1. Metrics are being developed to track downloads and reuse of research data to understand impact and reassure researchers. A new service called IRUS for Data will provide metrics for data repositories across different platforms.
2. There is debate around what data citations mean and how they should be used and understood. Projects are working to develop best practices and encourage responsible use of citation metrics for data.
3. Ensuring research data sharing is recognized in existing systems like journal policies is challenging due to lack of standards. Initiatives are working with publishers and repositories to develop guidance and implement principles for data citation.
This document summarizes a webinar for the Research Data Discovery Service Phase 3 project. The webinar agenda included project updates, a review of the latest system status including harvesting and requirements, a discussion of metadata, an overview of next steps for Phase 3, and time for questions. Participants were encouraged to provide feedback and help test the beta version of the system as it is further developed into a production research data discovery service.
Rachel Bruce, deputy chief innovation officer at Jisc talking about the feedback from the research data shared service pilots on DMP. Research Data Network, York
This document describes Spotlight Data, a company that uses text mining, machine learning, and data visualization to help with research data management. It introduces key members of Spotlight Data's team and describes some of their current projects, including work with the UK government and Durham University applying text mining and machine learning to large datasets. It also provides an overview of Spotlight Data's Nanowire system for ingesting, processing, and analyzing both structured and unstructured data at scale using a microservices architecture.
The document provides an overview of the UK research data discovery service, which aggregates research data from universities and national data centers to enable discovery of UK research data. It describes the pilot and development of the service, including participating organizations, requirements gathering, and next steps to transition the beta service into a production service. The demonstration shows the search capabilities of the beta discovery service platform.
Northumbria University is working to implement a robust research data management (RDM) solution. It has engaged in several activities to assess current RDM practices and infrastructure needs, including interviews with grant holders, a survey of researchers, and workshops with the Digital Curation Centre. Through these workshops, the university used the RISE model to evaluate its capabilities for data ingest, access, preservation, and more across several potential repository platforms. This helped provide evidence to secure budget and staffing to pilot and roll out a new RDM system starting in 2018. The university aims to go to procurement in September 2017 after finalizing business requirements and an options appraisal.
1. Metrics are being developed to track downloads and reuse of research data to understand impact and reassure researchers. A new service called IRUS for Data will provide metrics for data repositories across different platforms.
2. There is debate around what data citations mean and how they should be used and understood. Projects are working to develop best practices and encourage responsible use of citation metrics for data.
3. Ensuring research data sharing is recognized in existing systems like journal policies is challenging due to lack of standards. Initiatives are working with publishers and repositories to develop guidance and implement principles for data citation.
This document summarizes a webinar for the Research Data Discovery Service Phase 3 project. The webinar agenda included project updates, a review of the latest system status including harvesting and requirements, a discussion of metadata, an overview of next steps for Phase 3, and time for questions. Participants were encouraged to provide feedback and help test the beta version of the system as it is further developed into a production research data discovery service.
Rachel Bruce, deputy chief innovation officer at Jisc talking about the feedback from the research data shared service pilots on DMP. Research Data Network, York
This document describes Spotlight Data, a company that uses text mining, machine learning, and data visualization to help with research data management. It introduces key members of Spotlight Data's team and describes some of their current projects, including work with the UK government and Durham University applying text mining and machine learning to large datasets. It also provides an overview of Spotlight Data's Nanowire system for ingesting, processing, and analyzing both structured and unstructured data at scale using a microservices architecture.
The document provides an overview of the UK research data discovery service, which aggregates research data from universities and national data centers to enable discovery of UK research data. It describes the pilot and development of the service, including participating organizations, requirements gathering, and next steps to transition the beta service into a production service. The demonstration shows the search capabilities of the beta discovery service platform.
