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1 LINKED OPEN DATA AT THE UPF AUTHOR: JORGE PANTOJA MASTER THESIS UPF / 2013 SUPERVISOR Dr. MIQUEL OLIVER RIERA MASTER IN INFORMATION AND COMMUNICATION TECHNOLOGIES STRATEGIC MANAGEMENT BARCELONA SCHOOL OF MANAGEMENT

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3 Acknowledgments I dedicate this work to: My parents, sister and grandmother, for being a constant support for me Andrea, for always believe in me, being there for me and her constant love to me. Miquel Oliver, for his guidance, suggestions, constant support and inspiring activity My friends of UEPA, for being a great team this year I would also like to acknowledge the support I have received from my colleagues at the UPF, especially the Rectorate's Office and the NeTS Research Group. iii

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5 Abstract Linked Open Data is a movement to publish data and connect it on the web. Recently, this approach was extended to the education sector and universities play an important role on it. This creates some direct and extras benefits that can impact the current business models of the universities. The two main benefits are related to the improvement of the current transparency system and creating economic value over the data assets of each institution. The present work is mainly focused on describing the current evolution of this movement across European Universities, creating a guideline with best practices for universities and considering the initiative developed at the UPF as an example. Resumen Linked Open Data es un movimiento a nivel mundial para publicar datos y enlazarlos en la web. Recientemente, este enfoque se ha extendido al sector de la Educación, en donde las universidades juegan un papel importante. Esto crea algunos beneficios directos y extras que pueden impactar en los modelos de negocio actuales de las universidades. Los dos principales beneficios están relacionados al mejoramiento del sistema actual de transparencia y a generar valor económico sobre los activos de datos de cada institución. El presente trabajo está enfocado principalmente a describir la presente evolución de este movimiento a través de las Universidades Europeas, creando una guía de buenas prácticas para universidades y considerando la iniciativa desarrollada en la UPF como ejemplo. Resum Linked Open Data és un moviment a nivell mundial que té com objectiu la publicació de dades i enllaçar-les a través de la web. Recentment, aquest enfocament s ha estès cap al sector d educació superior on les universitats hi desenvolupen un paper central. Linked Open Data crea beneficis directes addicionals que poden tenir impacte sobre els models de negoci actuals de les universitats. Dues avantatges principals que ofereix Linked Open Data estan relacionades amb la millora del sistema actual de transparència i la creació de valor econòmic per part de tercers a partir dels actius de dades de cada institució. Aquest treball se centra principalment en la descripció de l'evolució actual d'aquest moviment a través d universitats europees, la creació d'una guia amb les millors pràctiques per a les universitats tenint en compte la iniciativa desenvolupada a la UPF com a cas d estudi. v

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7 Table of contents Abstract... 5 Table of contents... 7 List of Figures List of Tables INTRODUCTION What is Open Data? What is Linked Data? What is Linked Open Data? What is Open Innovation? Open Innovation Platforms Linked Open Data in Universities Thesis Goal and Objectives Thesis structure LINKED OPEN DATA AROUND THE WORLD Adoption and Relevance of Open Data Worldwide Linked Open Data across European Universities State of the Art on Open Data in Universities Research Findings Key aspects for a Linked Open Data portal Summary LINKED OPEN DATA EXAMPLE: UPF ECOSYSTEM The Ecosystem Ideas Flow Generation in the Ecosystem a) Driving innovation b) Business focus outcomes Stakeholders of the Ecosystem a) Students b) External Application Developers and Analysts c) Entrepreneurial and Business Community d) Teaching and Research UPF staff (PDI) e) Administrative and Service staff (PAS) f) Managers and Directors g) Affiliated Centers vii

