The document discusses how data citation fits within data services for the Advanced Cooperative Arctic Data and Information Service (ACADIS) project. It identifies user needs for data citation like attribution, metrics tracking, and reproducibility. It also outlines current data service packages and proposes integrating data citation to meet user needs. Short-term steps are defined to collect citation metadata, enact versioning, clarify roles, and separate citations from identifiers. The document emphasizes aligning data services with user community priorities and using metadata to define responsibilities.
To architect or engineer? Lessons from DataPool on building RDM repositoriesjiscdatapool
There cannot be many mature products where development meetings have not been interrupted with a rueful declaration that to make further progress “you wouldn’t start from here”. This encapsulates one key difference between the architect and engineer, the latter prepared to work with the set of tools provided, the other preferring to start with a blank sheet of paper or an open space. In building research data repositories using two different softwares, Microsoft Sharepoint and EPrints, the DataPool Project is working somewhere between these extremes. Which approach will prove to be the more resilient for research data management (RDM)? In this talk we will look at the relevant factors.
These are the slides for Robert H. McDonald for the Future Trends Panel Presentation at the the Inter-institutional Approaches to Supporting Scholarly Communication Symposium held on August 16, 2012 at the Georgia Institute of Technology.
Relational Databases are Evolving To Support New Data CapabilitiesEDB
A commissioned study conducted by Forrester Consulting on behalf of EnterpriseDB, published in January 2015, presents a case study for the evolution of relational database management systems. The study, Relational Databases are Evolving to Support New Data Capabilities, found that the majority—78%—of database decisions makers wanted one solution that could handle relational and NoSQL data types.
The study finds that relational databases are evolving to address the needs of end users seeking to link unstructured and structured data types and that decision makers should look to invest in these solutions. EDB’s Postgres Plus Advanced Server, for example, addresses these needs with such capabilities as support for unstructured data types, non-durable tables, tools for large-scale data loads, and integration technologies that connect standalone NoSQL solutions with Postgres.
To architect or engineer? Lessons from DataPool on building RDM repositoriesjiscdatapool
There cannot be many mature products where development meetings have not been interrupted with a rueful declaration that to make further progress “you wouldn’t start from here”. This encapsulates one key difference between the architect and engineer, the latter prepared to work with the set of tools provided, the other preferring to start with a blank sheet of paper or an open space. In building research data repositories using two different softwares, Microsoft Sharepoint and EPrints, the DataPool Project is working somewhere between these extremes. Which approach will prove to be the more resilient for research data management (RDM)? In this talk we will look at the relevant factors.
These are the slides for Robert H. McDonald for the Future Trends Panel Presentation at the the Inter-institutional Approaches to Supporting Scholarly Communication Symposium held on August 16, 2012 at the Georgia Institute of Technology.
Relational Databases are Evolving To Support New Data CapabilitiesEDB
A commissioned study conducted by Forrester Consulting on behalf of EnterpriseDB, published in January 2015, presents a case study for the evolution of relational database management systems. The study, Relational Databases are Evolving to Support New Data Capabilities, found that the majority—78%—of database decisions makers wanted one solution that could handle relational and NoSQL data types.
The study finds that relational databases are evolving to address the needs of end users seeking to link unstructured and structured data types and that decision makers should look to invest in these solutions. EDB’s Postgres Plus Advanced Server, for example, addresses these needs with such capabilities as support for unstructured data types, non-durable tables, tools for large-scale data loads, and integration technologies that connect standalone NoSQL solutions with Postgres.
Improving user engagement in a data repository with web analyticsIUPUI
Presented at LITA Forum 2013
Abstract: A goal of data curation activities is to enable discovery and reuse of valuable data sets. How well repositories facilitate these activities is difficult to measure with existing metrics. In this presentation we will discuss how to utilize usage statistics from DSpace (Apache SOLR) and Google Analytics to better understand how researchers discover, access, and use datasets archived in an institutional repository. Our focus will be on data analysis to explore the information seeking needs and behavior of data repository users. Ultimately, this analytic approach will inform the outreach, marketing, and impact evaluation of data repositories.
