Keynote presentation for the Colorado Alliance of Research Libraries 2014 Research Data Management Conference, 11 July 2014. Focuses on why data management and sharing is important, and the role of libraries.
Data management overview and UC3 tools for IASSIST 2014Carly Strasser
Presentation to introduce current landscape of data management and UC3 tools and services that support data sharing. For IASSIST in Toronto, 5 June 2014.
Biodiversity—A Healthy Ecosystem Thrives on Fresh Ideas (Part 1 of 3), Phil J...Allen Press
Video of this presentation is available at https://www.youtube.com/watch?v=h38PvZMMJP0&list=PLybpVL27qHff3BVHuNXqYsqTs2e98_MpT&index=8
To maintain the long-term sustainability of the ecosystem, we need a steady flow of innovation and risk and a strong current of entrepreneurial spirit. Wherever ideas are generated—by a small, rebellious start-up or by a long-established player at the top of the food chain—they provide the catalyst and movement that keep things alive and well. We’ll conclude the day by looking at the transformational promise of open, linked, and shared data, the alignment of repository networks, data and metadata exchange, and a wrap-up of the current trends in scholarly publishing from the perspective of the university press.
Symbiosis—Is Collaboration the New Innovation? (Part 1 of 3), Alice MeadowsAllen Press
Video of this presentation is available at https://www.youtube.com/watch?v=YWGk4dt8Edk&list=PLybpVL27qHff3BVHuNXqYsqTs2e98_MpT&index=1
A significant development over the past couple of years has been the increase in collaboration between entities that support the scholarly publishing enterprise—creating efficiency and fueling innovation. We’ll begin the day with the example of ORCID, showing how collaboration can expand from a single idea and make connections that benefit many, and what this might mean for the future. We’ll follow this with an expedition into open source solutions in knowledge production that build collaboration, and we’ll hear about a project that helps institutions create connected data regarding their scholarship by using open standards.
Trove: More Than a Treasure? ALIA Conference Presentation 2010 Brisbane by Ro...Rose Holley
Describes the innovative development of Trove at the National Library of Australia. Trove is a search engine for Australians about Australians. It contains 90 million items from over 1000 contributing organisations.
Data Management for Mountain Observatories WorkshopCarly Strasser
Keynote presentation for 2014 Mountain Observatories Workshop, 16 July 2014.
Abstract:
While methods for collecting data are well taught, there is less emphasis on managing the resulting data effectively. New mandates, announcements, memos, and requirements from agencies and publishers are emerging that encourage better data management, data sharing, and data preservation. Scientists with good management skills will be able to maximize the productivity of their own research, effectively and efficiently share their data with the community, and benefit from the re-use of their data by others. I will offer an overview of data management landscape - discussing recent events, resources, and new directions for data stewardship. I will also cover best practices for data management, which will facilitate data sharing and reuse, and introduce tools researchers can use to help in their data stewardship endeavours.
Data management overview and UC3 tools for IASSIST 2014Carly Strasser
Presentation to introduce current landscape of data management and UC3 tools and services that support data sharing. For IASSIST in Toronto, 5 June 2014.
Biodiversity—A Healthy Ecosystem Thrives on Fresh Ideas (Part 1 of 3), Phil J...Allen Press
Video of this presentation is available at https://www.youtube.com/watch?v=h38PvZMMJP0&list=PLybpVL27qHff3BVHuNXqYsqTs2e98_MpT&index=8
To maintain the long-term sustainability of the ecosystem, we need a steady flow of innovation and risk and a strong current of entrepreneurial spirit. Wherever ideas are generated—by a small, rebellious start-up or by a long-established player at the top of the food chain—they provide the catalyst and movement that keep things alive and well. We’ll conclude the day by looking at the transformational promise of open, linked, and shared data, the alignment of repository networks, data and metadata exchange, and a wrap-up of the current trends in scholarly publishing from the perspective of the university press.
