm --- p.17 / Chapter 2.6 --- Comparisons of different container loading algorithms --- p.18 / Chapter 3. --- Principle of LFF Algorithm --- p.8 / Chapter 3.1 --- Definition of Flexibility --- p.8 / Chapter 3.2 --- The Less Flexibility First Principle (LFFP) --- p.23 / Chapter 3.3 --- The 2D LFF Algorithm --- p.25 / Chapter 3.3.1 --- Generation of Corner-Occupying Packing Move (COPM) --- p.26 / Chapter 3.3.2 --- Pseudo-packing and the Greedy Approach --- p.27 / Chapter 3.3.3 --- Real-packing --- p.30 / Chapter 3.4 --- Achievement of 2D LFF --- p.31 / Chapter 4. --- Error Bound Analysis on 2D LFF --- p.21 / Chapter 4.1 --- Definition of Error Bound --- p.21 / Chapter 4.2 --- Cause and Analysis on Unsatisfactory Results by LFF --- p.33 / Chapter 4.3 --- Formal Proof on Error Bound --- p.39 / Chapter 5. --- LFF for Container Loading Problem --- p.33 / Chapter 5.1 --- Problem Formulation and Term Definitions --- p.48 / Chapter 5.2 --- Possible Problems to be solved --- p.53 / Chapter 5.3 --- Implementation in Container Loading --- p.54 / Chapter 5.3.1 --- The Basic Algorithm --- p.56 / Chapter 5.4 --- A Sample Packing Scenario --- p.62 / Chapter 5.4.1 --- Generation of COPM list --- p.63 / Chapter 5.4.2 --- Pseudo-packing and the greedy approach --- p.66 / Chapter 5.4.3 --- Update of corner list --- p.69 / Chapter 5.4.4 --- Real-Packing --- p.70 / Chapter 5.5 --- Ratio Approach: A Modification to LFF --- p.70 / Chapter 5.6 --- LFF with Tightness Measure: CPU time Cut-down --- p.75 / Chapter 5.7 --- Experimental Results --- p.77 / Chapter 5.7.1 --- Comparison between LFF and LFFR --- p.77 / Chapter 5.7.2 --- "Comparison between LFFR, LFFT and other algorithms" --- p.78 / Chapter 5.7.3 --- Computational Time for different algorithms --- p.81 / Chapter 5.7.4 --- Conclusion of the experimental results --- p.83 / Chapter 6. --- Conclusion --- p.85 / Bibiography --- p.88

