Thursday, March 30, 2017

Building the library of the future



Building the library of the future

The array of forces that impact upon the library’s operating environment makes any modelling of transformation during the coming years an almost impossible task. The political and economic forces that drive the functions and finances of parent institutions, the imperative for commercial publishers to meet investor’s demands for earnings per share growth, technological advances from Silicon Valley and beyond, are all part of the world in which the library will have to flourish.

What we can do, however, is look at trends and consider how best to take advantage of these to develop a library that is positioned for success tomorrow. A glance at the world of the academic library in 2017 reveals a few key themes that are conditioning professional practice, resource allocation, and investment priorities. These include the creation of advanced learning environments for students, an increasing move towards a global, distributed collection of information resources, the deployment of tools and technologies required to curate the evolving scholarly record, and a growing expectation of both domain and methodological expertise among recruits to the library profession.

Against this backdrop, in its strategic plan to 2025, Carnegie Mellon University announced its intention to create a 21st century library that serves as a cornerstone of world-class research and scholarship. While a large part of our vision is built upon a large-scale shift to digital forms of content, and web-based services, we are certain that the library will remain a vital presence on campus. 

We see a need to celebrate an enduring sense of ‘libraryness’ – an environment and culture that supports scholarship and provides access to professional librarians in interactive research and study environments.

It is our view that the abundance of scholarly content in digital form brings a degree of complexity that will only increase demand for expertise in information discovery and organisation.

We set out four key themes:
  • Develop information specialists as partners in research, teaching, and learning;
  • Collaborate with peer institutions to provide co-ordinated access to a global collection of information resources;
  • Steward the evolving scholarly record, and champion new forms of scholarly communication; and
  • Be recognised globally as a leader in the development of the scholarly information ecosystem.
To understand the world in which these themes will unfold, we need to reflect upon some of the trends evident in today’s library. These are neither exhaustive, nor are they mutually exclusive: I make this point to highlight the complex world of the contemporary research environment.

21st-century library spaces for 21st-century learners
Today, many universities are building new, or remodelling old, libraries to meet demands for serious space – learning environments that support interactions with information in a variety of forms. The design of the contemporary library draws heavily upon the space reallocation made possible by advanced storage retrieval systems (bookBots) and the transfer to offsite storage of lesser-used collections, freeing up space to meet student demand. While today’s libraries are busier than ever, few students make extensive use of traditional offerings such as lending collections and reference services.

Libraries will continue to be recognised as a place of research and learning for the entire university community, at the heart of the campus-based experience. They will provide an array of spaces to meet a variety of learning needs: individual and group study, collaboration and fabrication spaces, active learning studios, and an array of specialist learning technologies. As access to the contemporary scholarly record in digital form becomes universal, libraries will create specialised facilities for the special collections and archives which distin guish most clearly one library from another. On many campuses, libraries will also serve as an academic commons, providing an opportunity for faculty and students to interact across disciplinary boundaries, and in a space that reflects the diversity of the university community.

Access to a global collection of information resources

Today’s library collections remain distinctly hybrid: a blend of print collections acquired over many years, coupled with digital collections purchased or licensed from commercial publishers and learned societies. Institutional and disciplinary repositories have been in operation for more than a decade and are, increasingly, being joined by data repositories as important parts of the scholarly information system. Open access publishers such as PLoS have led the way in building complex and interactive articles, which are presented alongside data, executable content, and other artefacts of the research process.

We are almost at the point where all scholarly information exists in digital form, and open access to books and journal articles will transform scholarly publishing models. The need to build and own library collections ‘just in case’ will be overtaken by a network login model. Such a model will operate across a vast array of content, including the huge resource of digitised archives and special collections developed by the academy over the past 20 years, and large-scale collections presented by Google and others. Scholarly content will be discoverable through robust search facilities, and delivered through shared, licensed collections. 

The evolving scholarly record

Until the late 1990s, researchers built their information workflows around the library, where both the research record and current content were provided in printed form. In today’s digital world, researchers’ access to information takes place outside the library, and to remain a vital part of scholarship, libraries must develop their services around the researchers’ workflow.

We increasingly recognise the importance of going beyond our role as information providers and into an environment where we provide services and expertise in all information aspects of the research process. This includes the creation and operation of campus research information systems, using proprietary services such as Symplectic Elements, which allow easy curation and re-use of a scholar’s publications record, and indicators of the impact of their work from citation and altmetric databases.

