This saves knowledge workers and life science teams valuable time and resources in locating the latest clinical trial data alongside other critical content.

RightFind Navigate customers already find information about U.S. clinical trials through the connector to ClinicalTrials.gov. The new connector expands users’ access to this data from around the world.

“Researchers need easier ways to access the latest clinical evidence and identify trends within the data for a multitude of use cases across the drug development lifecycle,” said Tracey Armstrong, President and CEO, CCC. “Typically, researchers visit multiple clinical trial websites to find information, then manually collect the data. The Clinical Trial Registries Data Connector in RightFind Navigate brings together data from multiple clinical trial registries with other types of content, including scientific literature, to enable knowledge workers to find and explore the information they need in one place.”

CCC helps companies manage vast amounts of published content and proprietary internal information and data. As experts in processing data from thousands of sources across a diverse set of industries, CCC has established a proven record of working with a wide range of companies, including content providers and technology partners, to unify data sources and make content more discoverable.

The post Clinical Trial Registries Added to CCC’s RightFind Navigate Data Sources appeared first on Copyright Clearance Center.

Pharmaceutical and life science companies are dealing with tremendous growth in available information and an increasingly diverse range of sources that make it challenging to maintain a comprehensive and up-to-date understanding on key research advancements. RightFind Navigate’s machine-learning driven semantic enrichment and advanced personalization features help users locate the most relevant information in scientific literature, clinical trials, patents, and many other sources. This pilot expands the data intelligence already available in RightFind Navigate with the introduction of disambiguated researcher and institution profiles.

RightFind Navigate is part of the RightFind Suite, which provides a single integrated and scalable solution to meet the evolving needs of today’s research organizations. RightFind Navigate unifies searching across multiple licensed content sources, publicly available data, and internal proprietary content, empowering researchers to reveal connections and drive innovation. The solution provides a flexible, scalable, open ecosystem designed to maximize an organizations’ return on their content and data investments.

“Many of our RightFind customers already enjoy the benefits of semantic search and the breadth of information sources that are available in RightFind Navigate,” said Tracey Armstrong, President and CEO, CCC. “We are excited to pilot the introduction of research and institution profiles that allow users to see the web of connections between the various entities engaged in a particular research field, whether these are researchers in corporations or in academia, and with whom they are affiliated.”

The post CCC Announces RightFind Navigate News appeared first on Copyright Clearance Center.

“These concerns we uncovered directly lead to disruption in various stages of the research lifecycle – including, but definitely not limited to, the transition to open access publication,” Carmichael noted. 

“In embarking on our study of metadata management, it’s become clear, at least to me, that an ecosystem-wide commitment to improving data quality from the policy level down to editorial system configurations will help facilitate the transition to open, while also helping to preserve research integrity, enhance findability of research, and improve impact measurement.” 

Carmichael welcomed first Deni Auclair of Media Growth Strategies, who worked with CCC to create the State of Scholarly Metadata interactive report. Auclair spoke with dozens of community members to map the complexities and the breakages, as well as the value of metadata across all research stages. 

“We asked questions around implementation and use of quality metadata with the goal of figuring out how we can improve. We asked questions like who should create and maintain metadata? Where should it originate? What resources do these various stakeholders invest to create, curate, or maintain various types of metadata? What are their biggest challenges when it comes to metadata management or the use of persistent identifiers? What are the most critical metadata elements? What’s at stake if those elements don’t persist through the scholarly communication process? And who should own metadata quality and control?” Auclair explained. 

“Basically, the industry is leaving money on the table because the lack of standards is hindering search and discovery. Research is repeated or it’s slowed down, because content isn’t discoverable, especially in underrepresented areas of the world. And there’s a massive amount of manual effort involved in managing metadata.” 

President of the Society for Scholarly Publishing (SSP) Randy Townsend then addressed the role of researchers who are asked to bear a growing burden for providing rich metadata. 

“The case for rich metadata is pretty clear, but the way in which we integrate that metadata into our processes is still a challenge,” he said. “And when metadata is an afterthought, because we’re laser-focused on the post-publication value, then we’ve already missed opportunities in the after-submission and peer review processes to continually enhance and enrich that metadata,” Townsend told Carmichael. 