無線通信和移動技術已經從根本上改變了人和人之間相互通信的方式，隨著像智能手機這樣功能強大的移動設備不斷普及，現在我們有更多的機會去監測用戶的運動狀態、社交情況和地理位置等信息。近期，越來越多的基於智能手機的傳感研究相繼出現，這些研究利用智能手機中的多種傳感、定位以及近距離無線設備來識別手機用戶當前的活動狀態和周圍環境。一些可識別用戶活動狀態和監控身體健康狀況的移動應用程式已經被開發并投入使用。儘管如此，當前大部份關於智能手機的研究忽視了這樣一個問題，智能手機是用戶與外界通信的一個指令中心。移動用戶可以使用智能手機用很多種方式聯繫他們的朋友，例如打電話、發送短消息、電子郵件、或者通過即時通信程序或者社交網絡，這些多渠道的通信方式和人與人之間面對面的交流一樣重要，因此智能手機是識別用戶和其他聯繫人的社會關係的關鍵。在本論文中，我們提出用智能手機中 獨有的多渠道用戶通信數據來對用戶的的社會關係進行分類。作為我們研究的開始，我們生成人工的通信數據並且用社交矩陣來為人與人之間的通信建立模型，這也幫助我們測試了很多可以應用在此類問題的數據挖掘算法。接下來，我們通過招募真實用戶來採集他們的各種社交通信數據，這些數據包括手機通話記錄、電子郵件、社交網絡（Facebook和Renren）和面對面的交流。通過在社交矩陣上應用不同的分類算法，我們發現SVM的分類性能要超過KNN和決策樹算法，SVM對於社會關係的分類準確率可以達到82.4%。我們也對來自不同渠道的通信數據進行了比較，最終發現來自社交網絡和面對面交流的數據在社交關係分類中起更大的作用。另外，我們通過使用降低維度算法可以把社交矩陣從65維度映射到9維度，關係分類的準確率卻沒有明顯降低，在降低維度的過程中我們也可以提取出用戶主要的通信特徵，從而更好地解釋社會關係分類的原理。最後，我們也應用了CUR矩陣分解算法從社交矩陣65列中選出13列建立新的社交矩陣，關係分類的準確率從82.4%降低到77.7%，但是我們卻可以通過 CUR來選擇合適的傳感器抽樣採集頻率，這樣可以在利用手機採集數據過程中節省更多手機電量。 / Wireless Communications and Mobile Computing have fundamentally changed the way people interact and communicate with each other. The proliferation of powerful and programmable mobile devices, smartphones in particular, has offered an unprecedented opportunity to continuously monitor the physical, social and geographical activities of their users. Recently, much research has been done on smartphone-based sensing which leverages the rich set of sensing, positioning and short-range radio capabilities of the smartphones to identify the context of user activities and ambient environment conditions. Mobile applications for personal behavior tracking and physical wellness monitoring have also been developed. Despite that, most of the existing work in mobile sensing has neglected the role of smartphone as the command-center of the user’s communications with the outside world. As mobile users contact their friends via phone, SMS, emails, instant messaging, and other online social-networking applications, these multi-modal communication activities are as equally important as physical activities in proling one’s life. They also hold the key to understand the user’s social relationship with other people of interest. In this thesis, we propose to use the unique multi-model interaction data from smartphone to classify social relationships. To jump start our study, we generate articial interaction data and build social interaction matrix to modeMl the interaction between people. This also helps us in testing a wide range of data mining analysis techniques for this type of problem. We then carry out a social interaction data collection campaign with a group of real users to obtain real-life multi-modal communication data, e.g., phone call, Email, online social network(Facebook and Renren), and physical location/proximity. After applying different classification algorithms on social interaction matrix, we find that SVM outperforms KNN and decision tree algorithms, with a classification accuracy of 82.4% (the accuracies of KNN and decision tree are 79.9% and 77.6%, respectively). We also compare the data from different interaction channels and finally find that on-line social network and location/proximity data contribute more to the overall classification accuracy. Additionally, with dimensionality reduction algorithms, the social interaction matrix can be embedded from 65 to 9 dimensional space while preserving the high classification accuracy and we also get principle interaction features as by-product. At last, we use CUR decomposi¬tion to select 13 out of the 65 features in the social interaction matrix. The classification accuracy drops from 82.4% to 77.7% after CUR decomposition. But it can help to determine the right sensor sampling frequency so as to enhance energy efficiency for social data collection. / Detailed summary in vernacular field only. / Sun, Deyi. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2012. / Includes bibliographical references (leaves 90-96). / Abstracts also in Chinese. / Chapter 1 --- Introduction --- p.1 / Chapter 2 --- Research Background --- p.7 / Chapter 2.1 --- Related work of social relationship analysis --- p.7 / Chapter 2.1.1 --- Community detection in social network --- p.8 / Chapter 2.1.2 --- Social influence analysis --- p.10 / Chapter 2.1.3 --- Modeling social interaction data --- p.10 / Chapter 2.1.4 --- Social relationship prediction --- p.12 / Chapter 2.2 --- Classification methodologies --- p.14 / Chapter 2.2.1 --- Algorithms for social relationship classification --- p.14 / Chapter 2.2.2 --- Algorithms for dimensionality reduction --- p.16 / Chapter 3 --- Problem Formulation of Relationship Classicification --- p.19 / Chapter 3.1 --- Multi-modal data in smartphones --- p.20 / Chapter 3.2 --- Formulation of relationship classification problem --- p.21 / Chapter 3.3 --- Refinement of feature definition and energy efficiency --- p.27 / Chapter 3.4 --- Chapter summary --- p.28 / Chapter 4 --- Social Interaction Data Acquisition --- p.30 / Chapter 4.1 --- Social interaction data collection campaign overview --- p.31 / Chapter 4.2 --- Format of raw interaction data --- p.33 / Chapter 4.3 --- Building social interaction matrix with real-life interaction data --- p.37 / Chapter 4.4 --- Chapter summary --- p.43 / Chapter 5 --- Statistical Analysis of Social Interaction Data --- p.45 / Chapter 5.1 --- Coverage of social interaction data --- p.46 / Chapter 5.2 --- Social relationships statistics --- p.48 / Chapter 5.3 --- Social relationship interaction patterns --- p.52 / Chapter 5.4 --- Chapter summary --- p.59 / Chapter 6 --- Automatic Social Relationship Classification Based on Smartphone Interaction Data --- p.61 / Chapter 6.1 --- Comparison of different classification algorithms --- p.62 / Chapter 6.2 --- Advantages of multi-modal interaction data --- p.65 / Chapter 6.3 --- Comparison of interaction data in different communication channels --- p.67 / Chapter 6.4 --- Dimensionality reduction on social interaction data --- p.72 / Chapter 6.5 --- Discussions in deploying social relationship classification application --- p.80 / Chapter 6.5.1 --- Considerations of user privacy --- p.81 / Chapter 6.5.2 --- Saving smartphone resources --- p.82 / Chapter 6.6 --- Chapter summary --- p.83 / Chapter 7 --- Conclusion and Future Work --- p.86 / Bibliography --- p.90

'Data Management and Curation' Breakout session from the Living the Future 8 Conference, April 23-24, 2012, University of Arizona Libraries, Tucson, AZ.

<p dir="ltr">There is a critical need for improvement in scientific data management when the big-data era arrives. Motivated by the evolution and significance of FAIR principles in contemporary research, the study focuses on the development and evaluation of a FAIR-compliant data resource portal. The challenge lies in translating the abstract FAIR principles into actionable, technological implementations and the evaluation. After baseline selection, the study aims to benchmark standards and outperform existing FAIR compliant data resource portals. The proposed approach includes an assessment of existing portals, the interpretation of FAIR principles into practical considerations, and the integration of modern technologies for the implementation. With a FAIR-ness evaluation framework designed and applied to the implementation, this study evaluated and improved the FAIR-compliance of data resource portal. Specifically, the study identified the need for improved persistent identifiers, comprehensive descriptive metadata, enhanced metadata access methods and adherence to community standards and formats. The evaluation of the FAIR-compliant data resource portal with FAIR implementation, showed a significant improvement in FAIR compliance, and eventually enhanced data discoverability, usability, and overall management in academic research.</p>