Vienna, 21.08.2019 Library Services for Open Science Ricardo Eito-Brun Universidad Carlos III

1. Indexing and Organizing Knowledge to support Open Innovation Anew role for libraries in the Open Science context. Vienna, 21.08.2019 Library Services for Open Science Ricardo Eito-Brun Universidad Carlos III reito@uc3m.es

2. What is Open Innovation (OI) and related-information needs? • Which are the tools that we have to support OI? • What constraints do they have? • Proposed solution. Index

3. “An innovation is the implementation of a new or significantly improved product (good or service), or process, a new marketing method, or a new organizational method in business practices, workplace organization or external relations.” (Oslo Manual) • “doing things differently in the realm of economic life” (A. Schumpeter) Context of research:What is Innovation?

4. Innovation management (IM) is a sub-discipline of management that studies: • The rules that govern the generation, diffusion and adoption of innovation, and • The relationships between innovation inputs and outputs. • For a long time, innovation has been understood as a linear model: a sequence of steps – from basic research to serial production and market launch -, executed by a single entity. • In the linear model, the development of innovations depended on the funding and execution of internal R&D activities. • Linear models were replaced by collaborative models Context of research:What is Open Innovation?

5. Context of research:What is Open Innovation? • Collaborative models are based on feedback and interactions between partners. • The approach evolved to the Open Innovation paradigm proposed by Chesbrough (2003). • Today, innovation is seen as a: • non-linear, • evolutionary, • interactive process between the company and its environment, • that requires the close collaboration of different agents. • Ideas may come from both inside and outside the company. • Different agents have a different level of participation in the generation of the knowledge used as input to create new products

6. Context of research:What is Open Innovation? • Thepillars of Open Innovation : (Gassmann and Enkel, 2004): • Obtain, gather and integrateexternalknowledgefrom: • Clients. • Suppliers • Competitors • Universities • Research centers • Expose ideas (notnecessarily final products) to themarked. • Developpartnerships to combine skills, competences and complementarytechnologies.

7. Context of research:Open Innovation and Lead Users Regarding end-user involvement, Von Hippel (1998) was the first author to talk about “lead users”: “Users of a given product or service that combine two characteristics: • They expect attractive innovation-related benefits from a solution to their needs and so are motivated to innovate, and • They experience needs that will become general in a Marketplace, but experience them months or years earlier than the majority of the target market.”

8. The ProblemVisibility of innovation capabilities • OI depends on the ability to cooperate with other partners in the different phases of innovation: • Gather needs and requirements. • Design and construction. • Testing and validation • Launch to market. • OI is global: agents must give visibility to their capabilities and achievements (products, skills, patents, etc.) in a global context. • How can we identify partners in a global context? • Which are the tools that we have now to give visibility to other agents? • Business directories or databases • Collaborative, Web 2.0, Innovation platforms.

9. The problem Visibility of Innovation Capabilities Company databases • They focus on giving contact details and financial data. • They are oriented to assess the “health of the companies from an financial, economic perspective”. • Questions are: • Do these databases offer the data to support OI activities? • Do they provide data to identify areas of expertise and previous experience of companies? • How easy is to find partners for specific projects?

10. The ProblemVisibility of Innovation Capabilities • In addition, they have some constraints: • They are not exhaustive, and some of them exclude SMEs (and of course Lead Users). • They classify companies using large, general activity codes like SIC, NAICS, etc. • They focus on company financial data: sales, audits, #employees…. • In these database we cannot find: • Descriptions of products and services. • Projects and previous experience. • Technical achievements like patentsor papers. • Compliance with technical standards. • Information about their intellectual capital (skills, competences, areas of expertise)

11. The ProblemVisibility of Innovation Capabilities Collaborative, Innovation platforms • These are tools to support open innovation. • The differences between the different tools is fuzzy, as they share some features. • Types of tools: innovation contests, innovation markets, co-creation communities and toolkits. • Innovation Contests “A web-based competition of innovators who use their skills, experiences and creativity to provide a solution for a particular contest challenge defined by an organizer.” Examples: innovation-community.de, designboom.com, crowdsrping.com, deviantARt.com o newsgrounds.com.

12. The ProblemVisibility of Innovation Capabilities Collaborative, Innovation platforms • Innovation Markets • Virtual environmentsthatconnectdemand and supply. • Basedon Web 2.0 technology (social web) • Theyact as mediatorsbetweendifferentagents in theinnovationdevelopmentprocess. • InnoCentive, created in 2001 by Eli Lilly and usedbycompanieslike Procter & Gamble, Roche, NASA and TheEconomist. • Examples: InnoCentive, NineSigma, Atizo, Your-Entcore, Battle of Concepts, iBridge, Quirky, Yet2.com o BrainfloororTopCoder.

13. The ProblemVisibility of Innovation Capabilities Collaborative, Innovation platforms • Innovation Markets • The performance of innovationmarkets (Innocentive) wasanalyzedbyLakhani(2015). • 30% of theproblemsthatcompaniescouldnotsolveinternally, weresolvedbythe “users of the portal”. • Onaverage: • 240 personsanalyzedtheproblem • 10 potentialsolutionswereposted • Theeffortdedicated to solvethe problema was in between 74 hours and 2 weeks • Twothirds of “problema solvers” have a doctoral degree in scientificareas.