Northumbria University is working to implement a robust research data management (RDM) solution. It has engaged in several activities to assess current RDM practices and infrastructure needs, including interviews with grant holders, a survey of researchers, and workshops with the Digital Curation Centre. Through these workshops, the university used the RISE model to evaluate its capabilities for data ingest, access, preservation, and more across several potential repository platforms. This helped provide evidence to secure budget and staffing to pilot and roll out a new RDM system starting in 2018. The university aims to go to procurement in September 2017 after finalizing business requirements and an options appraisal.
The document summarizes a workshop on interoperability between grant funding systems. Key points discussed include:
- Desire to reduce duplication by allowing data to be shared between research organization and funding council systems.
- Initial outcomes from the workshop on possible ways to share data on costs, people, students, spending, and outcomes.
- Barriers to interoperability include the diversity of research organization systems and incomplete adoption of standards.
- The new grants system will take an agile approach, gradually introducing functionality based on user research and testing.
UK Research Data Discovery Service metadata schemaJisc RDM
An overview of the metadata schema being developed for the UK research data discovery service. Dom Fripp at the Research Data Network event at Cardiff University, May 2016.
This document provides an overview and agenda for a research data network event focusing on research data management. The event aims to discuss latest developments in RDM tools and services, share ideas and practices, and network. Presentations from the event will be shared online. Logistics like wifi access and note sharing are provided. The document also includes an agenda item on business case and costing for RDM that will discuss pain points around tracking costs, cost recovery, and evaluating benefits of RDM. It will share outputs from a Jisc project on developing business cases and costing models for RDM.
Presented by Peter Burnhill at e-Journals are forever? Preservation and Continuing Access to e-journal Content. A DPC, EDINA and JISC joint initiative, British Library, London, 26 April 2010.
1) The document outlines the PECAN Phase 2 project which developed a prototype entitlement registry to match up title information with institutional subscriptions and post-cancellation entitlement.
2) Key components of the prototype included designing an entitlement registry demonstrator to ingest and display data, assessing methods for automating data ingestion and maintaining record accuracy over time.
3) Challenges identified included the dynamic nature of deals and titles, defining packages, and developing standard data formats and workflows for publisher data supply to minimize manual intervention.
The document discusses a project to make OpenURL activity data more openly available and develop prototype services using the anonymized data. The data includes date/time, anonymized IP addresses and institution IDs, and OpenURL request data. Potential uses include article/journal recommendations, student/research analysis, and publisher comparisons. The project aims to license the aggregated level 2 data under an open license, extend the openurl.ac.uk site, and explore including other institutions' data.
National data services lightening talk at the RDAJisc RDM
Our slides for the lightening talk at the annual RDA in Tokyo. All about the national shared services to support research data infrastructure. March 2016.
Research at risk: developing a shared research data management service for UK...Jisc RDM
Rachel Bruce presented on Jisc's plans to develop a shared research data management service for UK universities. The service aims to help universities meet research funder requirements for data management and sharing in a cost effective way. It will provide services such as storage, metadata, and tools to help with data discovery and reuse. Jisc conducted surveys that found universities wanted services for preservation, automation, integration, and reducing their IT burden. The shared service is being developed through 2017 based on requirements identified.
The document discusses a project to investigate using Archivematica, an open-source digital preservation system, to provide digital preservation functionality for research data at the Universities of Hull and York. The project involved three phases: exploring Archivematica and research data needs, developing Archivematica features, and implementing proof-of-concept systems at both universities. Key findings included that Archivematica could meet many preservation needs but had limitations identifying research file formats, and that collaboration was important for addressing challenges in preserving research data long-term.
Preservation of Research Data: Dataverse / Archivematica Integration by Allan...datascienceiqss
Scholars Portal, a program of the Ontario Council of University Libraries (OCUL), provides the technical infrastructure to store, preserve, and provide access to shared digital library collections in Ontario - including hosting a local instance of Dataverse since 2011. As part of a national project known as Portage (a project of the Canadian Association of Research Libraries), Scholars Portal is partnering with Artefactual Systems, Dataverse, the University of British Columbia, the University of Alberta, and others, to integrate Dataverse with preservation software Archivematica. When completed, this project will facilitate the long-term preservation of research data according to the Open Archival Information System (OAIS) Reference Model.