“From my perspective, metadata should begin to be captured upstream in the idea development phase, which is from the research that you all presented a few minutes ago. Theoretically, that puts the onus on the researcher. And the challenge there is we’re putting more and more requirements and pressure on the researcher, who may not be qualified or have the bandwidth to meet those expectations,” he concluded. 

Bringing in a perspective from the scholarly publishing community in South America, Ana Heredia, a senior associate at Maverick Publishing Specialists, reported that the challenges around metadata and persistent identifiers are not very different from those seen in North America or Europe. 

“There are several articles, blog posts, talks, and guidelines or tool kits being shared and being prepared on how to raise awareness and engage researchers around the importance of metadata. I am involved in some of them, advocating for researchers to take a more active role in metadata sharing,” Heredia stated. 

“Of course, researchers benefit from accessing contextual information around other researchers’ data, but only very engaged individuals will have the necessary knowledge, as was mentioned before, or would take the necessary time to enter the data properly for it to be reused,” she told Carmichael. “Librarians and publishers typically are the ones who have this knowledge, because they are used to indexes. They are used to taxonomies and standards for research information. 

“If I had to summarize,” Heredia concluded, “I would say librarians and publishers have the how. Funders have the why. And researchers have the what.” 

Finally, Jamie Carmichael welcomed Wolfgang Mayer, head of e-resource management at the University of Vienna to provide an institutional perspective on the role universities can play to improve the quality of scholarly metadata, especially supporting researchers. 

“Obviously, it’s the task of the university to enable [researchers] to put as much effort and energy into research and less into administration as we could. But nevertheless, administration of their publications, of their research data, of their identifiers, of the metadata – that is still part of their job,” Mayer told Carmichael. 

“In Europe, it’s a little different than the US, I think. Funders, based upon the Coalition S initiative, are trying to increase the pressure regarding Open Access and the traceability and visibility of these publications,” he explained. 

“I think it’s also a generation gap. With young researchers with new projects, when we can present incentives regarding the visibility of their work especially, they are quite easily motivated to put thought into the metadata. [The University of Vienna] is the second-largest university in northern Europe, with 10,000 researchers and more than 90,000 students. We are creating ORCID IDs, creating sets of Ringgold IDs, helping the researchers from the beginning of their research projects to create research data and wherever possible, to help them across the research workflow.” 

As CCC’s Jamie Carmichael observed in her closing remarks, “A dedication to metadata stewardship across each stakeholder group is a shared responsibility. For service providers like CCC, supporting them is vital.” 

The post The State of Scholarly Metadata in 2023 – Industry Insights From Around the Globe appeared first on Copyright Clearance Center.

On Monday, September 18, at Poortgebouw, the University of Leiden, the Netherlands, CCC in partnership with the GO FAIR Foundation will host its inaugural FAIR Forum on “The Evolving Role of Data in the AI Era.” Complimentary registration is here.

With new AI services being introduced on an almost daily basis, the adoption of FAIR Data Principles is more important than ever. This one day in-person forum will provide leaders in research-intensive businesses with expert insights on the importance of FAIR data to successful AI initiatives and best practices for FAIR implementation.

Click below to listen to the latest episode of the Velocity of Content podcast.

At this special program, CCC and GOFAIR will welcome global FAIR and AI experts including Barend Mons, President, CODATA; Erik Schultes, FAIR Implementation Lead, GO FAIR Foundation; Lars Juhl Jensen, Professor, NNF Center for Protein Research; Jane Lomax, Head of Ontologies, SciBite; and Martin Romacker, Product Manager, Roche Data Marketplace.

Tracey Armstrong, President & CEO, CCC, and Babis Marmanis, Executive Vice President & CTO, CCC, will also share insights.

Molecular biologist Barend Mons is responsible for groundbreaking research on malaria parasites. He became involved with creating the FAIR data principles in 2014, and today is a leading advocate for their adoption. In a CCC Town Hall panel program this spring, he explained why he had committed himself to this ambitious effort.

“There’s no way to work without machines, and that’s why I need FAIR data for my own research,” Mons told me. “But I also became an advocate because I think it can change the face of science and the whole way we do open science fundamentally, which is needed.”

GO FAIR Foundation’s Erik Schultes acknowledged the challenge posed by the ever-growing volume of data in all fields – a challenge exacerbated by inadequate metadata identification.

