These slides present the paper entitled "A linked data model for semantic sensor stream". It does not include all the details, but an effort is made to show the main contribution of the paper.
UCSF Informatics Day 2014 - Jocel Dumlao, "REDCap / MyResearch"CTSI at UCSF
This document provides an overview of MyResearch and REDCap systems at UCSF. MyResearch is a data hosting service that provides a secure, HIPAA-compliant environment for storage and management of research data. It offers tools like a virtual desktop, shared drives, and data analysis software. REDCap is a web-based tool for building surveys and electronic data capture forms. It offers features like auto-validation, file uploads, and export to analysis packages. Both systems provide training through online and in-person sessions.
This document discusses research data management services at the University of Western Australia (UWA). It provides information on the Institutional Research Data Store (IRDS), a no-cost research data storage option for UWA researchers that provides 25GB of secure storage. It also discusses requirements for research data management and sharing from funding bodies like the Australian Research Council, and options for making data available through UWA's Research Data Online platform. Contact information is provided for the Research Data Coordinator for any questions.
Integrating research indicators for use in the repositories infrastructure petrknoth
The current repository infrastructure, which consists of thousands of repositories, does not make effective use of research indicators largely exploited by commercial players in the area. Research indicators, including citation counts and Mendeley reader counts, enable the development and improvement of functionality researchers use on a daily basis. For example, they make it possible to increase the performance in information retrieval and recommendation tasks and serve as an enabler for the development of research analytics & metrics functionality, such as the analysis of research trends or collaboration networks. We believe that there is a strong case for making a better use of these indicators within the repositories infrastructure to improve the functionality of services users rely on.
This presentation was provided by Corey Harper of Elsevier Labs during the NISO webinar, Using Analytics to Extract Value from the Library's Data, held on September 12, 2018.
The Kaleidoscope of Impact: same data, different perspectives, constantly cha...Kudos
Scholars, scientists, academic institutions, publishers and funders are all interested in impact. We have different roles and goals, and therefore different reasons for needing to understand impact; we are therefore asking different questions about impact, and those questions continue to evolve, much as the concept of impact itself is evolving. To answer our different questions, do we need different data, in separate silos, or are we looking at the same data, from different angles? This session gathered researcher, library, publisher and metrics provider perspectives to consider who has an interest in impact, what data they are interested in, how they use it, and how the situation is evolving as e.g. business models and technical infrastructures shift.
RDAP14: Developing an RDM Educational Service Using the New England Collabora...ASIS&T
Research Data Access and Preservation Summit, 2014
San Diego, CA
March 26-28, 2014
Regina Raboin,
Research Data Management Services Group Coordinator/Science Librarian,
Tufts University
Andrew Creamer, Project Coordinator,
University of Massachusetts Medical School
Donna Kafel, Project Coordinator,
University of Massachusetts Medical School
Elaine Martin, Library Director/NECDMC PI,
University of Massachusetts Medical School
COAR Next Generation Repositories WG - Text mining and Recommender system sto...petrknoth
One of the key aims of the COAR NGR group is to help us to overcome the challenges that still make it difficult to move beyond repositories as document silos. The group wants to see a globally interoperable network of repositories and global services built on top of repositories fulfilling the expectations of users in the 21st century. During this talk, I will address two use cases the COAR NGR working group aims to enable: text and data mining and recommender systems.
Capturing and Analyzing Publication, Citation and Usage Data for Contextual C...NASIG
Libraries have long sought to demonstrate the value of their collections through a variety of usage statistics. Traditionally, a strong emphasis is placed on high usage statistics when evaluating journals in collection development discussions. However, as budget pressures persist, administrators are increasingly concerned with looking beyond traditional usage metrics to determine the real impact of library services and collections. By examining journal usage in the context of scholarly communication, we hope to gain a more holistic understanding of the use and impact of our library’s resources. In this session, we begin by outlining our methodology for gathering comprehensive publication and citation data for authors affiliated with Northwestern University’s Feinberg School of Medicine, utilizing Web of Science as our primary data source and leveraging a custom Python script to manage the data. Using this data we discuss various potential metrics that could be employed to measure and evaluate journals in institutional and field-specific contexts, including but not limited to: number of publications and references per journal, co-citation networks, percentage of references per journal, and increases or decreases of references over time per title. We then consider the development of normalized benchmarks and criteria for creating field-specific core journal lists. We also discuss a process for establishing usage thresholds to evaluate existing journal subscriptions and to highlight potential gaps in the collection. Finally, we apply and compare these metrics to traditional collection development tools like COUNTER usage reports, cost-per-use analysis, Inter-Library Loan statistics and turnaway reports, to determine what correlations or discrepancies might exist. We finish by highlighting some use-cases which demonstrate the value of considering publication and citation metrics, and provide suggestions for incorporating these metrics into library collection development practices.
Speakers: Joelen Pastva and Jonathan Shank, Northwestern University
Project GitHub page: https://goo.gl/2C2Pcy
UCSF Informatics Day 2014 - Jocel Dumlao, "REDCap / MyResearch"CTSI at UCSF
This document provides an overview of MyResearch and REDCap systems at UCSF. MyResearch is a data hosting service that provides a secure, HIPAA-compliant environment for storage and management of research data. It offers tools like a virtual desktop, shared drives, and data analysis software. REDCap is a web-based tool for building surveys and electronic data capture forms. It offers features like auto-validation, file uploads, and export to analysis packages. Both systems provide training through online and in-person sessions.