8 h) International Universities and Organizations i) Local and International Governments j) Citizens Summary THE UPF CASE The UPF Linked Open Data Approach Open Data Projects at the UPF The UPF as part of the Web of University Data a) The process for Opening Data at the UPF UPF Business Model UPF Business Model Evolution Data Sources Available at the UPF The Process for Publishing the Data Open Data Policy Key Success Factors for the Linked Open Data initiative at the UPF Participation and Communication Summary LEGAL AND TECHNICAL ISSUES Legal Aspects, LOPD and Open Data Licenses Linked Data Modelling and Schema Metadata used at the UPF Arquitecture, Tools and Requirements of the Project Summary BENEFITS, RISKS AND OPEN RESEARCH TOPICS Benefits for the UPF Benefits for the European Higher Education Sector Open Data Economic Value Business Models Generation for the Education Sector The importance of standards Main Risks Open Research Topics for Linked Open Data Summary CONCLUSIONS AND RECOMMENDATIONS Conclusions Recommendations for future work at the UPF viii

9 BIBLIOGRAPHY AND REFERENCES GLOSSARY ix

10 List of Figures Fig A representation of an RDF Graph with two nodes... 2 Fig. 2 Open Innovation Platforms [17]... 6 Fig Countries offering open data (Data from the OKFN Census) Fig. 4 Capgemini Analysis Report about the Open Data Economy Fig Linking Open Data cloud diagram, by Richard Cyganiak and Anja Jentzsch.. 13 Fig. 6 Graphical Representation of the universities that have done more efforts in terms of linked open data Fig (a-b-c-d, from left to right, up to down) Study results: group of parameters: 1-4, according to Table Fig (a-b-c, from left to right, up to down) Study results: group of parameters: 5-7, according to Table Fig Linked Open Data Ecosystem across Universities Fig. 10 Stakeholder engagement in an open innovation scenario [25] Fig Puntaje de Universidades - Informe de transparencia en la web de las Universidades Españolas Fig Ranking - Informe de transparencia en la web de las Universidades Españolas Fig. 13 UPF Business Model Fig. 14 UPF Budget 2013 Incomes and Outcomes representation Fig. 15 UPF Expenses on research and materials Fig. 16 Indicadors de recerca i innovació de les universitats públiques catalanes Fig. 17 MIT Budget mix 2013 Incomes and Outcomes representation [30] Fig. 18 UPF - MIT comparison in terms of tuitions, investments and research Fig. 19 UPF Business Model Evolution considering Open Data Fig. 20 Open Data Influence within the current UPF Business Model Fig. 21 Institutional data at the UPF Fig. 22 Open Data publications processes at the UPF Fig. 23 Linked data schema at the UPF Fig. 24 Arquitecture of the Open Data Project at the UPF x

11 List of Tables Table 1 List of Universities with Open Data initiatives considered for the analysis Table 2 This table shows the number of datasets showed on the main web and as linked data graphs, the number of applications developed and the number of triples Table 3 List of parameters analyzed Table 4 List of Technological tools used within the open data portals Table 5 List of technological tools used for open data Table 6 List of technological tools for linked data Table 7 Common visualization tools used in open data Table 8 Steps for the linked open data project at the UPF Table 9 Recommended data types to be consider within the Linked open data project at the UPF Table 10 Open Data Licenses to be used within the Linked Open Data project at the UPF Table 11 Common linked data vocabularies Table 12 Metadata to use within the Linked Open Data Project at the UPF Table 13 Technological tools used for Opening the Data at the UPF Table 14 Staff requirements within the Linked Open Data Project at the UPF Table 15 Hardware requirements within the Linked Open Data Project at the UPF Table 16 Direct marginal benefits Table 17 Extras benefits Table 18 Open data business models for the educational domain xi