“All the data we have today, six months from now, it’s going to be doubled. A year from now, that’s going to be quadrupled,” Schultes noted. “If that data is not made accessible online and if there isn’t sufficient metadata that can allow search engines or machine agents to locate it in some meaningful way, then indeed that data can be lost in plain sight.”

The post FAIR Forum To Address “Evolving Role of Data in the AI Era” appeared first on Copyright Clearance Center.

That’s how an information professional at a large pharmaceutical company described what drives the collaboration between info pros and data scientists at his organization. As he noted, “the one thing our researchers and data scientists don’t have is time, and having information specialists who understand the data sources is one thing they need. The scientists appreciate our focus on data quality and our ability to enhance the data with a specialized taxonomy.”

In fact, he sees himself as an information tour guide—helping connect his organization’s data scientists to the right data sources for each project and arranging for text and data mining licenses to enable the scientists to glean intelligence from the data.

Wondering how you can act as an ‘information tour guide?’ Consider the following: 

Reach out to your entry-level colleagues

This is particularly important with data scientists who are recent graduates; while they are familiar with high-powered tools for data analysis, they often need support in working with project stakeholders and applying the tools to specific business problems. As the information professional noted, some new hires come from a linguistics background; applying their knowledge to the pharmaceutical industry requires significant adjustment. 

While information professionals need not have expertise as programmers, he sees the importance of understanding the basic concepts and language of data science. “There is such potential for collaboration, particularly as we are looking at large language models and prompt engineering,” he observed. “It’s easy to get intimidated by the complexity of the data, until we remember that we bring our expertise in information management. While the data scientists get focused on building a new algorithm to solve a particular problem, we info pros can point them to a system we already have in place or to an approach others have taken to address the issue.”   

Share what you’re doing behind the scenes

One of the important roles information professionals can play in supporting data scientists is in evaluating output and identifying ways to bring more structure to unstructured data. As this info pro described it, “we work with the data scientists on entity extraction, making sure that it is normalized according to our ontologies. The scientists assume that this works automatically; they often don’t see that we are evaluating the quality of the search results, determining whether this three-letter acronym references a process or is just the initials in an author’s name, for example. We think about the real-world problems that can pop up when we normalize the data. Sometimes that involves reviewing the output and manually curating the data based on our knowledge of users’ searching behavior.” 

Be adaptable and stay on top of emerging needs

The job of information professionals is to give the scientists more context around the information, he said. “We look for ways to link data more effectively, to help the scientists address the most important business challenges. And we work hard on finding ways to calculate what is relevant and useful to each scientist. This is a moving target—what their interests are today may not be what they are focused in six months from now. We have to stay on top of their priorities so that we are feeding them the information they care about today.” By focusing on the emerging information needs of the data scientists, information professionals can contribute to addressing the most critical issues their enterprise is facing.  

This is the final installment of Mary Ellen Bates’ series around Info Pros in a Data-Driven Enterprise. To see the previous blog posts in this series, check out:  

• 5 Tips to Establish Collaborative Relationships Between Info Pros & Data Scientists  

• Bringing Data Science to the Information Center  

The post 3 Ways to Become an Information Tour Guide for Data Scientists  appeared first on Copyright Clearance Center.

Now, as the researchers within her organization begin a research project on an issue they influence, and start focusing on their data needs, she is brought in as the information expert. She asks the questions that scientists often don’t consider: 

• Do we have the license that allows you to do what you need?  
• How may people will need access to it? 
• How long do we need access? 

Relationship building over time – becoming part of researchers’ workflows

Her ability to serve effectively as a gatekeeper is due to her success at relationship building over time. As she described it to me, “I had worked with one director on several projects and we had built a strong relationship, so now she makes sure that all her scientists contact me for help at the beginning of every project. I have become part of their workflow, and they know to ask me for literature searches or external data sources. And, looking more broadly, I like to insert myself in the project planning and budgeting process. Before the start of each fiscal year, I send out a reminder to the project budget managers, reminding them of the resources we have available and asking how that fits with their next year’s portfolio.” She emphasized the need to “institutionalize our successes so that people understand the importance of bringing the library into their projects at the outset. The data scientists get better outcomes and less stress—they’re happier people—because the library handles the data acquisition and management and we see the continuum of data needs within the institution.”