This document discusses research data management services at the University of Western Australia (UWA). It provides information on the Institutional Research Data Store (IRDS), a no-cost research data storage option for UWA researchers that provides 25GB of secure storage. It also discusses requirements for research data management and sharing from funding bodies like the Australian Research Council, and options for making data available through UWA's Research Data Online platform. Contact information is provided for the Research Data Coordinator for any questions.
Integrating research indicators for use in the repositories infrastructure petrknoth
The current repository infrastructure, which consists of thousands of repositories, does not make effective use of research indicators largely exploited by commercial players in the area. Research indicators, including citation counts and Mendeley reader counts, enable the development and improvement of functionality researchers use on a daily basis. For example, they make it possible to increase the performance in information retrieval and recommendation tasks and serve as an enabler for the development of research analytics & metrics functionality, such as the analysis of research trends or collaboration networks. We believe that there is a strong case for making a better use of these indicators within the repositories infrastructure to improve the functionality of services users rely on.
This presentation was provided by Corey Harper of Elsevier Labs during the NISO webinar, Using Analytics to Extract Value from the Library's Data, held on September 12, 2018.
The Kaleidoscope of Impact: same data, different perspectives, constantly cha...Kudos
Scholars, scientists, academic institutions, publishers and funders are all interested in impact. We have different roles and goals, and therefore different reasons for needing to understand impact; we are therefore asking different questions about impact, and those questions continue to evolve, much as the concept of impact itself is evolving. To answer our different questions, do we need different data, in separate silos, or are we looking at the same data, from different angles? This session gathered researcher, library, publisher and metrics provider perspectives to consider who has an interest in impact, what data they are interested in, how they use it, and how the situation is evolving as e.g. business models and technical infrastructures shift.
RDAP14: Developing an RDM Educational Service Using the New England Collabora...ASIS&T
Research Data Access and Preservation Summit, 2014
San Diego, CA
March 26-28, 2014
Regina Raboin,
Research Data Management Services Group Coordinator/Science Librarian,
Tufts University
Andrew Creamer, Project Coordinator,
University of Massachusetts Medical School
Donna Kafel, Project Coordinator,
University of Massachusetts Medical School
Elaine Martin, Library Director/NECDMC PI,
University of Massachusetts Medical School
COAR Next Generation Repositories WG - Text mining and Recommender system sto...petrknoth
One of the key aims of the COAR NGR group is to help us to overcome the challenges that still make it difficult to move beyond repositories as document silos. The group wants to see a globally interoperable network of repositories and global services built on top of repositories fulfilling the expectations of users in the 21st century. During this talk, I will address two use cases the COAR NGR working group aims to enable: text and data mining and recommender systems.
Capturing and Analyzing Publication, Citation and Usage Data for Contextual C...NASIG
Libraries have long sought to demonstrate the value of their collections through a variety of usage statistics. Traditionally, a strong emphasis is placed on high usage statistics when evaluating journals in collection development discussions. However, as budget pressures persist, administrators are increasingly concerned with looking beyond traditional usage metrics to determine the real impact of library services and collections. By examining journal usage in the context of scholarly communication, we hope to gain a more holistic understanding of the use and impact of our library’s resources. In this session, we begin by outlining our methodology for gathering comprehensive publication and citation data for authors affiliated with Northwestern University’s Feinberg School of Medicine, utilizing Web of Science as our primary data source and leveraging a custom Python script to manage the data. Using this data we discuss various potential metrics that could be employed to measure and evaluate journals in institutional and field-specific contexts, including but not limited to: number of publications and references per journal, co-citation networks, percentage of references per journal, and increases or decreases of references over time per title. We then consider the development of normalized benchmarks and criteria for creating field-specific core journal lists. We also discuss a process for establishing usage thresholds to evaluate existing journal subscriptions and to highlight potential gaps in the collection. Finally, we apply and compare these metrics to traditional collection development tools like COUNTER usage reports, cost-per-use analysis, Inter-Library Loan statistics and turnaway reports, to determine what correlations or discrepancies might exist. We finish by highlighting some use-cases which demonstrate the value of considering publication and citation metrics, and provide suggestions for incorporating these metrics into library collection development practices.
Speakers: Joelen Pastva and Jonathan Shank, Northwestern University
Project GitHub page: https://goo.gl/2C2Pcy
Clarivate was selected as the citation provider for the 2018 Excellence in Research for Australia (ERA) evaluation. The role involved preparing, submitting, and checking citation data from Clarivate's databases to support the ERA evaluation. Clarivate mapped institutional publication records to citations in the Web of Science and provided tagging portals and APIs to help with this process. They also offered seminars and support to help universities understand the citation data and benchmarks. Moving forward, Clarivate wants to leverage feedback to better support the quality of Australian research.