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13 1. INTRODUCTION 1.1. What is Open Data? Open data is a worldwide movement to open up public data within public and private organizations. In order to describe clearly this term, it is important to understand what means openness in relation to data and content. Therefore, we will use the statement given by the open definition 1 [1] about it: A piece of data or content is open if anyone is free to use, reuse, and redistribute it subject only, at most, to the requirement to attribute and/or share-alike. According to this, open data refers to publicly available data, without restrictions and at no cost. This data should be published under specific terms and structured formats, ensuring that the data is available to anyone and for any purpose. By anyone, means that the data should be understandable and usable, in machine-readable formats. The specific terms are represented through standard licensing agreements that permit the free of charge copying, use, reuse, redistribution and modification of the data, subject to attribution (BY) and share alike (SA) requirements 2. In order to guarantee the widest use of the data, it should be published as structured data and in non-proprietary formats What is Linked Data? Linked data goes a step further to publish and connect data on the web [2]. The idea is to create links among data from different sources, using unique identifiers [3] (i.e. URI 3 ) to represent real world objects and abstract concepts [4]. This allows sharing and relating data with a high level of expressiveness and semantics, in machine-readable and standard formats. Linked data is based on a set of principales and was originally proposed by Tim Berners-Lee in 2006, to apply the web architecture for sharing structured data on a global scale [5]. Now, it is considered a world movement that has been supported by several organizations, including governments, companies, startups, non-for-profit organizations, universities, among others [6]. In order to support this movement, Tim Berners-Lee suggested a five star deployment scheme to rank open data 4, which states the following (from less to more linked data ): One star: Make your stuff available on the web (whatever format) under an open license. 1 h p://opendefini on.org/ 2 h p://opendefini on.org/licenses/ 3 An URI (Uniform Resource Iden fier) provide a simple and extensible way for iden fying a resource that can use any of the internet protocols to be shared. 4 h p://5stardata.info/ 1

14 Two stars: Make it available as structured data (e.g., Excel 5 instead of image scan of a table). Three stars: Use non-proprietary formats (e.g., CSV 6 instead of Excel). Four stars: Use URIs 3 [3] to denote things, so that people can point at your stuff. Five Stars: Link your data to other data to provide context. Additionally to that, the same author recommends four rules when exposing Linked Data, those are 7 : Use URIs 3 [3] as names for things. For instance, ftp://data.upf.edu/resource.txt. Use HTTP URIs 8 so that people can look up those names. For instance, When someone looks up a URI, provide useful information, using the standards (RDF* 9, SPARQL 10 ). Include links to other URIs 3 [3], so that they can discover more things. In linked data, each dataset is a graph 11 that contains a set of triples using specific representations such as JSON-LD or the RDF model 9, which is a set of open formats to publish data on the web. A Triple is a data entity that relates one object with another (e.g. people, places, cars or relationships among them) and is composed by a subject, a predicate and an object (Fig. 1). Basically, a linked data file contains a lot of triples of data (i.e. represented with URIs 3 ) that may be saved in a triple store 12 (e.g. The RDF Datastore) creating a unique graph of data using these triples and the relations among the objects represented on those triples. Each graph (e.g. RDF Graph 11 ) or file, follows a specific schema and semantics to organize the data. This is done through vocabularies or ontologies, to define concepts and relationships over a specific domain and area of concern. These vocabularies and ontologies are formal conceptualizations to share a common understanding of the structure of the data 13. Fig A representation of an RDF Graph with two nodes 14 5 Excel is a proprietary format developed by Microso. 6 CSV (Comma Separated Values) is an open format that stores tabular data in plain-text form. 7 h p://www.w3.org/designissues/linkeddata.html 8 HTTP URIs, means using the internet protocol HTTP, to combine URIs with a simple and wellunderstood (universal) retrieval mechanism [4]. 9 RDF is a standard model for data interchange on the Web, using URIs to connect things. h p://www.w3.org/rdf/. 10 SPARQL is language to query and manipulate RDF graph content on the Web or in an RDF store. h p://www.w3.org/tr/sparql11-overview/. 11 An RDF graph is a set of RDF triples and a triple consists of a subject, predicate and object to represent resources on the web. 12 A triplestore is a purpose-built database for the storage and retrieval of triples. h p://en.wikipedia.org/wiki/triplestore 13 h p://www-ksl.stanford.edu/kst/what-is-an-ontology.html 14 h p://www.w3.org/tr/2013/cr-rdf11-concepts / 2