Creating a big impact with contract and licensing negotiations

The info pro observed that some of the biggest impacts she has had while serving as the information procurement clearinghouse have been around contract and licensing negotiations. “We have had times when a team might think that they have identified the data that they want, and then we start the negotiation and discover that it’s too expensive, or the publisher can’t offer the right kind of licensing, or they couldn’t do what they thought they could do with the data. At that point, the team may decide to modify the project; I see that as a success, in that we’re not spending money on something we would not be able to use. And, honestly, I am using a basic reference interview technique from librarianship—asking them what the question is that they are trying to answer.”

She also noted that, a year ago, a reorganization moved the data analyst—who was responsible for the internal and external data analytics of the non-profit—to the library. “Since the library serves as a procurement clearinghouse for external information, we have the perspective to start looking at how the data analyst can support our knowledge management and internal data infrastructure,” she said.

Where information science and data science intersect

I asked her whether she thought info pros had any blind spots with respect to working with data scientists and she answered that “sometimes we info pros aren’t viewed as having the relevant data analysis skill sets, so we twist ourselves in knots to position ourselves as a key resource. I do think it is important that we work with the data scientists enough to understand their motivations and their workflow. I have learned to not assume that I understand their perspective.”

Take data cleanup, for example. “I often have to put work in at the start of a project to make the data consistent and avoid ambiguities; I know that, if I don’t do that at the beginning, the project team will have more work to do on their end because the data input is bad. When I explain my process to them with references to resources that they understand like Jupyter Notebook rather than using librarian jargon, they are much more likely to see the value of working with me at the start of the project.”

In her experience, info pros recognize data scientists as being fellow “info nerds” and that can lead to mistaken assumptions. “Take data from the US Census Bureau, for example,” she said. “Librarians understand census data as an entity—we know how it is created, how it’s maintained, what kind of structure it has, what its limitations are, where the ambiguities are. Data scientists, on the other hand, are more focused on how they can transform the data in whatever tool they are using rather than about whether the data needs to be made consistent or whether the structure allows for a particular type of analysis. We have to remember that we look at information from a different, broader perspective and can see issues that the data scientists might not anticipate.”

As an info pro who operates primarily as a solo librarian, she finds this kind of collaboration exciting; finding where information science and data science intersect and what her most strategic role can be in furthering the goals of her organization. 

This is the second in a three-part series from Mary Ellen Bates around Info Pros in a Data Driven Enterprise. View the first blog post in this series here: 

• 5 Tips to Establish Collaborative Relationships Between Info Pros & Data Scientists  

The post Bringing Data Science to the Information Center appeared first on Copyright Clearance Center.

A May 10, 2023, CCC Town Hall panel shared best practices for developing research data that is FAIR through culture, training, and technology. The discussion also detailed how FAIR data saves lives, saves money, and drives confidence in science on four continents.

The LinkedIn Live special event included George Strawn, a scholar at the US National Academies of Sciences, Engineering, and Medicine who served as CIO with the National Science Foundation from 2003 to 2009. Strawn joined the roundtable discussion with reflections on a half-century of internet evolution and the transformative role of FAIR data in the future.

Click below to listen to the latest episode of the Velocity of Content podcast.

In his remarks, Strawn identified three steps in the evolution of computing. The first step came after World War II with the ENIAC and UNIVAC, the first programmable digital computers that were enormous standalone machines. Then came the internetworking era that began in the 1970s, when Strawn was beginning his career as a computer scientist at the University of Iowa. Now in 2023, he reflected on the new era in computing that FAIR data will bring.

“The first wonderful step was computers themselves. The second, equally important step has been the internet age of interconnected computers,” Strawn told me. “I think FAIR is ushering in the third phase of information technology, which is interoperable data as well as interconnected computers.”

The post Making Research Data FAIR appeared first on Copyright Clearance Center.

When asked about the specific role of the information science team, he described it as being focused on supporting colleagues within the data science groups by enabling access to external information and data and in developing knowledge graphs and deeper machine-learning analysis to support the researchers’ activities. In addition, his group looks at how scientists search for and discover critical information, in order to create new curation, discovery and analysis tools for their day-to-day searches.