This document summarizes Helen Henderson's presentation on institutional identifiers. It discusses existing standards like ONIX, COUNTER, and ISSN, as well as new standards being developed like KBART, Project TRANSFER, and CORE. It outlines several scenarios where institutional identifiers could be used, such as in the electronic resources supply chain, eLearning, research funding, and author registries. It describes the stakeholders involved in each scenario and key issues to address. Finally, it provides the timeline and work plan for the NISO working group developing a new institutional identifier standard.
Big Data (SOCIOMETRIC METHODS FOR RELEVANCY ANALYSIS OF LONG TAIL SCIENCE D...AKSHAY BHAGAT
This document discusses the DataBridge project, which aims to enable easier discoverability and use of long tail science data. DataBridge will create a multidimensional network and social network for scientific data by mapping datasets connected by relationships between their metadata, usage, and the methods used to analyze them. This will allow researchers to more easily find relevant datasets by automatically forming communities of similar data. The document outlines DataBridge's vision and progress to date, including the algorithms it is investigating for measuring similarity between datasets in order to facilitate searching for collaborators and discoveries.
Crossref LIVE19 - Researcher and metadata user viewLudo Waltman
The document discusses using Crossref data in VOSviewer software to analyze journal citation networks. It provides three recommendations: 1) Ensure the basic infrastructure for working with Crossref data works well. 2) Work with publishers to increase the completeness of metadata like abstracts, affiliations, and license data. 3) Participate in initiatives to improve and enrich metadata and develop sustainable funding models for such initiatives.
The document provides an introduction to MEDIN Data Guidelines. It explains that the guidelines are data archive standards intended to instill good practice, provide a consistent format for contractors to work to when returning data, and allow for easy ingestion of data into data archiving centers. The guidelines encompass a range of data types from public sightings to complex surveys. They are structured around six tables and provide standard templates for documenting project, survey, sample, and data information.
RDAP 16: If I could turn back time: Looking back on 2+ years of DMP consultin...ASIS&T
This document summarizes Andi Ogier's experience providing data management plan (DMP) consulting at Virginia Tech over the past 2 years. It outlines the goals and timeline of DMP consulting services, things that have been done to educate researchers on DMPs, statistics on DMP consulting, logistics of the consulting process, feedback received from the National Science Foundation, and plans for the future of DMP consulting at Virginia Tech including more embedded consulting and leveraging new data repository services.
Research information management: making sense of it allDigital Science
"Research information management: making sense of it all" - Julia Hawks, VP North America, Symplectic
Slides from Shaking It Up: Challenges and Solutions in Scholarly Information Management, San Francisco, April 22, 2015
Navigating the data management ecosystem - John KratzDigital Science
The document outlines a 4 unit project plan to develop the Data LifeCycle Metrics (DLM) project. Unit 1 involves field research through surveys, interviews and focus groups to determine requirements for DLM. The output is metrics design and requirements. Unit 2 extends existing usage tracking capacity and the output is a COUNTER-based usage API. Unit 3 formulates test metrics and extends the technology with the output being a DLM application. Unit 4 develops tools for the community to use metrics with the outputs being a DLM Reports application and widgets, and a bibliometric analysis report.
This document discusses statistical and visualization methods for analyzing metagenomic data. It introduces several R/Bioconductor packages for metagenomic analysis, including metagenomeSeq for differential abundance analysis of 16S data and metagenomicFeatures for annotating 16S features. It also describes msd16s example data. Additionally, it discusses the benefits of R/Bioconductor including infrastructure objects, documentation, and reproducibility. Finally, it introduces Metaviz, an interactive browser-based tool for exploring hierarchical metagenomic data through integration and visualization of multiple data sources.
Navigating the data management ecosystem - Dan ValenDigital Science
This document discusses several key aspects of effective data management and open access to research outputs. It notes that repositories, APIs, data citations, and open access policies are essential to enable easy reuse and verification of data. Common objections to open data practices, such as risk of being scooped, are addressed. The benefits of data sharing are outlined, including enabling verification and tracking impact. Effective tools and infrastructure are needed to support open data practices, including repositories, APIs, reporting dashboards, and curation workflows.
This presentation was provided by Carly Strasser of the Chan Zuckerberg Initiative during the NISO hot topic virtual conference "Effective Data Management," which was held on September 29, 2021.
Practical applications for altmetrics in a changing metrics landscapeDigital Science
"Practical applications for altmetrics in a changing metrics landscape" - Sara Rouhi, Altmetric product specialist, and Anirvan Chatterjee, Director Data Strategy for CTSI at UCSF
Key lecture for the EURO-BASIN Training Workshop on Introduction to Statistical Modelling for Habitat Model Development, 26-28 Oct, AZTI-Tecnalia, Pasaia, Spain (www.euro-basin.eu)
A short review of the new initiatives related to research data management at Harvard University for the CRADLE workshop at IASSIST 2017 (http://www.iassist2017.org/).
Mary Pickstone, Research Support Librarian
PowerPoint accompaniment to the Researchers Development Programme, PAHC, MMU session on 1st November 2017.
Open Research is the process of sharing your research findings with others, for example through Open Access publications, Open Data or blogging. It increases the visibility and accessibility of your work. This session covers the key areas related to open research, such as how to create a simple data management plan; obtaining informed consent for data sharing from research participants; the anonymisation and storage of sensitive data.