Symbiosis—Is Collaboration the New Innovation? (Part 1 of 3), Alice MeadowsAllen Press
Video of this presentation is available at https://www.youtube.com/watch?v=YWGk4dt8Edk&list=PLybpVL27qHff3BVHuNXqYsqTs2e98_MpT&index=1
A significant development over the past couple of years has been the increase in collaboration between entities that support the scholarly publishing enterprise—creating efficiency and fueling innovation. We’ll begin the day with the example of ORCID, showing how collaboration can expand from a single idea and make connections that benefit many, and what this might mean for the future. We’ll follow this with an expedition into open source solutions in knowledge production that build collaboration, and we’ll hear about a project that helps institutions create connected data regarding their scholarship by using open standards.
Trove: More Than a Treasure? ALIA Conference Presentation 2010 Brisbane by Ro...Rose Holley
Describes the innovative development of Trove at the National Library of Australia. Trove is a search engine for Australians about Australians. It contains 90 million items from over 1000 contributing organisations.
Data Management for Mountain Observatories WorkshopCarly Strasser
Keynote presentation for 2014 Mountain Observatories Workshop, 16 July 2014.
Abstract:
While methods for collecting data are well taught, there is less emphasis on managing the resulting data effectively. New mandates, announcements, memos, and requirements from agencies and publishers are emerging that encourage better data management, data sharing, and data preservation. Scientists with good management skills will be able to maximize the productivity of their own research, effectively and efficiently share their data with the community, and benefit from the re-use of their data by others. I will offer an overview of data management landscape - discussing recent events, resources, and new directions for data stewardship. I will also cover best practices for data management, which will facilitate data sharing and reuse, and introduce tools researchers can use to help in their data stewardship endeavours.
Getting onboard the data training: How librarians fit inDiane Clark
Academic librarians' roles and responsibilities are evolving and expanding into the area of data, how to manage, share, access and preserve. Providing training on the topic of how to discuss data with faculty and researchers was the focus of upskilling a cohort of academic librarians.
Cal Poly - Data Management for ResearchersCarly Strasser
October 17, 2013 @ 1 Robert E. Kennedy Library, Data Studio, California Polytechnic State University.
Researchers rarely learn about good data management practices. Instead we develop our own systems that are often unintelligible to others. In this talk, Strasser, PhD, will focus on the common mistakes that scientists make and how to avoid them. She will provide best practices for data management, which will facilitate data sharing and reuse, and introduce tools you can use.
How open is open? An evaluation rubric for public knowledgebasesmhaendel
Presented at the 2017 International Biocuration Conference.
Data relevant to any given scientific investigation is highly decentralized across thousands of specialized databases. Within the Biocuration community, we recognize that the value of open scientific knowledge bases is that they make scientific knowledge easier to find and compute, thereby maximizing impact and minimizing waste. The ever-increasing number of databases makes us necessarily question what are our priorities with respect to maintaining them, developing new ones, or senescing/subsuming ones that have completed in their mission. Therefore, open biomedical data repositories should be carefully evaluated according to quality, accessibility, and value of the database resources over time and across the translational divide.
Traditional citation count and publication impact factors as a measure of success or value are known to be inadequate to assess the usefulness of a resource. This is especially true for integrative resources. For example, almost everyone in biomedicine relies on PubMed, but almost no one ever cites or mentions it in their publications. While the Nucleic Acids Research Database issues have increased citation of some databases, many still go unpublished or uncited; even novel derivations of methodology, applications, and workflows from biomedical knowledge bases are often “adapted” but never cited. There is a lack of citation best practices for widely used biomedical database resources (e.g. should a paper be cited? A URL? Is mention of the name and access date sufficient?).
We have developed a draft evaluation rubric for evaluating open science databases according to the commonly cited FAIR principles -- Findable, Accessible, Interoperable, and Reusable, but with three additional principles: Traceable, Licensed, and Connected. These additions are largely overlooked and underappreciated, yet are critical to reuse of the knowledge contained within any given database. It is worth noting that FAIR principles apply not only to the resource as a whole, but also to their key components; this “fractal FAIRness” means that even the license, identifiers, vocabularies, APIs themselves must be Findable, Accessible, Interoperable, Reusable, etc. Here we report on initial testing of our evaluation rubric on the recent NIH/Wellcome Trust Open Science projects and seek community input for how to further advance this rubric as a Biocuration community resource.