Also available at: http://hdl.handle.net/1805/3665
Meeting the NSF DMP Requirement June 13, 2012IUPUI
June 13 version of the IUPUI workshop Meeting the NSF Data Management Plan Requirement: What you need to know. This workshop is co-sponsored by the Office of the Vice Chancellor for Research and the University Library.
Presentation given at the Indiana University School of Medicine's Ruth Lilly Medical Library. Contains information and resources specific to Indiana University Purdue University Indianapolis (IUPUI). For full class materials, see LYD17_IUPUIWorkshop folder here: https://osf.io/r8tht/.
Data Curation Models JHU Barbara Pralle RDAP12ASIS&T
Data Curation Services Models: John Hopkins University
Barbara Pralle
Curation Service Models panel
Presentation at Research Data Access & Preservation Summit
22 March 2012
ESI Supplemental 1 E-research Support SlidesDuraSpace
E-Research Support at
Johns Hopkins University & Purdue University
Supplemental Webinar
Wednesday, October 17, 2012
Presented by Sayeed Choudhurry & James Mullins
Good systems development often depends on multiple data management disciplines that provide a solid foundation. One of these is metadata. While much of the discussion around metadata focuses on understanding metadata itself along with its associated technologies, this perspective often represents a typical tool-and-technology focus, which has not achieved significant results to date. A more relevant question when considering pockets of metadata is whether to include them in the scope of organizational metadata practices. By understanding what it means to include items in the scope of your metadata practices, you can begin to build systems that allow you to practice sophisticated ways to advance their data management and supported business initiatives. After a bit of practice in this manner you can position your organization to better exploit any and all metadata technologies in support of business strategy.
Find more data management webinars here: http://www.datablueprint.com/resource-center/webinar-schedule/
Improving user engagement in a data repository with web analyticsIUPUI
Presented at LITA Forum 2013
Abstract: A goal of data curation activities is to enable discovery and reuse of valuable data sets. How well repositories facilitate these activities is difficult to measure with existing metrics. In this presentation we will discuss how to utilize usage statistics from DSpace (Apache SOLR) and Google Analytics to better understand how researchers discover, access, and use datasets archived in an institutional repository. Our focus will be on data analysis to explore the information seeking needs and behavior of data repository users. Ultimately, this analytic approach will inform the outreach, marketing, and impact evaluation of data repositories.
Also available at: http://hdl.handle.net/1805/3665
Meeting the NSF DMP Requirement June 13, 2012IUPUI
June 13 version of the IUPUI workshop Meeting the NSF Data Management Plan Requirement: What you need to know. This workshop is co-sponsored by the Office of the Vice Chancellor for Research and the University Library.
Presentation given at the Indiana University School of Medicine's Ruth Lilly Medical Library. Contains information and resources specific to Indiana University Purdue University Indianapolis (IUPUI). For full class materials, see LYD17_IUPUIWorkshop folder here: https://osf.io/r8tht/.
Data Curation Models JHU Barbara Pralle RDAP12ASIS&T
Data Curation Services Models: John Hopkins University
Barbara Pralle
Curation Service Models panel
Presentation at Research Data Access & Preservation Summit
22 March 2012
ESI Supplemental 1 E-research Support SlidesDuraSpace
E-Research Support at
Johns Hopkins University & Purdue University
Supplemental Webinar
Wednesday, October 17, 2012
Presented by Sayeed Choudhurry & James Mullins
Good systems development often depends on multiple data management disciplines that provide a solid foundation. One of these is metadata. While much of the discussion around metadata focuses on understanding metadata itself along with its associated technologies, this perspective often represents a typical tool-and-technology focus, which has not achieved significant results to date. A more relevant question when considering pockets of metadata is whether to include them in the scope of organizational metadata practices. By understanding what it means to include items in the scope of your metadata practices, you can begin to build systems that allow you to practice sophisticated ways to advance their data management and supported business initiatives. After a bit of practice in this manner you can position your organization to better exploit any and all metadata technologies in support of business strategy.