This presentations includes the basic fundamentals of time series data forecasting. It starts with basic naive, regression models and then explains advanced ARIMA models.
Naming in content_oriented_architectures [repaired]haroonrashidlone
This document summarizes a paper about naming in content-oriented architectures. It discusses two main naming types: self-certifying flat naming using cryptography, and user-friendly hierarchical naming. Key issues discussed are scalability, security, and flexibility. The document also covers how each naming type establishes security through integrity, confidentiality, provenance and availability. It compares the two approaches on usability, binding relationships, scalability through aggregation, and flexibility.
Clarivate was selected as the citation provider for the 2018 Excellence in Research for Australia (ERA) evaluation. The role involved preparing, submitting, and checking citation data from Clarivate's databases to support the ERA evaluation. Clarivate mapped institutional publication records to citations in the Web of Science and provided tagging portals and APIs to help with this process. They also offered seminars and support to help universities understand the citation data and benchmarks. Moving forward, Clarivate wants to leverage feedback to better support the quality of Australian research.
This document summarizes Helen Henderson's presentation on institutional identifiers. It discusses existing standards like ONIX, COUNTER, and ISSN, as well as new standards being developed like KBART, Project TRANSFER, and CORE. It outlines several scenarios where institutional identifiers could be used, such as in the electronic resources supply chain, eLearning, research funding, and author registries. It describes the stakeholders involved in each scenario and key issues to address. Finally, it provides the timeline and work plan for the NISO working group developing a new institutional identifier standard.
Big Data (SOCIOMETRIC METHODS FOR RELEVANCY ANALYSIS OF LONG TAIL SCIENCE D...AKSHAY BHAGAT
This document discusses the DataBridge project, which aims to enable easier discoverability and use of long tail science data. DataBridge will create a multidimensional network and social network for scientific data by mapping datasets connected by relationships between their metadata, usage, and the methods used to analyze them. This will allow researchers to more easily find relevant datasets by automatically forming communities of similar data. The document outlines DataBridge's vision and progress to date, including the algorithms it is investigating for measuring similarity between datasets in order to facilitate searching for collaborators and discoveries.
Crossref LIVE19 - Researcher and metadata user viewLudo Waltman
The document discusses using Crossref data in VOSviewer software to analyze journal citation networks. It provides three recommendations: 1) Ensure the basic infrastructure for working with Crossref data works well. 2) Work with publishers to increase the completeness of metadata like abstracts, affiliations, and license data. 3) Participate in initiatives to improve and enrich metadata and develop sustainable funding models for such initiatives.
The document provides an introduction to MEDIN Data Guidelines. It explains that the guidelines are data archive standards intended to instill good practice, provide a consistent format for contractors to work to when returning data, and allow for easy ingestion of data into data archiving centers. The guidelines encompass a range of data types from public sightings to complex surveys. They are structured around six tables and provide standard templates for documenting project, survey, sample, and data information.
RDAP 16: If I could turn back time: Looking back on 2+ years of DMP consultin...ASIS&T
This document summarizes Andi Ogier's experience providing data management plan (DMP) consulting at Virginia Tech over the past 2 years. It outlines the goals and timeline of DMP consulting services, things that have been done to educate researchers on DMPs, statistics on DMP consulting, logistics of the consulting process, feedback received from the National Science Foundation, and plans for the future of DMP consulting at Virginia Tech including more embedded consulting and leveraging new data repository services.
Research information management: making sense of it allDigital Science
"Research information management: making sense of it all" - Julia Hawks, VP North America, Symplectic
Slides from Shaking It Up: Challenges and Solutions in Scholarly Information Management, San Francisco, April 22, 2015
Navigating the data management ecosystem - John KratzDigital Science
The document outlines a 4 unit project plan to develop the Data LifeCycle Metrics (DLM) project. Unit 1 involves field research through surveys, interviews and focus groups to determine requirements for DLM. The output is metrics design and requirements. Unit 2 extends existing usage tracking capacity and the output is a COUNTER-based usage API. Unit 3 formulates test metrics and extends the technology with the output being a DLM application. Unit 4 develops tools for the community to use metrics with the outputs being a DLM Reports application and widgets, and a bibliometric analysis report.
This document discusses statistical and visualization methods for analyzing metagenomic data. It introduces several R/Bioconductor packages for metagenomic analysis, including metagenomeSeq for differential abundance analysis of 16S data and metagenomicFeatures for annotating 16S features. It also describes msd16s example data. Additionally, it discusses the benefits of R/Bioconductor including infrastructure objects, documentation, and reproducibility. Finally, it introduces Metaviz, an interactive browser-based tool for exploring hierarchical metagenomic data through integration and visualization of multiple data sources.
Navigating the data management ecosystem - Dan ValenDigital Science
This document discusses several key aspects of effective data management and open access to research outputs. It notes that repositories, APIs, data citations, and open access policies are essential to enable easy reuse and verification of data. Common objections to open data practices, such as risk of being scooped, are addressed. The benefits of data sharing are outlined, including enabling verification and tracking impact. Effective tools and infrastructure are needed to support open data practices, including repositories, APIs, reporting dashboards, and curation workflows.