We are also offering support in the curation and showcasing of outputs from the research process. Institutional repositories are being augmented by data and software curation services such as Figshare, helping researchers meet the growing open access requirements of their funders and their institutions.

In the near future, the print-centric scholarly record will have shifted to a complex series of digital and networked objects. Data, computer models, lab notebooks, blogs, community review and discussion, interactive and executable content will all form the record of scholarship alongside articles and monographs. Library services will be developed to capture, preserve, and share this record, promoting re-use and curation.  Research funder needs will be assessed and managed, for example through the creation of data management plans.

I’m often surprised when people tell me they think the internet put librarians out of business.  In reality, our expertise is in even greater demand than it was in the print world, although the skills and domain knowledge have become more complex.

Our colleagues will be recognised as information specialists closely integrated with the academic communities they serve. They will bring expertise in information activities to all aspects of the research process including grant applications, data management planning, measuring and improving research impact, publishing and information discovery, storage, and re-use. They will also be key partners in learning and teaching, building digital learning objects, developing digital literacy skills, and preparing students for careers in the knowledge professions.

At Carnegie Mellon University we appreciate our good fortune in creating our library of the future in a university that is home to one of the world’s leading schools of computer science, with a machine learning department specialising in fields such as advanced data manipulation and the development of algorithms to improve search, discovery and retrieval. We see their research interests aligning closely with some of the major challenges of information use in a digital world. For example, how do we best replicate serendipity in a massive-scale digital library? How do we help a researcher sift and understand the key content, when in some fields it is impossible for experts to keep up to date with the volume of core literature being published each year? How do we help a student identify the most relevant material scattered across commercial publishers’ sites, university repositories, in print collections and in the open web?

We anticipate an ambitious research agenda to investigate these and other facets of the library of the 21st century.  A century ago, Andrew Carnegie created and defined the library of the 20th century. Our ambition is that the university which bears his name will define the library for the next 100 years.


Regards

Pralhad Jadhav

Senior Manager @ Knowledge Repository

Khaitan & Co      
                                                              
Upcoming Event | MANLIBNET 17th Annual International Conference on 15-16 September 2017 at Jaipuria, Noida, India 


NCVT To Award Class 10 And 12 Certificates To ITI Students, Says Union Minister



NCVT To Award Class 10 And 12 Certificates To ITI Students, Says Union Minister

New Delhi:  The central government has proposed to set up a separate board for Industrial Training Institutes (ITIs). The board will allow them to conduct exams and award certificates at the same level as education boards like CBSE. The proposal was accepted by the Ministry of Human Resource Development (MHRD). The move is expected to aide more than 2 million students who graduate from over 13,000 Industrial Training Institutes every year. It will also help students in pursuing regular courses from other schools and colleges.

As per reports in press Trust of India the Union Skill Development & Entrepreneurship Minister Rajiv Pratap Rudy, today informed the Lok Sabha that the proposed ITI Board will be formed on the lines of CBSE and ICSE. He also informed that the certificates awarded by the board will be equivalent to class 10 and class 12 certificates which are issued by regular school education boards in India.

Rudy admitted that recently there has been a decline in the quality of education being provided at various ITIs but he assured that in coming years new ITIs set up in the country will be at par with the quality of central schools such as Kendriya Vidyalayas and other training institutes providing quality education. He said,"23 lakh students used to pass out from ITIs but did not get the equivalent certificate of X or XII standard because no such provision was there earlier".

Senior Officials in the Ministry of Skill Development and Entrepreneurship, said that once the proposal is fromalised, the National Council for Vocational Training (NCVT) will have the proper authority to conduct examination and award certificates for class 10 and class 12 enrolled in ITIs.


Regards

Pralhad Jadhav

Senior Manager @ Knowledge Repository

Khaitan & Co       
                                                             
Upcoming Event | MANLIBNET 17th Annual International Conference on 15-16 September 2017 at Jaipuria, Noida, India 


Intelligent adoption of artificial intelligence



Intelligent adoption of artificial intelligence

AI has the potential to disrupt the core of business processes. However, blind adoption of technology and hype-based purchase may not lead to the desired results

Artificial intelligence (AI) is one of the most talked about technologies in recent times. It is capable of increasing enterprise revenue through identifying, analysing and, most importantly, acting on the insights from underlying data. The pertinent question is, “Should we wait for AI to evolve fully and then apply it or should we look at specific applications to solve business challenges?” 