15 1.3. What is Linked Open Data? Linked data does not specifically means openness. In order to make data connected and open, it should be referred within the context of Linked Open Data. This means, exposing, sharing, and connecting related data on the web, through open formats and open licenses [7]. It allows metadata to be enriched and discoverable, creating network effects for the publication and linking of more data. Linked open data creates a powerful ecosystem where governments, businesses and citizens interact, sharing and consuming data [9]. This creates some direct marginal and extra benefits [10] that can be obtained by sharing and connecting data on the web. In governments, the process for collecting, managing and updating data is usually a service paid by taxes. The dissemination and share of that data is mainly done for transparency and accountability issues at some marginal distribution costs. At this point, linked open data brings the opportunity to optimize these costs, giving an additional value to the data with the possibility to have an average cost recovery, monetizing the untapped value of those data assets. It creates a public participation and collaboration system, where openness will strengthen democracy, promoting the efficiency and effectiveness in government activities. In the private sector (businesses) the situation is similar; it improves the relationship with customers, share costs with partners and generates revenue by monetizing data assets. This creates a competitive advantage for companies through direct interactions with customers, partners and suppliers. In the case of citizens, they can share personal and non-personal data, but it is more common for them to have the role of data consumers and as beneficiaries of the services generated within the ecosystem. Nonetheless, sharing personal data through anonimization techniques or pseudonymisation techniques [11] may help citizens to overcome privacy issues and to be benefited of the linked open data movement. Therefore, linked open data can help organizations to improve its transparency and accountability, but at the same time increase the value proposition of their data assets. Principally, it can spur the innovation and ideas generation with a business focus, through an effective communication strategy and public participation. Considering that, linked open data has become a strategic topic in the digital and yearly agendas for some public and private organizations, aligning their accountability strategies with their business priorities. For instance, governments that belong to the G8 15 have been developing open data initiatives in order to make their public data open, supported by specific policies and principles. Although most of these countries have already developed well-structured open data platforms, they have to improve and extend them, considering some relevant aspects such as quantity, formats, usability, quality, provenance and standardization. For instance, the data portal from the Government of the United States (data.gov) has more than datasets, but just a small portion of them have been converted to linked open data formats and most of them do not offer metadata related to quality and provenance. Another example is the data portal from the Government of the United Kingdom (data.gov.uk), that even though they have developed a mature platform that offers richer metadata; the government is continuously 15 The Group of Eight (G8) is a forum for the governments of eight of the world's largest na onal economies. h p://en.wikipedia.org/wiki/g8 16 h p://catalog.data.gov/dataset. Informa on collected the Nov

16 improving it, in terms of usability, quantity and standardization. In particular, the interest of the UK government is to promote the open data movement around the world. Similarly, organizations like the World Bank (data.worldbank.org) and the United Nations (data.un.org) have also developed open data portals in order to support this worldwide movement. Moreover, one of the most active participants of open data around the world is the Open Knowledge Foundation (okfn.org) that is a non-for-profit organization founded in UK that has created tools and dissemination practices for open data that are widely used around the world. Also, open data has been growing fast around the world. According to the 2013 Open Data Census 17 from the Open Knowledge Foundation, there are 76 international countries 18 that are already involved on this movement. For instance, most of them are publishing their transportation timetables and national statistical data. Among them, 62 countries are implementing ambitious open government reforms and participating in the Open Government Partnership 19 (OGP), which is a multilateral initiative launched in 2011 with 8 countries 19, and that today has a high relevance, demonstrating the importance of this approach around governments. On the list, Ecuador is not included and Spain 20 is part of it with a list of commitments to improve its transparency system and other aspects such as public administration. The data portal from Spain (www.datos.gob.es) has been categorized as the most user-friendly open-data website in the European Union (awarded by LAPSI) [8], for reusing public-sector information (i.e. PSI). In Ecuador, the first data portal was recently (datosabiertos.ec 21 ), but it is not an official effort from the government. These countries have been greatly benefited from this movement. For example, Spain has estimated the volume of business activities benefited by the re-use of open data in the infomediary sector, with a value between 332 and 550 million euros per year 22. Also, in 2010, the impact of the re-use of public sector information (i.e. PSI) in the EU27 economy was estimated at 32 billion euros, considering an annual growth of 7%. [12]. According to this, linked open data has been considered as a top priority for big and small organizations around the world that are aligning their open data strategies as part of their foundational mission, in order to improve their transparency and at the same time generating an additional value to their data. 17 evolu on and current state of open data around the world 18 h p://census.okfn.org/country/ 19 The Open Government Partnership is a mul lateral ini a ve that aims to secure concrete commitments from governments to promote transparency, empower ci zens, fight corrup on, and harness new technologies to strengthen governance. Data collected the Nov h p://www.opengovpartnership.org/about 20 h p://www.opengovpartnership.org/country/spain 21 Datosabiertos.ec, is an ini a ve from the organizacion fundapi (h p://www.fundapi.org/) and Inven o ESPOL E.P. (h p://www.inven o.gob.ec/). 22 h p://epsipla orm.eu/content/spain-yearly-re-use-turnover million-euro 4