This presentation was provided by Carly Strasser of the Chan Zuckerberg Initiative during the NISO hot topic virtual conference "Effective Data Management," which was held on September 29, 2021.
Practical applications for altmetrics in a changing metrics landscapeDigital Science
"Practical applications for altmetrics in a changing metrics landscape" - Sara Rouhi, Altmetric product specialist, and Anirvan Chatterjee, Director Data Strategy for CTSI at UCSF
Key lecture for the EURO-BASIN Training Workshop on Introduction to Statistical Modelling for Habitat Model Development, 26-28 Oct, AZTI-Tecnalia, Pasaia, Spain (www.euro-basin.eu)
A short review of the new initiatives related to research data management at Harvard University for the CRADLE workshop at IASSIST 2017 (http://www.iassist2017.org/).
Mary Pickstone, Research Support Librarian
PowerPoint accompaniment to the Researchers Development Programme, PAHC, MMU session on 1st November 2017.
Open Research is the process of sharing your research findings with others, for example through Open Access publications, Open Data or blogging. It increases the visibility and accessibility of your work. This session covers the key areas related to open research, such as how to create a simple data management plan; obtaining informed consent for data sharing from research participants; the anonymisation and storage of sensitive data.
This presentations includes the basic fundamentals of time series data forecasting. It starts with basic naive, regression models and then explains advanced ARIMA models.
Naming in content_oriented_architectures [repaired]haroonrashidlone
This document summarizes a paper about naming in content-oriented architectures. It discusses two main naming types: self-certifying flat naming using cryptography, and user-friendly hierarchical naming. Key issues discussed are scalability, security, and flexibility. The document also covers how each naming type establishes security through integrity, confidentiality, provenance and availability. It compares the two approaches on usability, binding relationships, scalability through aggregation, and flexibility.
The document discusses three papers related to routing in Information-Centric Networking (ICN).
The first paper proposes INFORM, a dynamic interest forwarding algorithm for ICN that aims to discover temporary copies of content, forward requests towards the "best" interface, guarantee data delivery, and limit network overhead.
The second paper presents NLSR, an ICN routing protocol that uses content names instead of IP addresses. It advertises link state information and computes multiple paths between nodes to forward interests.
The third paper proposes a two-layer intra-domain routing scheme with a lower topology maintenance layer and upper prefix announcement layer. It deals with trade-offs between actively publishing popular content versus serving unpopular content
The document discusses Binary Decision Diagrams (BDDs) and Ordered BDDs (OBDDs) which provide a more compact representation of Boolean functions compared to truth tables. It describes algorithms for reducing, applying logical operations, restricting variables, and checking satisfiability on BDDs/OBDDs. OBDDs ensure variables appear in the same order on all paths, allowing efficient equivalence checking. The document concludes with applications of OBDDs in symbolic model checking where sets of states are represented as OBDDs.
This document summarizes a paper on Content Centric Networking (CCN). Some key points of CCN include that it considers only named data packets rather than host identities, supports multicasting when multiple data sources are found, uses name prefixes for routing instead of IP prefixes, and builds security into each data packet through digital signatures rather than securing the data channel. CCN is evaluated to have lower throughput than TCP initially but can perform better in scenarios where data sharing is common. There are some open concerns about CCN including the structure of content names and inter-domain routing.
This document proposes a framework for managing and querying multidimensional historical data distributed across an unstructured peer-to-peer network. When data is published, it is summarized into a synopsis containing an index and sub-synopses storing compressed data portions. The index and sub-synopses are distributed across the network with suitable replication to provide coverage for queries. The framework supports data publication and querying while ensuring peer autonomy and handling volatile peers through prompt reaction to disconnections to prevent broken index references.
Semantic Similarity and Selection of Resources Published According to Linked ...Riccardo Albertoni
The position paper aims at discussing the potential of exploiting linked data best practice to provide metadata documenting domain specific resources created through verbose acquisition-processing pipelines. It argues that resource selection, namely the process engaged to choose a set of resources suitable for a given analysis/design purpose, must be supported by a deep comparison of their metadata. The semantic similarity proposed in our previous works is discussed for this purpose and the main issues to make it scale up to the web of data are introduced. Discussed issues contribute beyond the re-engineering of our similarity since they largely apply to every tool which is going to exploit information made available as linked data. A research plan and an exploratory phase facing the presented issues are described remarking the lessons we have learnt so far.
Linked Open Data - State of the Art, Challenges and ApplicationsRui Vieira
This document discusses linked open data, including its definition, architecture, challenges, and applications. Specifically, it defines linked open data as open data that is distributed over the network in a standardized, machine-readable format using semantic technologies. It outlines some of the key challenges in implementing linked open data at scale, such as data quality, security, and aggregation issues. Finally, it presents examples of applications of linked open data in government and sensor data integration.
The document discusses advances in data management practices and technologies for ecosystem science. It describes the role of a data manager in facilitating data management, from collecting raw data to organizing it in standard formats and metadata according to community practices. Well-managed data is stored and shared through repositories to enable discovery, access, interoperability and future reuse. Resources and experts are available to help researchers improve their data management.