The document summarizes a workshop on interoperability between grant funding systems. Key points discussed include:
- Desire to reduce duplication by allowing data to be shared between research organization and funding council systems.
- Initial outcomes from the workshop on possible ways to share data on costs, people, students, spending, and outcomes.
- Barriers to interoperability include the diversity of research organization systems and incomplete adoption of standards.
- The new grants system will take an agile approach, gradually introducing functionality based on user research and testing.
UK Research Data Discovery Service metadata schemaJisc RDM
An overview of the metadata schema being developed for the UK research data discovery service. Dom Fripp at the Research Data Network event at Cardiff University, May 2016.
This document provides an overview and agenda for a research data network event focusing on research data management. The event aims to discuss latest developments in RDM tools and services, share ideas and practices, and network. Presentations from the event will be shared online. Logistics like wifi access and note sharing are provided. The document also includes an agenda item on business case and costing for RDM that will discuss pain points around tracking costs, cost recovery, and evaluating benefits of RDM. It will share outputs from a Jisc project on developing business cases and costing models for RDM.
Presented by Peter Burnhill at e-Journals are forever? Preservation and Continuing Access to e-journal Content. A DPC, EDINA and JISC joint initiative, British Library, London, 26 April 2010.
1) The document outlines the PECAN Phase 2 project which developed a prototype entitlement registry to match up title information with institutional subscriptions and post-cancellation entitlement.
2) Key components of the prototype included designing an entitlement registry demonstrator to ingest and display data, assessing methods for automating data ingestion and maintaining record accuracy over time.
3) Challenges identified included the dynamic nature of deals and titles, defining packages, and developing standard data formats and workflows for publisher data supply to minimize manual intervention.
The document discusses a project to make OpenURL activity data more openly available and develop prototype services using the anonymized data. The data includes date/time, anonymized IP addresses and institution IDs, and OpenURL request data. Potential uses include article/journal recommendations, student/research analysis, and publisher comparisons. The project aims to license the aggregated level 2 data under an open license, extend the openurl.ac.uk site, and explore including other institutions' data.
National data services lightening talk at the RDAJisc RDM
Our slides for the lightening talk at the annual RDA in Tokyo. All about the national shared services to support research data infrastructure. March 2016.
Research at risk: developing a shared research data management service for UK...Jisc RDM
Rachel Bruce presented on Jisc's plans to develop a shared research data management service for UK universities. The service aims to help universities meet research funder requirements for data management and sharing in a cost effective way. It will provide services such as storage, metadata, and tools to help with data discovery and reuse. Jisc conducted surveys that found universities wanted services for preservation, automation, integration, and reducing their IT burden. The shared service is being developed through 2017 based on requirements identified.
The document discusses a project to investigate using Archivematica, an open-source digital preservation system, to provide digital preservation functionality for research data at the Universities of Hull and York. The project involved three phases: exploring Archivematica and research data needs, developing Archivematica features, and implementing proof-of-concept systems at both universities. Key findings included that Archivematica could meet many preservation needs but had limitations identifying research file formats, and that collaboration was important for addressing challenges in preserving research data long-term.
Preservation of Research Data: Dataverse / Archivematica Integration by Allan...datascienceiqss
Scholars Portal, a program of the Ontario Council of University Libraries (OCUL), provides the technical infrastructure to store, preserve, and provide access to shared digital library collections in Ontario - including hosting a local instance of Dataverse since 2011. As part of a national project known as Portage (a project of the Canadian Association of Research Libraries), Scholars Portal is partnering with Artefactual Systems, Dataverse, the University of British Columbia, the University of Alberta, and others, to integrate Dataverse with preservation software Archivematica. When completed, this project will facilitate the long-term preservation of research data according to the Open Archival Information System (OAIS) Reference Model.