Reusable data for biomedicine: A data licensing odysseymhaendel
Biomedical data integrators grapple with a fundamental blocker in research today: licensing for data use and redistribution. Complex licensing and data reuse restrictions hinder most publicly-funded, seemingly “open” biomedical data from being put to its full potential. Such issues include missing licenses, non-standard licenses, and restrictive provisions. The sheer diversity of licenses are particularly thorny for those that aim to redistribute data. Redistributors are often required to contact each sub-source to obtain permissions, and this is complicated by the fact that on each side of the agreement there may be multiple legal entities involved and some sub-sources may themselves already be aggregating data from other sub-sources. Furthermore, interpreting legal compliance with source data licensing and use agreements is complicated, as data is often manipulated, shared, and redistributed by many types of research groups and users in various and subtle ways. Here, we debut a new effort, the (Re)usable Data Project, where we have created a five-part rubric to evaluate biomedical data sources and their licensing information to determine the degree to which unnegotiated and unrestricted reuse and redistribution are provided. We have tested the (Re)usable Data rubric against various biomedical data sources, ranking each source on a scale of zero to five stars, and have found that approximately half of the resources rank poorly, getting 2.5 stars or less. Our goal is to help biomedical informaticians and other users navigate the plethora of issues in reusing and redistributing biomedical data. The (Re)usable Data project aims to promote standardization and ease of reuse licensing practices by data providers.
Open Science for Australian Institute of Marine Science WorkshopCarly Strasser
*Please excuse the typos :)
Presentation on open science and open data for the Australian Institute of Marine Science (AIMS) workshop on "Raising your research profile using research data". 18 June 2014.
This webinar will discuss the special needs of digital humanities researchers and help you learn how to talk them about their information management needs.
Topics that will be covered:
What is humanities data?
What special considerations are involved in creating DMPs for humanities data?
Where can you store humanities data?
What will humanities funding agencies be looking for? What regulations apply to humanities data (e.g., data sharing, data management, data availability)?
What librarians should know before meeting with a humanist; how humanists differ from other researchers in the way they think about their version of data.
Social Media News Communities: Gatekeeping, Coverage, and Statement BiasMounia Lalmas-Roelleke
We examine biases in online news sources and social media communities around them. To that end, we introduce unsupervised methods considering three types of biases: selection or "gatekeeping" bias, coverage bias, and statement bias, characterizing each one through a series of metrics. Our results, obtained by analyzing 80 international news sources during a two-week period, show that biases are subtle but observable, and follow geographical boundaries more closely than political ones. We also demonstrate how these biases are to some extent amplied by social media.
Librarians: how and why manage research data; CDU Darwin 080915Richard Ferrers
An ANDS(.org.au) presentation to Charles Darwin University librarians on research data management (RDM). What is RDM? Why do RDM? How to do RDM? Presentation 08 Sept 2015, Darwin Aust.
Overview of data management policies and data management plans, including the DMPTool. For Ecological Society of America 2013 Meeting in Minneapolis, MN 5 August 2013.
Getting onboard the data training: How librarians fit inDiane Clark
Academic librarians' roles and responsibilities are evolving and expanding into the area of data, how to manage, share, access and preserve. Providing training on the topic of how to discuss data with faculty and researchers was the focus of upskilling a cohort of academic librarians.
Cal Poly - Data Management for ResearchersCarly Strasser
October 17, 2013 @ 1 Robert E. Kennedy Library, Data Studio, California Polytechnic State University.
Researchers rarely learn about good data management practices. Instead we develop our own systems that are often unintelligible to others. In this talk, Strasser, PhD, will focus on the common mistakes that scientists make and how to avoid them. She will provide best practices for data management, which will facilitate data sharing and reuse, and introduce tools you can use.
How open is open? An evaluation rubric for public knowledgebasesmhaendel
Presented at the 2017 International Biocuration Conference.