Combining Data Lake and Data Wrangling for Ensuring Data Quality in CRISAnastasija Nikiforova
This presentation is a supplementary material for the "Combining Data Lake and Data Wrangling for Ensuring Data Quality in CRIS" presented at 15th International Conference on Current Research Information Systems (CRIS2022) - Linking Research Information across data spaces. It provides an insight on the ongoing study of combining data lake as a data repository and data wrangling seeking for an increased data quality in CRIS systems, although the proposed approach is domain-agnostic and can be used not only within CRIS.
Read the article here -> Azeroual, O., Schöpfel, J., Ivanovic, D., & Nikiforova, A. (2022, May). Combining Data Lake and Data Wrangling for Ensuring Data Quality in CRIS. In CRIS2022: 15th International Conference on Current Research Information Systems --> https://hal.archives-ouvertes.fr/hal-03694519/
1) This document discusses different techniques for cross-domain data fusion, including stage-based, feature-level, probabilistic, and multi-view learning methods.
2) It reviews literature on data fusion definitions, implementations, and techniques for handling data conflicts. Common steps in data fusion are data transformation, schema mapping, and duplicate detection.
3) The proposed system architecture performs data cleaning, then applies stage-based, feature-level, probabilistic, and multi-view learning fusion methods before analyzing dataset, hardware, and software requirements.
A hierarchical tensor based approach to compressing, updating and querying ge...ieeepondy
This document presents a new approach for compressing, continuously updating, and querying multidimensional geospatial data using a blocked hierarchical tensor representation. The original data is split into small blocks and represented hierarchically in a binary tree structure, allowing for compressed storage and efficient querying. Evaluation using reanalysis data shows the approach retains data quality while reducing storage costs and speeding computation compared to traditional methods.
A podium abstract presented at AMIA 2016 Joint Summits on Translational Science. This discusses Data Café — A Platform For Creating Biomedical Data Lakes.
Data Profiling, Data Catalogs and Metadata HarmonisationAlan McSweeney
These notes discuss the related topics of Data Profiling, Data Catalogs and Metadata Harmonisation. It describes a detailed structure for data profiling activities. It identifies various open source and commercial tools and data profiling algorithms. Data profiling is a necessary pre-requisite activity in order to construct a data catalog. A data catalog makes an organisation’s data more discoverable. The data collected during data profiling forms the metadata contained in the data catalog. This assists with ensuring data quality. It is also a necessary activity for Master Data Management initiatives. These notes describe a metadata structure and provide details on metadata standards and sources.
What researchers want with regard to research data management (RDM)heila1
Surveys, Surveys: Survey at UP 2010, Survey at UP 2013
Survey at CSIR 2013
RDM pilots @ UP
Started with one pilot; other researchers followed
What next?
• One of the most important decisions a distributed database designer has to make is data placement. Proper data placement is a crucial factor in determining the success of a distributed database system.
• There are four basic alternatives: namely,
– centralized,
– replicated,
– partitioned, and
– hybrid.
Temporal and spatial databases allow for the storage and querying of data that involves time or spatial aspects. Conventional databases only provide a snapshot of data, while temporal databases can maintain historical information and access past states of data. Spatial databases support spatial data types like polygons and spatial queries involving operations like overlap and distance. Key components of temporal and spatial databases are their data models, query languages, indexing structures like R-trees, and optimized algorithms for processing queries over time-series and geospatial data.
BioSHaRE: Making data useful without direct sharing: Cafe Variome and Omics b...Lisette Giepmans
BioSHaRE conference July 28th, 2015, Milan - Latest tools and services for data sharing
Stream 1: Tools for data sharing analysis and enhancement
Café Variome is a highly flexible data discovery platform suitable for use with genomic data and/or phenotype data in settings such as diagnostic networks, disease consortia, biobanks and research communities. It enables users to search for the existence rather than the substance of datasets, and as part of this offers a complete suite of data discovery capabilities, focused on the data rather than metadata. Following data discovery, the system also facilitates controlled data sharing.
‘Café Variome Central’ aims to consolidate all publicly available genetic variants into one discovery portal through which to announce, discover and acquire a comprehensive listing of observed neutral and disease-causing gene variants. It employs publicly available web services to gather and make searchable a set of pointers to records of interest, to help users discover the existence of variant data and direct them to the original data sources where the data may be examined in full.
The software is in production as version 1.0 software, available presently for collaborative applications: http://www.cafevariome.org/
Café Variome can be installed stand-alone, or federated to allow searching across instances while the data remains at the source
OmicsConnect, underpinned by an ‘extended DAS’ (eDAS) protocol for data transfer, enables data feed into a genome browser tool from diverse sources and controlling which users should have access to which data sources and which data slices in those datasets.
DAS is a Extensible Markup Language (XML) communication protocol that allows a single client (e.g. a genome browser) to integrate information from multiple DAS servers dispersed around the world to present a unified view of data. The eDAS system brings many new advantages; the data are controlled by the content providers and can be modified, restricted and updated as required and the data are shared in a way that makes it easy for the end user to get information about specific regions, genes or markers without having to download and process entire datasets.
The latest version of OmicsConnect is
available for use under standard terms of academic collaboration:
http://omicsconnect.org
The tool is currently being improved for better adaptability and faster performance (fall 2015).