Project update: A collaborative approach to "filling the digital preservation...Jenny Mitcham
A presentation given by Julie Allinson at the UK Archivematica group meeting on 6th November 2015 in Leeds. It describes work underway in the "Filling the Digital Preservation Gap" project using Archivematica to preserve research data
"Filling the Digital Preservation Gap" with ArchivematicaJenny Mitcham
A webinar given by Jenny Mitcham and Simon Wilson to Digital Preservation Coalition members on 25th November 2015. It describes work underway in the "Filling the Digital Preservation Gap" project using Archivematica to preserve research data
This document discusses various strategies and resources for archiving internet content for research purposes. It describes several existing large-scale web archives like the Internet Archive and Common Crawl, as well as national and institutional archives. It also outlines how researchers can collect targeted web archives using open-source tools or subscription-based services.
The document provides an introduction to PREMIS (Preservation Metadata: Implementation Strategies) and its application in audiovisual archives. It discusses the challenges of digital preservation and the need for preservation metadata to ensure long-term access. It then summarizes the key aspects of PREMIS, including the PREMIS Data Dictionary, its relationship to the OAIS reference model, the five interacting entities in the PREMIS data model, and issues around implementing PREMIS in archives.
A collaborative approach to "filling the digital preservation gap" for Resear...Jenny Mitcham
A presentation given by Chris Awre, Jenny Mitcham and Sarah Romkey at RDMF14 (the DCC's Research Data Management Forum) on 9th November 2015 in York. It describes work underway in the "Filling the Digital Preservation Gap" project using Archivematica to preserve research data
Repositories are systems to safely store and publish digital objects and their descriptive metadata. Repositories mainly serve their data by using web interfaces which are primarily oriented towards human consumption. They either hide their data behind non-generic interfaces or do not publish them at all in a way a computer can process easily. At the same time the data stored in repositories are particularly suited to be used in the Semantic Web as metadata are already available. They do not have to be generated or entered manually for publication as Linked Data. In my talk I will present a concept of how metadata and digital objects stored in repositories can be woven into the Linked (Open) Data Cloud and which characteristics of repositories have to be considered while doing so. One problem it targets is the use of existing metadata to present Linked Data. The concept can be applied to almost every repository software. At the end of my talk I will present an implementation for DSpace, one of the software solutions for repositories most widely used. With this implementation every institution using DSpace should become able to export their repository content as Linked Data.
1) The document outlines Muhammad Ans Jamil's masters research project which involves conducting a scoping review on emerging data storage technologies.
2) The project involves identifying key concepts and literature on the topic, selecting relevant research articles, and presenting and writing up the findings.
3) The method section describes searching databases like Science Direct and Google Scholar to find recent articles on topics like emerging storage technologies and DNA storage using keywords and filters.
Steven McEachern - ADA, DDI (metadata standard) and the Data LifecycleSteve Androulakis
Dr. McEachern is Director of the Australian Data Archive at the Australian National University, and has research interests in data management and archiving, community and social attitude surveys, new data collection methods, and reproducible research methods.
This talk was given for the Monthly Tech Talks event hosted by Australian data infrastructure groups ANDS, NeCTAR, RDS and others.
A collaborative approach to "filling the digital preservation gap" for Resear...Jenny Mitcham
A presentation given by Jenny Mitcham at the Northern Collaboration Conference on 10th September 2015 at Leeds. It describes work underway in the "Filling the Digital Preservation Gap" project using Archivematica to preserve research data
A collaborative approach to filling the digital preservation gap for RDMnortherncollaboration
This document discusses a collaborative project between the University of Hull and University of York to investigate how the digital preservation system Archivematica could be used to provide digital preservation functionality for research data management. The project aims to test Archivematica, make it better suited for research data, and set up proof of concepts at both universities. Archivematica packages data in a standard way for long-term preservation, and could be incorporated into research data workflows and linked to other systems. While it has limitations, it offers a flexible way to help address the "digital preservation gap" in research data infrastructure.