Data relevant to any given scientific investigation is highly decentralized across thousands of specialized databases. Within the Biocuration community, we recognize that the value of open scientific knowledge bases is that they make scientific knowledge easier to find and compute, thereby maximizing impact and minimizing waste. The ever-increasing number of databases makes us necessarily question what are our priorities with respect to maintaining them, developing new ones, or senescing/subsuming ones that have completed in their mission. Therefore, open biomedical data repositories should be carefully evaluated according to quality, accessibility, and value of the database resources over time and across the translational divide.
Traditional citation count and publication impact factors as a measure of success or value are known to be inadequate to assess the usefulness of a resource. This is especially true for integrative resources. For example, almost everyone in biomedicine relies on PubMed, but almost no one ever cites or mentions it in their publications. While the Nucleic Acids Research Database issues have increased citation of some databases, many still go unpublished or uncited; even novel derivations of methodology, applications, and workflows from biomedical knowledge bases are often “adapted” but never cited. There is a lack of citation best practices for widely used biomedical database resources (e.g. should a paper be cited? A URL? Is mention of the name and access date sufficient?).
We have developed a draft evaluation rubric for evaluating open science databases according to the commonly cited FAIR principles -- Findable, Accessible, Interoperable, and Reusable, but with three additional principles: Traceable, Licensed, and Connected. These additions are largely overlooked and underappreciated, yet are critical to reuse of the knowledge contained within any given database. It is worth noting that FAIR principles apply not only to the resource as a whole, but also to their key components; this “fractal FAIRness” means that even the license, identifiers, vocabularies, APIs themselves must be Findable, Accessible, Interoperable, Reusable, etc. Here we report on initial testing of our evaluation rubric on the recent NIH/Wellcome Trust Open Science projects and seek community input for how to further advance this rubric as a Biocuration community resource.
Reusable data for biomedicine: A data licensing odysseymhaendel
Biomedical data integrators grapple with a fundamental blocker in research today: licensing for data use and redistribution. Complex licensing and data reuse restrictions hinder most publicly-funded, seemingly “open” biomedical data from being put to its full potential. Such issues include missing licenses, non-standard licenses, and restrictive provisions. The sheer diversity of licenses are particularly thorny for those that aim to redistribute data. Redistributors are often required to contact each sub-source to obtain permissions, and this is complicated by the fact that on each side of the agreement there may be multiple legal entities involved and some sub-sources may themselves already be aggregating data from other sub-sources. Furthermore, interpreting legal compliance with source data licensing and use agreements is complicated, as data is often manipulated, shared, and redistributed by many types of research groups and users in various and subtle ways. Here, we debut a new effort, the (Re)usable Data Project, where we have created a five-part rubric to evaluate biomedical data sources and their licensing information to determine the degree to which unnegotiated and unrestricted reuse and redistribution are provided. We have tested the (Re)usable Data rubric against various biomedical data sources, ranking each source on a scale of zero to five stars, and have found that approximately half of the resources rank poorly, getting 2.5 stars or less. Our goal is to help biomedical informaticians and other users navigate the plethora of issues in reusing and redistributing biomedical data. The (Re)usable Data project aims to promote standardization and ease of reuse licensing practices by data providers.
Open Science for Australian Institute of Marine Science WorkshopCarly Strasser
*Please excuse the typos :)
Presentation on open science and open data for the Australian Institute of Marine Science (AIMS) workshop on "Raising your research profile using research data". 18 June 2014.
This webinar will discuss the special needs of digital humanities researchers and help you learn how to talk them about their information management needs.
Topics that will be covered:
What is humanities data?
What special considerations are involved in creating DMPs for humanities data?
Where can you store humanities data?
What will humanities funding agencies be looking for? What regulations apply to humanities data (e.g., data sharing, data management, data availability)?
What librarians should know before meeting with a humanist; how humanists differ from other researchers in the way they think about their version of data.
Social Media News Communities: Gatekeeping, Coverage, and Statement BiasMounia Lalmas-Roelleke
We examine biases in online news sources and social media communities around them. To that end, we introduce unsupervised methods considering three types of biases: selection or "gatekeeping" bias, coverage bias, and statement bias, characterizing each one through a series of metrics. Our results, obtained by analyzing 80 international news sources during a two-week period, show that biases are subtle but observable, and follow geographical boundaries more closely than political ones. We also demonstrate how these biases are to some extent amplied by social media.