Find more data management webinars here: http://www.datablueprint.com/resource-center/webinar-schedule/
Using Feedback from Data Consumers to Capture Quality Information on Environm...Anusuriya Devaraju
Data quality information is essential to facilitate reuse of Earth science data. Recorded quality information must be sufficient for other researchers to select suitable data sets for their analysis and confirm the results and conclusions. In the research data ecosystem, several entities are responsible for data quality. Data producers (researchers and agencies) play a major role in this aspect as they often include validation checks or data cleaning as part of their work. It is possible that the quality information is not supplied with published data sets; if it is available, the descriptions might be incomplete, ambiguous or address specific quality aspects. Data repositories have built infrastructures to share data, but not all of them assess data quality. They normally provide guidelines of documenting quality information. Some suggests that scholarly and data journals should take a role in ensuring data quality by involving reviewers to assess data sets used in articles, and incorporating data quality criteria in the author guidelines. However, this mechanism primarily addresses data sets submitted to journals. We believe that data consumers will complement existing entities to assess and document the quality of published data sets. This has been adopted in crowd-source platforms such as Zooniverse, OpenStreetMap, Wikipedia, Mechanical Turk and Tomnod. This paper presents a framework designed based on open source tools to capture and share data users’ feedback on the application and assessment of research data. The framework comprises a browser plug-in, a web service and a data model such that feedback can be easily reported, retrieved and searched. The feedback records are also made available as Linked Data to promote integration with other sources on the Web. Vocabularies from Dublin Core and PROV-O are used to clarify the source and attribution of feedback. The application of the framework is illustrated with the CSIRO’s Data Access Portal.
Supporting Libraries in Leading the Way in Research Data ManagementMarieke Guy
Marieke Guy, Institutional Support Officer, Digital Curation Centre, UKOLN, University of Bath, UK presents on Supporting Libraries in Leading the Way in Research Data Management at Online Information, London 20th -21st November 2012
Meeting the NSF DMP Requirement: March 7, 2012IUPUI
March 7 version of the IUPUI workshop Meeting the NSF Data Management Plan Requirement: What you need to know. This workshop is co-sponsored by the Office of the Vice Chancellor for Research and the University Library.
This presentation was provided by Tim McGeary of Duke University during the NISO virtual conference, Open Data Projects, held on Wednesday, June 13, 2018.
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors.
And...
Speakers:
Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
DevOps and Testing slides at DASA ConnectKari Kakkonen
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In this presentation, we examine the challenges and limitations of relying too heavily on PHP frameworks in web development. We discuss the history of PHP and its frameworks to understand how this dependence has evolved. The focus will be on providing concrete tips and strategies to reduce reliance on these frameworks, based on real-world examples and practical considerations. The goal is to equip developers with the skills and knowledge to create more flexible and future-proof web applications. We'll explore the importance of maintaining autonomy in a rapidly changing tech landscape and how to make informed decisions in PHP development.
This talk is aimed at encouraging a more independent approach to using PHP frameworks, moving towards a more flexible and future-proof approach to PHP development.
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
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https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
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Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
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• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
• Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
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Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
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Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
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2. Heatmap utilization for testing
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Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...
Ucar data citationworkshop_yarmey_20120405
1. Data Citation as a Service
Lynn Yarmey – UCAR Data Citation Workshop – April 5-6, 2012
2. Background
• Conversation started in the context of defining
‘Levels of Service’ for ACADIS data
Lynn Yarmey – UCAR Data Citation Workshop – April 5-6, 2012 Program Logo
3. Background (overly simplified)
• Conversation started in the context of defining
‘Levels of Service’ for ACADIS data
Approach for prescribing services for incoming data sets
given the assumption that these data sets do not have the
same needs, resources, and user communities.
Lynn Yarmey – UCAR Data Citation Workshop – April 5-6, 2012 Program Logo
4. Background (overly simplified)
• Conversation started in the context of defining
‘Levels of Service’ for ACADIS data
Advanced Cooperative Arctic Data and Information Service –
A collaborative (NSIDC, NCAR-CISL, NCAR-EOL, Unidata)
data service project to support the collection, description,
distribution, and archiving of NSF-funded Arctic research data.
Lynn Yarmey – UCAR Data Citation Workshop – April 5-6, 2012 Program Logo
5. Data Service Packages
• Planning and collection
• Discovery
• Distribution
• Readability/Reuse
• Archiving
• Visualization
• Interoperability
Lynn Yarmey – UCAR Data Citation Workshop – April 5-6, 2012 Program Logo
6. But…
• Planning and collection
• Discovery
• Distribution
• Readability/Reuse
• Archiving
• Visualization
• Interoperability
Where does data citation fit?