“Filling the digital preservation gap”an update from the Jisc Research Data ...Jenny Mitcham
This document summarizes the findings of the Jisc Research Data Spring project at the University of York and Hull which investigated how Archivematica could be used to provide digital preservation for research data. The project tested Archivematica, explored how it handles different file formats and research data, and identified ways to improve Archivematica and integrate it into research data management workflows. The next phases will develop Archivematica further and implement proof of concepts at York and Hull to preserve research data using Archivematica.
This document describes the PDS Imaging Node AIMS Inventory Component project. The project aims to (1) crawl through a 700TB digital image archive to extract metadata from each file and directory, (2) represent each item as an "Archive Product" object, (3) index and store the Archive Products to build an inventory of the archive that can be easily queried. It utilizes various open source tools like Apache OODT, Solr, and File Manager to extract metadata, index the Archive Products, and build a searchable inventory of the archive. Future work includes utilizing additional tools to build a richer user interface for searching the documentation.
In this session, we’ll focus exclusively on OpenStack Swift, OpenStack’s object store capability. We’ll review the architecture, use cases, deployment strategies and common obstacles as we “open up the covers” on this exciting element of the OpenStack architecture.
The document provides an overview of BagIt, an open source file packaging format developed by the Library of Congress to facilitate the transfer of digital content. It describes how BagIt works, the steps involved in using it, and its evolution and adoption by other institutions. Key points include that a BagIt package contains files bundled with metadata in a machine-readable format allowing for automated validation and ingestion. The format has been adapted to various programming environments and seen broader community involvement over time.
This document provides an overview of existing web archives and their use for research. It discusses several major web archives including the Internet Archive, Common Crawl, Pandora Archive, and national archives. For each, it describes their size and collection strategies, as well as positives and negatives for research use. The talk concludes with examples of how existing web archives in Australia are being used for research.
Update on the Bentley Historical Library's ArchivesSpace Archivematica DSpace Workflow Integration project, with development provided by Artefactual Systems.
Similar a From Box to Hydra via Archivematica (20)
Recent national and international mandates and reports seek to promote an open research infrastructure which facilitates easy access to knowledge and information for all. For example, The UK Open Research Data Task Force report, released in February 2019, recommends user-friendly services for research data management and infrastructure to maximise interoperability and discoverability.
Jisc has built the Open Research Hub (JORH), which integrates a repository, preservation, reporting and storage platform. This cloud-based service is a community governed, multi-tenant solution for universities and other research institutions to manage, store, preserve and share their published research data. Based on existing open standards, the service’s open and extensive data model incorporates best practice from across the sector, including DataCite, CrossRef, CERIF, Dublin Core and PREMIS.
While the Hub was built to address the needs of research data curation, its adoption of open, best practice standards means it has the potential to allow the service to handle a much wider range of digital research objects, including Open Access articles, theses and software. The data model, rich messaging layer and an open API facilitate interoperability with other institutional and scholarly communications systems. This provides the potential for the Hub to underpin infrastructure capable of meeting the requirements of an ever-evolving open research agenda.
This talk will introduce some of the key initiatives seeking to shape open research infrastructure and discuss how the Hub’s current and future development is directed towards facilitating open research best practice. Consideration will be given to how the Hub either meets or can meet recent recommendations such as FAIR, Plan S, ORDTF and the COAR’s Next Generation Repositories.
Jisc Research Data Shared Service Open Repositories 2018 PaperJisc RDM
The document discusses Jisc's plans to develop a national research data shared service in the UK. It provides context on open science policies and the need for research data management and preservation. It then summarizes Jisc's proposal to create a multi-tenant research repository with integrated preservation systems. This would provide a scalable, sustainable platform to help universities meet requirements for managing and preserving research outputs including data, software, and publications. The service is currently in development with pilots planned, and would offer repositories, preservation, or an end-to-end solution to members.