Contact info:
Prof. Anthony Brookes
University of Leicester
ajb97@leicester.ac.uk
Key words: genomics, genotype-phenotype, matchmaking, query-by-method apoi, rare disease, software
This document discusses research data management and related issues. It defines research data as any information used in research, including observational, experimental, and simulated data. Proper research data management is important for data preservation, access, and reuse. Institutions should establish research data services and policies to address questions around data ownership, sharing standards, and long-term preservation.
A scalable architecture for extracting, aligning, linking, and visualizing mu...Craig Knoblock
The document proposes an architecture for extracting, aligning, linking, and visualizing multi-source intelligence data at scale. The architecture uses open source software like Apache Nutch, Karma, ElasticSearch, and Hadoop to extract structured and unstructured data, integrate the data using machine learning, compute similarities, resolve entities, construct a knowledge graph, and allow querying and visualization of the graph. An example scenario of analyzing a country's nuclear capabilities from open sources is provided to illustrate the system.
Big data deep learning: applications and challengesfazail amin
This document discusses big data, deep learning, and their applications and challenges. It begins with an introduction to big data that defines it in terms of large volume, high velocity, and variety of data types. It then discusses challenges of big data like storage, transfer, privacy, and analyzing diverse data types. Applications of big data analytics include sensor data analysis, trend analysis, and network intrusion detection. Deep learning algorithms can extract patterns from large unlabeled data and non-local relationships. Applications of deep learning in big data include semantic indexing for search engines, discriminative tasks using extracted features, and transfer learning. Challenges of deep learning in big data include learning from streaming data, high dimensionality, scalability, and distributed computing.
Optimising Clinical Trials Monitoring Data review - Neill BarronNeill Barron
This document outlines a strategic approach to optimize trial monitoring and data review. It aims to develop a comprehensive strategy that delivers high quality data and improved study performance through three main workstreams: 1) Focusing on essential data, 2) In-stream remote monitoring, and 3) Targeted and adaptive site monitoring practices. The objectives are to ensure quality through subject protection, protocol execution, and data integrity while improving performance through high enrollment, protocol compliance, and timeline delivery. The strategy proposes shifting monitoring efforts from extensive source data verification to remote monitoring and targeted on-site activities based on site performance. It argues this comprehensive approach can double productivity through quality focus, detection efficiency, and site ownership.
This document provides an overview of the key concepts around big data and Hadoop. It discusses big data sources and challenges, including capturing, storing, searching, sharing, transferring, analyzing and presenting large amounts of data. It then describes how Hadoop provides a cost-effective solution for storage and processing of big data using a distributed architecture. Finally, the document outlines the core components of Hadoop including the Hadoop Distributed File System for storage and MapReduce for distributed processing.
This document provides an overview of wound healing, its functions, stages, mechanisms, factors affecting it, and complications.
A wound is a break in the integrity of the skin or tissues, which may be associated with disruption of the structure and function.
Healing is the body’s response to injury in an attempt to restore normal structure and functions.
Healing can occur in two ways: Regeneration and Repair
There are 4 phases of wound healing: hemostasis, inflammation, proliferation, and remodeling. This document also describes the mechanism of wound healing. Factors that affect healing include infection, uncontrolled diabetes, poor nutrition, age, anemia, the presence of foreign bodies, etc.
Complications of wound healing like infection, hyperpigmentation of scar, contractures, and keloid formation.
A review of the growth of the Israel Genealogy Research Association Database Collection for the last 12 months. Our collection is now passed the 3 million mark and still growing. See which archives have contributed the most. See the different types of records we have, and which years have had records added. You can also see what we have for the future.
Strategies for Effective Upskilling is a presentation by Chinwendu Peace in a Your Skill Boost Masterclass organisation by the Excellence Foundation for South Sudan on 08th and 09th June 2024 from 1 PM to 3 PM on each day.
বাংলাদেশের অর্থনৈতিক সমীক্ষা ২০২৪ [Bangladesh Economic Review 2024 Bangla.pdf] কম্পিউটার , ট্যাব ও স্মার্ট ফোন ভার্সন সহ সম্পূর্ণ বাংলা ই-বুক বা pdf বই " সুচিপত্র ...বুকমার্ক মেনু 🔖 ও হাইপার লিংক মেনু 📝👆 যুক্ত ..
আমাদের সবার জন্য খুব খুব গুরুত্বপূর্ণ একটি বই ..বিসিএস, ব্যাংক, ইউনিভার্সিটি ভর্তি ও যে কোন প্রতিযোগিতা মূলক পরীক্ষার জন্য এর খুব ইম্পরট্যান্ট একটি বিষয় ...তাছাড়া বাংলাদেশের সাম্প্রতিক যে কোন ডাটা বা তথ্য এই বইতে পাবেন ...
তাই একজন নাগরিক হিসাবে এই তথ্য গুলো আপনার জানা প্রয়োজন ...।
বিসিএস ও ব্যাংক এর লিখিত পরীক্ষা ...+এছাড়া মাধ্যমিক ও উচ্চমাধ্যমিকের স্টুডেন্টদের জন্য অনেক কাজে আসবে ...
it describes the bony anatomy including the femoral head , acetabulum, labrum . also discusses the capsule , ligaments . muscle that act on the hip joint and the range of motion are outlined. factors affecting hip joint stability and weight transmission through the joint are summarized.