17 1.4. What is Open Innovation? Innovation can happen in two scenarios: open innovation and closed innovation. In the second scenario, the ideas are generated and developed internally within an organization. This usually happens when a technology, product or concept is well known, but also can occur when other solutions in the market are not mature or available [14]. On the other hand, in an open innovation scenario, external resources are used and innovative ideas are shared in order to accelerate the innovation process [15]. This happens when the technology, product or concepts are not well known and consumer market preferences are dynamic. Basically, it creates a global collaboration scenario, sharing risk and sharing rewards 23, but at the same time, improving the efficiency and effectiveness. Some benefits of this approach are the reductions of costs for research, a better productivity and a better overview of the market situation. For instance, popular operating systems for mobile devices such as Android [13] or Firefox OS, use this concept to attract developers to create new applications using their platforms. They have opened their platforms through open licenses so they can be adapted and customized to any hardware platform. Both operating systems provide a marketplace, as a way to communicate developers with the consumer market, such as Google Play 24 or Firefox Marketplace Open Innovation Platforms The decision to open a product, knowledge or data to external innovators means that a platform will be created. This platform should be supported through a business model, with a special attention on the value proposition and the governance that will design the rules for it 26 [16]. According to Kevin J. Boudreau and Karim R. Lakhani, on its article on How to Manage Outside Innovation 26 [17], there are three categories of platforms, which are based on a basic question that determines how the platform will be managed: who sells to whom? These are the integrator, product and two-sided platforms (Fig. 2) [17]. The first one is the most profitable and the one that captures more value since there is more control on it. For instance, Apple Store. In the product platform external innovators can directly interact with end users, but the platform owners implement the rules. For example, core technologies that are used through licenses for other products or Amazon cloud services. In a two sided platform, external innovators and users interact directly [18]. This is the most innovative platform, since there is constant feedback on it. It grows fast compared 23 h p://www.100open.com/2011/03/open-innova on-defined/ 24 play.google.com 25 h ps://marketplace.firefox.com/ 26 h p://sloanreview.mit.edu/ar cle/how-to-manage-outside-innova on/ 5

18 to the others and the platform plays the role of an intermediary element. For instance, Sony PlayStation considering players and video games developers. The open data platforms replicate the last approach, since they can interact directly as collaborative platforms among users and the developers of new ideas. That is the reason why exposing data to external innovators, creates more value in data platforms and generates a constant flow of interaction in an ecosystem that can be benefited from network effects to growth fast in terms of data users, quantity and quality of data. Fig. 2 Open Innovation Platforms [17] 1.6. Linked Open Data in Universities Considering the vast interest on open data around the world, it has been extended to other areas, such as the education sector. This represents one of the main domains of the global economy that has a high relevance in terms of knowledge generation. Specifically in the higher education area (i.e. EHEA), universities have been active participants in this movement and recently they have considered it as an internal need. For instance, in Spain, the UPM (i.e. Universidad Politécnica de Madrid) has the Ontology Engineering Group (OEG) 27 which is an active research group in the area of linked open data. However, this university has not considered this approach as an institutional need. In contrast, just a few Spanish universities have implemented (linked) open data portals as an institutional effort: Universidad Pablo de Olavide, Universidad de Zaragoza and recently the Universitat Pompeu Fabra and Universidad de León. Analogously to the case of governments, linked open data in universities, supports the internal transparency system. For instance, publishing data related to internal activities and procedures of each academic term in open formats. But, considering that the 27 h p://www.oeg-upm.net/ 6