Jisc Research Data Shared Service Open Repositories 2018 24x7Jisc RDM
This document discusses the Jisc Research Data Shared Service (RDSS) and its priorities and developments. The RDSS aims to provide a scalable, sustainable, and intuitive shared research data service. It offers three standard service options - an end-to-end service, repository service, and preservation service. The RDSS is working on developing a multi-tenant research repository and integrating with other Jisc services to support the full research lifecycle from publication to preservation. Further developments include preservation action registries and a potential national shared research platform.
Jisc Research Data Shared Service - a Samvera case studyJisc RDM
As part of its Research Data Shared Service (RDSS), Jisc has been developing a repository component as part of its core architecture . Through making an integrated research data management platform available to UK Universities, there is a growing demand from small to medium HEIs for the RDSS to provide a single repository solution that fits their needs for publications and data with workflows for Open Access and REF submissions. To achieve this, the repository must be integrated with other Jisc Open Access services such as Sherpa, Jisc Monitor and Publications router, along with those provided by external stakeholders such as ORCID, Crossref, DataCite and OpenAIRE.
This presentation is a case study in evaluating Samvera for this role, and its suitability as a multi-tenanted, sustainable hybrid repository that is both attractive to researchers and universities and aligns with the broader international objectives of the community, the FAIR agenda and open science.
Building a national Data Repository Data ModellingJisc RDM
This document outlines an agenda for a Jisc workshop on data modelling. The workshop will cover StarUML for data modelling, the Jisc Research Data Shared Service conceptual architecture, the canonical data model on GitHub, modelling for interoperability, making data FAIR according to metadata principles, a recent FAIR practices report, content modelling and content models, mapping between the canonical data model and CERIF standard, and an exercise for participants to build their own content model.
Building a national Data Repository System Integration Architecture OverviewJisc RDM
This document discusses publish-subscribe (pub-sub) messaging and how it was implemented for RDSS integration architecture. Pub-sub messaging uses asynchronous and decoupled integration mechanisms like files, databases or APIs to transmit messages. It outlines the lifecycle of a message and why pub-sub messaging provides benefits like operability, architectural compliance, and reliability. Finally, it provides references to the message specification, structure, transport and application behavior used for the pub-sub implementation.
Building a National Data Service Open Repositories 2018Jisc RDM
This document outlines the agenda and introductory information for a workshop on building a national research data service in the UK. The agenda covers introducing the Jisc Research Data Shared Service (RDSS) and demonstrating its data modeling and system integration architecture. Participants will have interactive sessions on workflows, events, and integrations. Speakers will include representatives from Jisc, Figshare, and Digirati discussing their experiences with RDSS. Jisc aims to create a shared, interoperable research data infrastructure for UK universities to better manage research data across institutions.
The Jisc RDMToolkit document discusses the development of a Research Data Management (RDM) toolkit by Jisc and Research Consulting. It provides a sneak peek of the toolkit, which gathers over 100 RDM resources and arranges them using a research data lifecycle model. The toolkit is built on a WordPress template for easy editing and will be maintained by a working group. It will undergo a thorough review after three years.
Stories from the Field: Data are Messy and that's (kind of) okJisc RDM
This document introduces Jude Towers and David Ellis, who are lecturers focused on quantitative methods and computational social science. They discuss how data can be messy, including inconsistencies in concepts and definitions, difficulties in data collection, and the politics of data cleaning. They argue that while data is imperfect, it is still useful for understanding society when the signal is distinguished from the noise. They provide two examples of working with messy real-world data: administrative health records from the NHS and social science replication problems. Their overall goal is to help people critically engage with quantitative data.
'Making the case for a research data shared service' in the Measuring Success and Changing Culture session Presented during the National RDM Strategies session of the Göttingen-CODATA RDM Symposium 2018
Research Data Shared Service update at DPCJisc RDM
The document discusses the Jisc Research Data Shared Service (RDSS) and its role in coordinating the preservation and sharing of research data. RDSS aims to provide core functionality for researchers to deposit, describe, store, publish, and ensure the integrity of their research data. It will also offer advice and best practices for research data management. The service coordinates efforts across universities and involves partnerships with other organizations to develop shared technology solutions for preserving UK research outputs.