LAND USE LAND COVER AND NDVI OF MIRZAPUR DISTRICT, UPRAHUL
This Dissertation explores the particular circumstances of Mirzapur, a region located in the
core of India. Mirzapur, with its varied terrains and abundant biodiversity, offers an optimal
environment for investigating the changes in vegetation cover dynamics. Our study utilizes
advanced technologies such as GIS (Geographic Information Systems) and Remote sensing to
analyze the transformations that have taken place over the course of a decade.
The complex relationship between human activities and the environment has been the focus
of extensive research and worry. As the global community grapples with swift urbanization,
population expansion, and economic progress, the effects on natural ecosystems are becoming
more evident. A crucial element of this impact is the alteration of vegetation cover, which plays a
significant role in maintaining the ecological equilibrium of our planet.Land serves as the foundation for all human activities and provides the necessary materials for
these activities. As the most crucial natural resource, its utilization by humans results in different
'Land uses,' which are determined by both human activities and the physical characteristics of the
land.
The utilization of land is impacted by human needs and environmental factors. In countries
like India, rapid population growth and the emphasis on extensive resource exploitation can lead
to significant land degradation, adversely affecting the region's land cover.
Therefore, human intervention has significantly influenced land use patterns over many
centuries, evolving its structure over time and space. In the present era, these changes have
accelerated due to factors such as agriculture and urbanization. Information regarding land use and
cover is essential for various planning and management tasks related to the Earth's surface,
providing crucial environmental data for scientific, resource management, policy purposes, and
diverse human activities.
Accurate understanding of land use and cover is imperative for the development planning
of any area. Consequently, a wide range of professionals, including earth system scientists, land
and water managers, and urban planners, are interested in obtaining data on land use and cover
changes, conversion trends, and other related patterns. The spatial dimensions of land use and
cover support policymakers and scientists in making well-informed decisions, as alterations in
these patterns indicate shifts in economic and social conditions. Monitoring such changes with the
help of Advanced technologies like Remote Sensing and Geographic Information Systems is
crucial for coordinated efforts across different administrative levels. Advanced technologies like
Remote Sensing and Geographic Information Systems
9
Changes in vegetation cover refer to variations in the distribution, composition, and overall
structure of plant communities across different temporal and spatial scales. These changes can
occur natural.
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How to Add Chatter in the odoo 17 ERP ModuleCeline George
In Odoo, the chatter is like a chat tool that helps you work together on records. You can leave notes and track things, making it easier to talk with your team and partners. Inside chatter, all communication history, activity, and changes will be displayed.
How to Fix the Import Error in the Odoo 17Celine George
An import error occurs when a program fails to import a module or library, disrupting its execution. In languages like Python, this issue arises when the specified module cannot be found or accessed, hindering the program's functionality. Resolving import errors is crucial for maintaining smooth software operation and uninterrupted development processes.
This slide is special for master students (MIBS & MIFB) in UUM. Also useful for readers who are interested in the topic of contemporary Islamic banking.
Walmart Business+ and Spark Good for Nonprofits.pdfTechSoup
"Learn about all the ways Walmart supports nonprofit organizations.
You will hear from Liz Willett, the Head of Nonprofits, and hear about what Walmart is doing to help nonprofits, including Walmart Business and Spark Good. Walmart Business+ is a new offer for nonprofits that offers discounts and also streamlines nonprofits order and expense tracking, saving time and money.
The webinar may also give some examples on how nonprofits can best leverage Walmart Business+.
The event will cover the following::
Walmart Business + (https://business.walmart.com/plus) is a new shopping experience for nonprofits, schools, and local business customers that connects an exclusive online shopping experience to stores. Benefits include free delivery and shipping, a 'Spend Analytics” feature, special discounts, deals and tax-exempt shopping.
Special TechSoup offer for a free 180 days membership, and up to $150 in discounts on eligible orders.
Spark Good (walmart.com/sparkgood) is a charitable platform that enables nonprofits to receive donations directly from customers and associates.
Answers about how you can do more with Walmart!"
Walmart Business+ and Spark Good for Nonprofits.pdf
Linked data representation
1. A Linked-data Model For
Semantic Sensor Streams
Authors: P. Barnaghi et al.
Presenter: Haroon Rashid
113/03/15
2. Problem
• Describe semantically sensor data streams
– Continuous observations and measurements
• Semantic representation of data streams
– Metadata increases the size of transferred data to
a greater extent
• Efficient Semantic Queries for large-scale
annotated data
213/03/15
3. Solution
• Use Linked data concept
– Store static, common attributes at one place
– Provide links to static data wherever needed
313/03/15
10. Data Distribution
• Clustering approach
– Store data on distributed repositories
– Results in fast query and resolution mechanisms
• Using K-means Clustering
– Involves both storing and fetching data in/from
different clusters
– Needs extensive training
1013/03/15
12. Questions
1. Can we improve data identification which will
enhance data resolution/composition?
2. Size of the stream stream/series?
1. Depends on application requirements,
bandwidth, caching, freshness
3. On clustering, query efficiency not shown
4. Can we use sample data for showing
efficiency of a technique in paper?
1213/03/15