Librarians: how and why manage research data; CDU Darwin 080915Richard Ferrers
An ANDS(.org.au) presentation to Charles Darwin University librarians on research data management (RDM). What is RDM? Why do RDM? How to do RDM? Presentation 08 Sept 2015, Darwin Aust.
Overview of data management policies and data management plans, including the DMPTool. For Ecological Society of America 2013 Meeting in Minneapolis, MN 5 August 2013.
October 18, 2013 @ Kennedy Library, Data Studio, Cal Poly. We hear about all things “open” these days: open access, open source, open data, open science, et cetera. But what does it really mean for how we do science? How are things changing, and what are the implications for individual researchers?
2013 DataCite Summer Meeting - Closing Keynote: Building Community Engagement...datacite
2013 DataCite Summer Meeting - Making Research better
DataCite. Co-sponsored by CODATA.
Thursday, 19 September 2013 at 13:00 - Friday, 20 September 2013 at 12:30
Washington, DC. National Academy of Sciences
http://datacite.eventbrite.co.uk/
Dataverse in the Universe of Data by Christine L. Borgmandatascienceiqss
Data repositories are much more than "black boxes" where data go in but may never come out. Rather, they are situated in communities, with contributors, users, reusers, and repository staff who may engage actively or passively with participants. This talk will explore the roles that Dataverse plays – or could play – in individual communities.
Cal Poly - Data Management: Who knew it was a hot topic?Carly Strasser
October 17, 2013 @ Robert E. Kennedy Library, Data Studio, California Polytechnic State University.
New mandates, announcements, memos, and requirements are emerging that encourage better data management, data sharing, and data preservation. In this presentation, data curation specialist Carly Strasser, PhD, offers a lay of the data management land by discussing recent events, resources, and new directions for data stewardship.
Metadata From the Source: Participatory Metadata Models in Post-Custodial Pro...Itza Carbajal
Presentation part of panel 6 focused on Re-thinking Metadata and Descriptive Practices
Abstract:
As the call from the United Nations for Human Rights-based approaches to data gains momentum across the world, the LLILAS Benson Digital Initiatives team at the University of Texas at Austin begins by asking “how can post-custodial models facilitate efforts at self determination?” In particular how can participatory metadata creation approaches used by LLILAS Benson in various post-custodial partnerships across Latin America improve archival description praxis. Speaker will deliberate on previous and current implementations of ethics driven participatory metadata creation practices used for post-custodial digitization projects in a cultural heritage institution. Insights aim to further establish collaborative information processes that will in turn bring about richer, culturally sensitive and human rights centered metadata for digital cultural heritage collections.
Slides from Monday 30 July - Data in the Scholarly Communications Life Cycle Course which is part of the FORCE11 Scholarly Communications Institute.
Presenter - Natasha Simons
Funders and publishers have something in common: for better or worse, we have the ability to influence the behavior of researchers. This talk will focus on what both groups can do to improve research now and in the future.
ESA Ignite talk on UC3 Dash platform for data sharingCarly Strasser
Ignite talk (20 slides / 15 seconds per slide) for ESA 2014 meeting in Sacramento, CA 12 August 2014. On the Dash platform for helping researchers manage and share their data via institutional repositories
Data Publication for UC Davis Publish or PerishCarly Strasser
Intro presentation for panel on going beyond publishing journal articles. UC Davis "Publish or Perish?" Event, 13 Feb 2014. Sorry about missing gradient on some of slides!
Cal Poly - Data Management and the DMPToolCarly Strasser
October 17, 2013 @ Robert E. Kennedy Library, Data Studio, California Polytechnic State University.
Many funders now require researchers to submit a Data Management Plan alongside their project proposals. The DMPTool is a free, online wizard that helps you create a data management plan specific to your project, and provides you with links and resources for ensuring your plan is successful.