The webinar discussed Jisc's proposal for a Research Data Shared Service (RDSS) to address issues with research data management across UK higher education institutions. The RDSS would provide cost-effective solutions for depositing, describing, storing, publishing, and preserving research data through standardized technology and shared expertise. An alpha version was being piloted with 16 institutions and would include repository, preservation, and advisory services. The goal was to increase access to and reuse of research data while reducing costs and risks for institutions.
Managing data behind creative masterpiecesJisc RDM
The document discusses research data in creative fields and Jisc's Research Data Shared Service (RDSS) to help manage such data. RDSS aims to enable open science through efficient capture, preservation and reuse of research data. It will provide core functions like deposit, description, storage, publication and preservation of data, as well as reporting and advisory services. RDSS addresses key issues in research data management to help reduce costs and risks for researchers and institutions.
This document provides an agenda for a lightning talks session taking place on June 27th, 2017. It lists 8 presenters, their institutions, and the titles of their short presentations. Topics will include the role of archivists in research data management, the HYDRA and SAMVERA platforms, open research at the University of Leeds, the THOR project, shared data center services, monitoring institutional compliance with RDM policy, and understanding what constitutes research data. The document also provides contact information for the session organizer.
Title: Monitoring institutional compliance with RDM policy
database that is used by the team to monitor compliance.
Research Data Network
University of Strathclyde
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!"
How to Setup Warehouse & Location in Odoo 17 InventoryCeline George
In this slide, we'll explore how to set up warehouses and locations in Odoo 17 Inventory. This will help us manage our stock effectively, track inventory levels, and streamline warehouse operations.
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.
Beyond Degrees - Empowering the Workforce in the Context of Skills-First.pptxEduSkills OECD
Iván Bornacelly, Policy Analyst at the OECD Centre for Skills, OECD, presents at the webinar 'Tackling job market gaps with a skills-first approach' on 12 June 2024
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 ...।
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1. From Box to Hydra via Archivematica
Turning proof of concept into reality
2. Background
• University of Hull and University of York working on a Research Data Spring
project
• Filling the digital preservation gap, 2015-16
• https://www.york.ac.uk/borthwick/projects/archivematica/
• Dual use cases for the University of Hull
• Digital preservation of archival materials
• Management and preservation of research data
3. Systems background
• Box
• Institutional subscription from 2015
• Supported and managed personal cloud storage service
• Archivematica
• No experience prior to the project, but had watched its development over a period
of years
• Particularly liked the combination of microservices that can be used flexibly
according to use case
4. Repository
• Hydra digital repository – http://hydra.hull.ac.uk
• Implemented 2012 based on previous Fedora repository
• Designed to hold any structured digital collection (within reason!) to meet
University’s needs
• NB ** Hydra is now Samvera **
• Community is refreshing and re-launching for the next decade
• Watch this space – http://samvera.org
• New website and logo coming shortly
5. Questions
• How can we enable a preservation workflow with the systems environment
available to us?
• How can we facilitate pathways to preserving archival materials and
research data alongside each other?
• What is required to bring these different components together to best
effect?