One challenge of information centers within enterprises is in finding a way to become integrated into the workflow of research teams. During an internal reorganization, this information scientist saw the greatest potential for his group would be to work much more closely with the data science organization. That has enabled his team to bring their core expertise—library and information science—into each project. 

In fact, he noted that “our profession has always been focused on how we can contribute, where we fit in a project lifecycle. In that sense, nothing has really changed from 20 years ago. Yes, the technology space has evolved and our skill sets have evolved, but the fundamental value we offer is our unique expertise in information science. The data scientists respect us as the experts in external data and information just as we respect them as the experts in their domain. Whenever they begin to map out a project, they bring an information scientist from our team in to ask us what kinds of resources we could provide and to spell out their information requirements. I think it is critical that we are always offered a seat at the table; we don’t have to fight to be brought into a project at the beginning.”

Establishing a Better Working Relationship

I asked him what advice he would offer to information professionals who have not yet established these kinds of collaborative relationships with the data scientists within their organization. His suggestions included: 

1. Make sure you elevate your capabilities in your organization’s core domain. Watch for new resources and tools, and share what you learn with the data scientists. Look for opportunities to bring your expertise to the forefront and highlight your familiarity with external information sources and licensing issues.
2. Often the data scientists are new to the organization—sometimes, they are right out of university—and they may not be aware of the role you can play. Your messaging around the value of information science and what information scientists can bring to the table is critical.
3. Be open about the fact that you’re not a data scientist, and you are not in competition with them. Sometimes you will be brought into projects in areas with which you are not familiar and much of the discussion at team meetings might go completely above you. But that’s OK—by building relationships around openness, trust and respect, everyone appreciates the information scientists for the expertise they bring to the table.
4. Keep in mind that, while information scientists and data scientists both live in a world of data, the data scientists have a far deeper set of technical capabilities. They understand how to interrogate data, how to manipulate and apply machine learning to the data; they have a technical level of expertise that information professionals don’t have. On the other hand, they may not fully appreciate your expertise in identifying resources, negotiating contracts, or working collaboratively to leverage the value of content.
5. Embrace change and take advantage of the opportunities you see. You either sit back and don’t innovate and become irrelevant, or you embrace the change and create your own opportunities. You need to constantly reassess what it is you deliver as an information scientist. 

Related to that last point, he noted that, if you had asked him 18 months ago whether he would be working on projects involving artificial intelligence, he would have recoiled in horror. Today, he is managing four AI-focused projects. When I asked how his team reacted to these changes, he described his approach: 

“I brought my team together and asked them to list on Post-It notes all the skills that they bring to the table as information scientists. What they didn’t know was that, in another room, I had already created a wall with Post-It notes listing all the skills I knew would be needed to run the AI project. I brought the team into the room and asked them to see how much overlap there was between the skills they have and the skills the project required. We all decided to embrace the change, have some fun and use our strong information science skill sets in these new areas.” 

By identifying the ways in which information scientists can best collaborate with data scientists, this information scientist ensures that the organization gets the most benefit from its information staff and resources. 

This is the first in a three-part series from Mary Ellen Bates around Info Pros in a Data Driven Enterprise. Subscribe to CCC’s Velocity of Content blog to receive the next installments directly in your inbox.  

The post 5 Tips to Establish Collaborative Relationships Between Info Pros & Data Scientists appeared first on Copyright Clearance Center.

Ringgold Solutions provides an authoritative organization data set including a persistent identifier (PID) that supports a wide array of use cases within scholarly communications. CCC’s Ringgold Identify Database covers all of the organizations that a scholarly publisher may have a relationship with including:

• Institutions that have signed Open Access agreements to understand author affiliations and funder information when creating, negotiating, and managing those deals in depth. We also include “read” organisations that don’t publish content, but need access to it and associated services, whether corporate, community college or governmental.
• Pre-undergrad organisations for publishers with content for newer readers.
• Small corporations that only publish one article – ever – so they can submit their article with an affiliation.

In essence, Ringgold Solutions cover any type of organization where a stakeholder, such as a publisher, funder, institution, or service provider may have an interaction with organizations for access, authorship, funding, customer service, and/or financial transaction – that’s the point, a complete view of organizations involved in the funding, creation and consumption of scholarly research.