14. The ProblemVisibility of Innovation Capabilities Collaborative, Innovation platforms? • Innovation platforms are web-based workspaces designed to support the collaborative innovation process. • Open to any person or entity, not only to companies. • Registered companies post “challenges”, with a technical description of the problem to solve. • Participants can propose their solution to the problem. • The company selects the most suitable solution. • Main constraints: • Partners can be identified only in the specific context of a problem. • The tools do not support partners’ assessments: only the assessment of the proposed solutions. • In other words: you do not get any information about the “solver”.

15. The ProposalSemantic-based Directories • We can conclude that a different type of “directory” is needed to support and foster collaboration and innovation: • We need data about individual researchers, lead users, university departments, research groups, small companies. • We need additional data related to work experience, skills and technical achievements (patents, technical papers, products) • Any partner should be able of posting “innovation opportunities”. • We need support of specialized terminologies to describe content: • Areas of interest and expertise. • Challenges. • Achievements: projects, products, services, technologies, patents, papers…

16. The ProposalSemantic-based Directories • Remember that Innovation development is a knowledge-intensive process. • Oslo Manual uses the term “linkages”: Services that connect the innovative organization with other entities in its context: universities, suppliers, clients, competitors, etc., and establish flows of knowledge and technology.” • Open innovationtalksabout “absorptivecapacity” (Cohen and Levinthal 1990): “The ability of a firm to recognize the value of new, external information, assimilate it and apply it to commercial ends, being possible to distinguish between potential and realized absorptive capacity and the acquisition, assimilation, transformation and exploitation.“

17. The ProposalSemantic-based Directories • UNE-CEN/TS 16555-5:2015 EX: Collaboration management. • This standard recognizes the role of collaboration as an integral part of the innovation process. • According to this standard: • Collaboration must be managed systematically. • Open innovation is one type of collaboration. • Collaboration can be motivated by lack of resources, knowledge, share costs ad risks, IPR acquisition… • Collaboration needs tools to find good partners, knowing their experience is similar projects and their past performance.

18. The ProposalSemantic-based Directories • Purpose is “building an OI knowledge-based platform” that can be used in two different ways : • To identify partners in a global context. • To get guidance on the assessment of the ideas sent in response to “innovation opportunities” • Having more information about solvers, gives a higher level of confidence to the proposed solutions.

19. The ProposalDescription of the Platform • Area: Biomedical engineering This a new branch of engineering, with several branches: bioinstrumentation, biomechanics, biomaterials, etc., although main focus is on genetics, tissue engineering, medical software, simulators and medical imaging. • One of the pillars is the use of terminologies and controlled vocabularies to ensure the consistency of the items’ description and to improve the capability to find partners and assess their contributions. • MeSH is being used to leverage free text descriptions of agents, achievements and innovation opportunities (MeSH on demand).

20. The ProposalDescription of the Platform

21. The ProposalUse Cases (I) Management of Entities • They are: Companies, lead users, researchers, research groups, etc., who can contribute to the innovation process (as challengers or solvers). • Functions: • Entity Registration • Attach data to entities: documents, patents, product descriptions, research projects. • Data are indexed using controlled vocabularies (MeSH on Demand). • MeSH headings are added to free text descriptions. • Complete the “profile of the entity” using the terms assigned to its achievements.

22. The ProposalUse Cases (II) Management of Innovation Opportunities • These are: Challenges posted by any registered entity. • Functions: • Posting opportunities. • Classify opportunities using MeSH. • Match the opportunity with the existing entities’ profiles and make a selective diffusion of information.

23. The ProposalIndexing of content with controlled terms MeSHtermsassigned to a researcherusinghis CV as an Entry (onlytitles of publications)

24. The ProposalIndexing of content with controlled terms Productwhitepaper: Compare termsfromMeSHwith Company classification in BVJ databas: “Computerprogrammingservices”, “Engineeringservices” (SIC, CAE, NAICS, CNAE…)

25. The ProposalIndexing of content with controlled terms Challenge: Compare tagsgive in theInnocentivesitewithtermsfromMeSH

26. The ProposalPlatform

27. The ProposalDescription of the Platform • Document analysis can be used to identify additional experts, who can contribute to the innovation process (potential partners). • Example: expert network for radiotherapy simulation software

28. The ProposalDescription of the Platform • Generated with BibExcel and VOSViewer. • Example: expert network for entities

29. The ProposalDescription of the Platform • The same tools can be used to identify the terms that are used to describe a specific area of research. • These networks can be used to identify relationships between techniques, methods, etc., and to foster creative thinking.

30. Conclusions • Terminology – which is the basis of controlled vocabularies - is a a key component in knowledge-intensive activities and tools. • Control of terms is expected to improve: • Capability of finding partners in OI platforms (researchers, lead users, SMEs). • The dissemination of innovation opportunities and challenges by direct matching with the agents’ profiles. • Capability of getting information about the solver when making the assessment of the proposed solutions. • Additional opportunities: • Access to external databases via public APIs (like PubMed) to get additional data related to the challenges.

31. Our ResearchThanks • Thanks!