6. Ingest to the system, either direct
or via ingest folder (Box)
Archivematica captures content
and processes it through
microservices
Archivematica outputs AIP for
storage and DIP for repository
DIP processor unpacks DIPs and
creates repository objects
Repository manages access to
objects
7. Project focus
• User assembles files and simple descriptive file(s) in Box
folder. Shares the folder with Archivematica
• System checks folder contents and if OK creates a bag
(BagIt standard) for each object which is passed to
Archivematica
• Archivematica processes the bag to create an AIP which
goes to a preservation store…
• …and also a DIP which is passed to the DIP processor
• DIP processor creates Hydra objects from the DIP
contents and injects them into the repository QA
queue…
• …matched to the AIP by UUID
8. Joining up the dots
• The joins between the three components were:
• A ‘Box-watcher’ – users share their data with a nominated Box user account for the
archivematica system. This account watch for shares with it, and automatically
create a BAGIT of the files found and transfer this to archivematica for processing
• A ‘DIP processor’ – this takes the BAGIT DIP from archivematica, breaks it open and
uses the information within this to create repository objects
• These tools were wrapped into a single gem, hullsync
• https://github.com/uohull/hullsync
9. Deposit options
• Depositors have several options:
• A folder containing multiple data files and one descriptive file a single AIP and a single repository
object with (optionally) one or more surrogate files for download (so can be a “metadata-only”
record)
• A folder containing multiple files and a csv file (one row per file) multiple AIPs with multiple
repository objects, each with (optionally) a surrogate for download
• A folder containing the top-level folder of a structure a zipped structure in a single AIP and a single
repository object (optionally) containing the zipped file for download
10. In detail – option 1
• A folder containing multiple data files and one descriptive file a single
AIP and a single repository object with (optionally) one or more surrogate
files for download (so can be a “metadata-only” record)
• Data files are associated with a .txt descriptive file providing associated metadata
• Descriptive file can be used to determine access permissions and content model
• Descriptive metadata can be provided using Dublin Core
• Can also submit README.txt for information to inform repository staff on
appropriate actions
11. In detail – option 2
• A folder containing multiple files and a csv file (one row per file) multiple
AIPs with multiple repository objects, each with (optionally) a surrogate for
download
• Use a .csv file instead of a .txt file for the descriptive information
• Use column headings to cover the same fields as in option 1
• Can associate the same or different metadata with each object
• Can create simple or compound objects
12. In detail – option 3
• A folder containing the top-level folder of a structure a zipped structure
in a single AIP and a single repository object (optionally) containing the
zipped file for download
• Aim is to allow the submission of a folder or nested folders of data, replicating how
the files are organised
• Files are unpacked by Archivematica, analysed, and then re-zipped up for submission
to the repository
13. Lessons learned
• Error handling needs attention when turning the p-o-c into production
• But the testing highlighted a lot of the errors that would need handling
• A key element when joining systems together
• Normalisation of filetypes requires additional consideration
• E.g., how to deal with TIFF files converted to JPG
• The zipping and unzipping workflows require further attention to ensure
success for this option
14. Next steps
• Take learning and tools from the Research Data Spring project and use these
as the basis for development of services
• Two use cases
• Research data storage and management service development
• City of Culture digital archive
• Understanding Archivematica pipelines and options better – Perpetua test!
• Focus on improving proof-of-concept and developing additional
functionality
15.
16. Research data storage and management
• Joint Library and ICTD project to discover and understand research data
storage and management needs amongst academic staff
• Open workshops
• Data interviews
• Capture and processing of research data a part of local provision alongside
advice and guidance on options outside the institution
17. City of Culture digital archive
• Hull2017 – City of Culture
• Events throughout the year
• Four data elements
• Business archive
• Creative archive
• Participatory archive
• Research and evaluation archive
• Applying the same technology environment to manage ingest and delivery
18. Key issues going forward
• What are the differences in pipeline processing in Archivematica between
research data and archival materials?
• Dealing with unusual file formats – a key learning point from the RDS
project
• Scaling up to meet heavier data demands
• Being realistic about what we can’t use this environment for and need
alternative approaches, e.g., Big Data
19. To conclude
• Combining components has its issues, but it has been better to exploit
systems that do certain parts of the workflow well and turn them into more
than the sum of their parts
• Data is not simple
• We need flexibility in how we look to manage it
• We need engagement with researchers to understand it
• Turning an idea into production needs careful planning
• Scope for community exchange or training on how to do this?
20. Thank you
c.awre@hull.ac.uk
(And many thanks to the University of York and my colleagues Richard Green and
Simon Wilson, plus Cottage Labs LLC for their work on this)