NISO Webinar on data curation services at the CDLCarly Strasser
"Building communities and Services in Support of Data-Intensive Research". Webinar on 18 Sept 2013 for the NISO Webinar Series. This was part 2 of 2 for Data Curation
"Undergrad ecologists aren't learning data management" - ESA 2013Carly Strasser
Presentation for Ecological Society of America 2013 Meeting in Minneapolis, MN on 6 August 2013. Results published in Ecosphere doi: 10.1890/ES12-00139.1
Adjusting primitives for graph : SHORT REPORT / NOTESSubhajit Sahu
Graph algorithms, like PageRank Compressed Sparse Row (CSR) is an adjacency-list based graph representation that is
Multiply with different modes (map)
1. Performance of sequential execution based vs OpenMP based vector multiply.
2. Comparing various launch configs for CUDA based vector multiply.
Sum with different storage types (reduce)
1. Performance of vector element sum using float vs bfloat16 as the storage type.
Sum with different modes (reduce)
1. Performance of sequential execution based vs OpenMP based vector element sum.
2. Performance of memcpy vs in-place based CUDA based vector element sum.
3. Comparing various launch configs for CUDA based vector element sum (memcpy).
4. Comparing various launch configs for CUDA based vector element sum (in-place).
Sum with in-place strategies of CUDA mode (reduce)
1. Comparing various launch configs for CUDA based vector element sum (in-place).
Show drafts
volume_up
Empowering the Data Analytics Ecosystem: A Laser Focus on Value
The data analytics ecosystem thrives when every component functions at its peak, unlocking the true potential of data. Here's a laser focus on key areas for an empowered ecosystem:
1. Democratize Access, Not Data:
Granular Access Controls: Provide users with self-service tools tailored to their specific needs, preventing data overload and misuse.
Data Catalogs: Implement robust data catalogs for easy discovery and understanding of available data sources.
2. Foster Collaboration with Clear Roles:
Data Mesh Architecture: Break down data silos by creating a distributed data ownership model with clear ownership and responsibilities.
Collaborative Workspaces: Utilize interactive platforms where data scientists, analysts, and domain experts can work seamlessly together.
3. Leverage Advanced Analytics Strategically:
AI-powered Automation: Automate repetitive tasks like data cleaning and feature engineering, freeing up data talent for higher-level analysis.
Right-Tool Selection: Strategically choose the most effective advanced analytics techniques (e.g., AI, ML) based on specific business problems.
4. Prioritize Data Quality with Automation:
Automated Data Validation: Implement automated data quality checks to identify and rectify errors at the source, minimizing downstream issues.
Data Lineage Tracking: Track the flow of data throughout the ecosystem, ensuring transparency and facilitating root cause analysis for errors.
5. Cultivate a Data-Driven Mindset:
Metrics-Driven Performance Management: Align KPIs and performance metrics with data-driven insights to ensure actionable decision making.
Data Storytelling Workshops: Equip stakeholders with the skills to translate complex data findings into compelling narratives that drive action.
Benefits of a Precise Ecosystem:
Sharpened Focus: Precise access and clear roles ensure everyone works with the most relevant data, maximizing efficiency.
Actionable Insights: Strategic analytics and automated quality checks lead to more reliable and actionable data insights.
Continuous Improvement: Data-driven performance management fosters a culture of learning and continuous improvement.
Sustainable Growth: Empowered by data, organizations can make informed decisions to drive sustainable growth and innovation.
By focusing on these precise actions, organizations can create an empowered data analytics ecosystem that delivers real value by driving data-driven decisions and maximizing the return on their data investment.
Levelwise PageRank with Loop-Based Dead End Handling Strategy : SHORT REPORT ...Subhajit Sahu
Abstract — Levelwise PageRank is an alternative method of PageRank computation which decomposes the input graph into a directed acyclic block-graph of strongly connected components, and processes them in topological order, one level at a time. This enables calculation for ranks in a distributed fashion without per-iteration communication, unlike the standard method where all vertices are processed in each iteration. It however comes with a precondition of the absence of dead ends in the input graph. Here, the native non-distributed performance of Levelwise PageRank was compared against Monolithic PageRank on a CPU as well as a GPU. To ensure a fair comparison, Monolithic PageRank was also performed on a graph where vertices were split by components. Results indicate that Levelwise PageRank is about as fast as Monolithic PageRank on the CPU, but quite a bit slower on the GPU. Slowdown on the GPU is likely caused by a large submission of small workloads, and expected to be non-issue when the computation is performed on massive graphs.