Real World, Granular Hierarchies Support Unique Use Cases

The Ringgold Identify Database hierarchies are robust, granular, and reflect the real-world relationships between different entities. When properly structured, these hierarchies are straightforward to navigate and can be rolled up or down to determine relationships at parent and children levels. Ringgold structures multiple parents’ data in the Ringgold Identify Database user interface and data implementations, to make it easy to support requirements for different use cases (e.g. whether an organization should be included or excluded in institutional agreements and reporting).

When using such a detailed and structured database, it is important to know that there are policies in place and the curators are data management experts. Robust centralized curation creates uniformity, consistency, and reliability. Here at CCC we believe in data quality and utility. That’s why we capture any organization or sub-unit of an organization irrespective of whether it is independently funded or managed, that itself exists to sponsor, produce, or utilize research. We present real world organization data and metadata so clients have the flexibility to apply the Ringgold Data for different use cases.

Powering a Robust Network of Interoperable Systems

Ringgold Solutions supports and enables interoperability across the scholarly ecosystem. The Ringgold Identify Database holds ISNI IDs , an open, ISO standard that enables broader interoperability, for over 99.6% of our data. We hold Funder IDs to enable easy identification of relevant funder information Ringgold Identify Database maps to ISNI and Funder IDs one to one, because we believe that persistent IDs are designed to uniquely identify an organization.

Ringgold Solutions in Action: Inspec, the Institution of Engineering and Technology

The level of granularity of Ringgold data is essential to support author affiliation information. Authors want to be recognized for where they are affiliated, not just by institution but by part of institution. For an author, it’s important if your groundbreaking research came from a research institute or lab, and to retain that distinction. We see this from the IET’s Inspec analytics product which maps granular affiliation information from over 22 million records and groups together articles in very granular fields to enable users to find those organizations with strengths in specific disciplines making it possible to find new research partners – powered by Ringgold Identify Database. Looking for Key Opinion Leaders involves this level of detail. Furthermore, without granularity, accurately identifying conflicts of interest is next to impossible. In datasets that do not include subunits or do not include them consistently, it is very difficult to tell whether a person at one organization is in any way related to another by their affiliation.

Ringgold Solutions – Proven. Trusted.

When Ringgold started 20 years ago, we learned that you need to dig deeper to address real world complexity. Use cases evolve, they grow, and in a community needing data driven decisions – Ringgold Solutions accommodates the growing use cases for the future of our scholarly communications ecosystem with data that is detailed, robust, and trustworthy – that’s what sets us apart.

Keep reading Approaches for Understanding Data Quality in Ringgold Identify Database.

Learn more about IET Inspec uses the Ringgold Identify Database data to standardize and enhance organizational data.

The post What Sets Ringgold Solutions Apart appeared first on Copyright Clearance Center.

The demand for data scientists is indeed strong and is even accelerating, with the US Bureau of Labor Statistics expecting employment of data scientists to grow 36% from 2021 to 2031, much faster than the average for all occupations.

Data scientists are found working in fields where data-driven decision making dominates, from financial services and information technology to healthcare and biotech. They often work closely with librarians and others trained in information science. The two roles are complementary, and organizations can benefit from aligning the positions strategically.

Click below to listen to the latest episode of the Velocity of Content podcast.

Mary Ellen Bates advises clients in research-intensive industries on their information needs. This week, she will report on findings from her recent study of best practices for info pros when working with data pros at the Medical Library Association/Special Libraries Association joint conference in Detroit. In a preview, Bates tells me about examples of how and when info pros should participate in a data-driven research project.

“The info pros ensure that the organization isn’t spending a whole lot of money on data that can’t be used or that can’t be used the way they thought it could, that can’t be reused, and it causes more work downstream that isn’t worth the cost to the organization,” she explains.

“Often, it’s making a strategic decision about not acquiring one kind of data, because while it appears good, the info pros see the bigger picture and see that the ramifications of acquiring this data does not actually serve the organization as well as the data scientists may have thought of it.

Mary Ellen Bates presents, “Successful Info Pros in a Data-Driven Enterprise,” Thursday, May 18, 10:30 a.m., at the Huntington Place Convention Center.

On Friday, May 19, 9:00 a.m., Christine McCarty represents CCC in a panel discussion, “Standards Update: What’s New With Standards?”

Both programs are part of the Medical Library Association/Special Libraries Association joint conference in Detroit May 16-19, 2023.

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