Lynn Yarmey – UCAR Data Citation Workshop – April 5-6, 2012 Program Logo
7. Approach
Disambiguate
‘Data Citation’
and
‘Data Service’
Lynn Yarmey – UCAR Data Citation Workshop – April 5-6, 2012 Program Logo
8. Approach
‘Data Citation’
Citation Metadata
Access Mechanism
+
‘Data Service’
Defined Need + User Community
Lynn Yarmey – UCAR Data Citation Workshop – April 5-6, 2012 Program Logo
9. Defined needs for data citations
• Data Locator
• Mechanism for professional recognition
§ Claiming attribution
• Tracking reuse statistics (metrics)
• Following citations (chaining)
• Connect data and resulting scholarship
• Referencing data used in support of scholarship
§ Supporting reproducibility
• Assurance of long-term support (?)
Lynn Yarmey – UCAR Data Citation Workshop – April 5-6, 2012 Program Logo
10. Generalized User Communities
• Data Authors/Submitters
§ Mechanism for professional recognition
§ Connecting data and resulting scholarship
§ Following citations (chaining)
§ Assurance of long-term support (?)
• Data Reusers/Downloaders
§ Data Locator
§ Specifying data used in support of scholarship
§ Following citations (chaining)
Lynn Yarmey – UCAR Data Citation Workshop – April 5-6, 2012 Program Logo
11. Bringing these together…(work in progress!)
Service Packages
User Needs
Data Locator
Planning and collection
Claiming attribution
Discovery Tracking reuse statistics
Distribution Following citations
Readability/Reuse Connect data and resulting
Archiving scholarship
Referencing data used in support
Visualization
of scholarship
Interoperability Supporting reproducibility
Assurance of long-term support
Lynn Yarmey – UCAR Data Citation Workshop – April 5-6, 2012 Program Logo
12. Implications
• Where in the data workflow citation/persistent
identifier are applied
• The granularity of citation application
• The object defined for persistent identification
• Workflow for citation assignment
• Roles
§ What is the role of the PI/data author?
§ What are the roles and responsibilities for data service
groups?
o What expertise is required to fulfill these?
Lynn Yarmey – UCAR Data Citation Workshop – April 5-6, 2012 Program Logo
13. Short-term steps for ACADIS
• Collect citation metadata
• Enact data versioning
• Distinguish citation recommendations and assignment
§ We can recommend citations for all data sets (we have
the metadata!)
§ But we will only assign citations to data sets with data
submitted (proposed)
§ …
Lynn Yarmey – UCAR Data Citation Workshop – April 5-6, 2012 Program Logo
14. Short-term steps for ACADIS
• …
• Separate application of citations vs. identifiers
§ Citations applied to all submitted data sets and not to
metadata-only data sets
§ Persistent identifiers applied to approved data sets
(AKA: “roughly stable,” “good” data sets)
• Be clear about this with data submitters and users
Lynn Yarmey – UCAR Data Citation Workshop – April 5-6, 2012 Program Logo
15. Dependency
What are the Service and User Community
priorities for the organization?
Lynn Yarmey – UCAR Data Citation Workshop – April 5-6, 2012 Program Logo
16. Taking a step back
What are the Service and User Community
priorities for the organization?
Should every service center be meeting every need and/or
offering every service?
Lynn Yarmey – UCAR Data Citation Workshop – April 5-6, 2012 Program Logo
17. Even further
What are the Service and User Community
priorities for the organization?
Should every service center be meeting every need and/or
offering every service?
Might a metadata model be helpful?
Lynn Yarmey – UCAR Data Citation Workshop – April 5-6, 2012 Program Logo
18. Thank You!
Special thanks to:
Mark Parsons, Matt Mayernik, and
the ACADIS team!
Visit ACADIS: aoncadis.org
Visit the Arctic Portal: coming soon!
Contact me: lynn.yarmey@colorado.edu
Lynn Yarmey – UCAR Data Citation Workshop – April 5-6, 2012 Program Logo