Techniques to optimize the pagerank algorithm usually fall in two categories. One is to try reducing the work per iteration, and the other is to try reducing the number of iterations. These goals are often at odds with one another. Skipping computation on vertices which have already converged has the potential to save iteration time. Skipping in-identical vertices, with the same in-links, helps reduce duplicate computations and thus could help reduce iteration time. Road networks often have chains which can be short-circuited before pagerank computation to improve performance. Final ranks of chain nodes can be easily calculated. This could reduce both the iteration time, and the number of iterations. If a graph has no dangling nodes, pagerank of each strongly connected component can be computed in topological order. This could help reduce the iteration time, no. of iterations, and also enable multi-iteration concurrency in pagerank computation. The combination of all of the above methods is the STICD algorithm. [sticd] For dynamic graphs, unchanged components whose ranks are unaffected can be skipped altogether.
Data Centers - Striving Within A Narrow Range - Research Report - MCG - May 2...pchutichetpong
M Capital Group (“MCG”) expects to see demand and the changing evolution of supply, facilitated through institutional investment rotation out of offices and into work from home (“WFH”), while the ever-expanding need for data storage as global internet usage expands, with experts predicting 5.3 billion users by 2023. These market factors will be underpinned by technological changes, such as progressing cloud services and edge sites, allowing the industry to see strong expected annual growth of 13% over the next 4 years.
Whilst competitive headwinds remain, represented through the recent second bankruptcy filing of Sungard, which blames “COVID-19 and other macroeconomic trends including delayed customer spending decisions, insourcing and reductions in IT spending, energy inflation and reduction in demand for certain services”, the industry has seen key adjustments, where MCG believes that engineering cost management and technological innovation will be paramount to success.
MCG reports that the more favorable market conditions expected over the next few years, helped by the winding down of pandemic restrictions and a hybrid working environment will be driving market momentum forward. The continuous injection of capital by alternative investment firms, as well as the growing infrastructural investment from cloud service providers and social media companies, whose revenues are expected to grow over 3.6x larger by value in 2026, will likely help propel center provision and innovation. These factors paint a promising picture for the industry players that offset rising input costs and adapt to new technologies.
According to M Capital Group: “Specifically, the long-term cost-saving opportunities available from the rise of remote managing will likely aid value growth for the industry. Through margin optimization and further availability of capital for reinvestment, strong players will maintain their competitive foothold, while weaker players exit the market to balance supply and demand.”
18. “Help us identify grants that are wasteful or that you
don’t think are a good use of taxpayer dollars.”
Rep. Adrian Smith (R-Nebraska), a member of the House Committee on Science
and Technology
23. Faster progress.
More credibility.
Better reproducibility.
Fox News, creationism,
& the war on science.
Increased collaboration & reuse.
Future scientists can use the data.
24. From Flickr by Redden-McAllister
From Flickr by Ken Cowell
From Flickr Brandi Jordan
26. … “Federal agencies investing in research
and development (more than $100 million
in annual expenditures) must have clear
and coordinated policies for increasing
public access to research products.”
Feb
2013
27. 1. Maximize free public access
2. Ensure researchers create data
management plans
3. Allow costs for data preservation and
access in proposal budgets
4. Ensure evaluation of data management
plan merits
5. Ensure researchers comply with their data
management plans
6. Promote data deposition into public
repositories
7. Develop approaches for identification and
attribution of datasets
8. Educate folks about data stewardship
From Flickr by Joe Crimmings Photography
39. “City All-Star Softball Team”, 1947. From Calisphere, Contributed by Oxnard Public Library
Data
managers
Administrators
Funders
Librarians
Information
services
Researchers
Publishers