Range of AI—Human assistant to human replacement

The combination of parallel processing power, massive data sets, advanced algorithms and machine learning capabilities are spawning varied versions of AI systems. 

Today, AI capabilities vary from specific/narrow to super, all-encompassing AI. 

Narrow, or specific AI, is an intelligent assistant that can aid humans in making complex decisions and enhance their cognitive powers by processing vast amounts of data. It can conceptualize and correlate data, recognize the patterns and deliver intelligent output. 

For instance, soft AI can be used to detect frauds in various sectors such as banks. 

A large sample of fraudulent transactions is fed into the AI system, which is trained to look for signs that separate fake transactions from genuine ones.

Another example of soft AI is the voice assistant that can understand voice inputs, analyse data about the users from a variety of sources (social media, smartwatches, etc.) to better understand their behaviour and deliver results tailored to users’ preferences.

Super, or strong AI, aims to make decisions on its own without any external support. 

These machines can think, learn, decide and converse like humans. Hence, they have the ability to replace humans altogether. 

However, super AI systems are yet to achieve breakthrough improvisation to fully comprehend human mind-maps and replicate human intelligence.

How is AI different from RPA and cognitive?

Though enterprises are increasingly understanding the benefits of AI, there still exists misperception around similar technologies—AI, robotic process automation (RPA) and cognitive. 

AI is described as the decision-taking capability based on simulation of human intelligence processes by machines. These machines “can act” as human. 

On the other hand, cognitive computing helps humans in fully or partially delivering judgement-based processes and assists in their decision-making. These systems deal with unstructured inputs, and “can think” as humans. 

The third type, referred to as RPA, can automate rule-based tasks and “can do” what humans can. Such systems lack self-learning capability and are effectively dumb: they just perform exactly as programmed. 

AI-use cases in business

As customers are becoming increasingly demanding, AI offers assistance on key requirements of evolving business: 

People-centric: The AI systems enable the enterprises to shift to a people-centric approach from being process-centric. The decisions are made based on unstructured real-time data rather than pre-defined processes. For instance, ride-sharing companies predict fleet demand based on factors such as weather forecasts, time of the day and historical customer behaviour.

Ease of use: AI enhances customer experience with offered convenience and assistance. For example, enterprises are using “customer digital assistants” that can recognize customers by face and voice to have relevant conversations, and provide tailored choices to help them make purchasing decisions.

Self-adaptive: AI has the capability to self-evolve, make connections between data, improve on past decisions and get smarter. For instance, machine learning-based intelligence enables an enterprise to improve sales performance by accurately predicting cross-selling and up-selling opportunities.

AI implementation strategy for enterprises

AI has the potential to disrupt the core of business processes. However, blind adoption of technology and hype-based purchase may not lead to the desired results. Enterprises can ride the wave of success with efficacious adoption of AI technology:

Getting familiar with the concept: Rather than adopt the technology in haste, enterprises should first educate themselves on the basic concepts and capabilities of AI. The better a company understands what narrow/soft AI does, the more likely is its successful adoption.

Identifying the problem to which AI is a solution: Enterprises should identify specific use cases in which AI could solve business problems and help them achieve specific project goals. They should further narrow down the possible AI implementations by assessing potential business and financial values.

Bridging the talent gap: AI requires talent pool with a strong understanding of advanced programming, domain knowledge and business context. Enterprises should bring these skills together instead of waiting for one person to bring all the dimensions. 

The importance of AI is well understood. However, its implementation remains limited.
It is imperative for firms to start applying AI for solving narrow-scope problems before expecting it to disrupt the core of the business. 

AI can be employed for everything from managing targeted advertisements to optimizing logistics to tracking assets to understanding the customers’ social behaviour. The trick is to get started on the right note.

Source | Mint – The Wall Street Journal | 30 March 2017

Regards

Pralhad Jadhav

Senior Manager @ Knowledge Repository

Khaitan & Co          
                                                          
Upcoming Event | MANLIBNET 17th Annual International Conference on 15-16 September 2017 at Jaipuria, Noida, India