19 innovation processes belongs more to the enterprise rather than Universities, linked open data can also help to improve the internal innovation processes through an innovative ecosystem together with the entrepreneurial and business communities. In this ecosystem, the university, students, researchers, faculty staff and businesses interact, share, connect and analyze data continuously, giving an additional value to the data. This can benefit each university individually, promoting the continuous use of the data. For instance, the University of Southampton, continuously promotes the use of their data portal (data.southampton.ac.uk) to create new services, especially for the University. Until now, the university has created approximately 18 applications 28, through internal and external developers. Basically, it means that this approach can accelerate the flow of innovation and knowledge generation processes in a collaborative and fruitful way. According to that, it can help to wake up the entrepreneurial spirit of students and professors, fostering the creation of new research projects and ideas to develop new businesses from them. Providing updated data in structured formats, students, professors and researchers can work directly with the phenomena itself rather than just using theories with the probability of having problems getting the right data. In that way, universities are fostering the creation of new ideas giving an added and more applied value to their data streaming from the research. Also, linked open data goes beyond the individual benefit of each isolated institution. It can help to create a network of research results data, as a collaborative work among universities. This will help to create new platforms and applications, to have more reliable data about university results and offerings that can be more valuable for the society. Therefore, the expansion of this movement around the world is helping the education sector to understand that this approach is strategic for each university and that it can also bring benefits to the whole group of educational institutions in Europe. In the specific case of Universities, an open innovation approach will foster the generation of new ideas among students, professors and researchers. However, this requires changes in the cultural aspects of the organization, especially within the governance and policies of each academic institution. Implementing this approach, through an ecosystem powered by collaborative linked open data platforms, can enhance the value proposition of each academic institution, with the dissemination of open educational resources (OER 29 ), for instance, institutional, research and teaching data. 28 h p://data.southampton.ac.uk/apps.html 29 Open Educa onal Resources (OER) are freely accessible, usually openly licensed documents and media that are useful for teaching, learning, educa onal, assessment and research purposes. h p://en.wikipedia.org/wiki/open_educa onal_resources 7

20 1.7. Thesis Goal and Objectives This thesis goal is to study and analyze how the linked open data approach can be extended to universities, supporting the current transparency models and describing how it can improve the innovation processes, considering the Pompeu Fabra University (UPF) as a strategic example. To achieve this goal, the thesis integrates the following objectives: Describe what is linked open data, open innovation and its strategic impact across Universities. Study the current open data movement across European universities. Describe the linked open data initiative at the UPF. Indicate how the current business model of the UPF can evolve considering open data and open innovation. Explain the benefits of open data and the future work at the UPF. Describe the economic value of open data. Describe open research topics in linked open data Thesis structure Considering the open data and open innovation approaches, this work will be focused on studying the state of the art of linked open data across universities in Europe and to describe the institutional initiative at the Pompeu Fabra University (UPF) 30. The main idea of this work is to try to give a complete overview of the project, understanding all the benefits, the process that was used for the development and in which ways it can evolve the current business model of the university. The thesis structure is the following. In this first chapter, an introduction to linked open data and open innovation is given, emphasizing the importance of them among universities. Some examples of the evolution of the linked open data movement in Europe are given and the state of art of this movement across European universities is presented in the second chapter. Then, the open data ecosystem for the UPF is explained, indicating how the open innovation approach is related to it. In chapter four, the linked open data initiative at the UPF is described. In the next chapter, some points related to open data licensing, metadata, vocabularies and technologies are discussed. Then, the direct and extras benefits of linked open data are explained in chapter six including the possible risks in an open data implementation and an explanation of the open data economic value in the education sector. Finally in chapter seven, the conclusions of the project are given, and some recommendations for future work at the UPF University are presented. Also, some open research topics within the linked open data movement in the educational domain are discussed. In this first chapter we have observed that linked open data is a worldwide movement that has been extended to other areas such as the education. Open data has a close 30 data.upf.edu 8

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