Program

Opening – Arlindo Oliveira (INESC-ID, IST/UL President), José Borbinha (INESC-ID, IST/UL), Gabriel Coimbra (IDC)

Information Digital Transformation Maturity Model – Gabriel Coimbra (IDC)

Technology Demonstrations

• Tableau data visualisation and analytics – Ricardo Pires (Xpand-IT)
• Pentaho data integration and analytics – André Lopes (Hitachi)
• SAS advanced analytics – Ricardo Galante (SAS)
• Celonis Intelligent Process Mining – Rafaela Nunes (Noesis)

LEGO Serious Play® – creative thinking through team building (exercise) – Bruno Horta Soares (NOVA IMS, IDC)

Open Panel – José Tribolet (INESC President, INESC-ID, IST/UL), José Borbinha (INESC-ID, IST/UL), Gabriel Coimbra (IDC)

Closing Session

Arlindo Oliveira is a professor of the Department of Computer Science and Engineering of Instituto Superior Técnico (IST), and a researcher of the IDSS Laboratory of the INESC-ID. He is presently the President of IST and member of its executive board. His major areas of interest are Algorithms and Complexity, Machine Learning, Bioinformatics and Digital Circuit Design. He recently published the book “The Digital Mind: How Science is Redefining Humanity“.

José Borbinha is professor of the Department of Computer Science and Engineering of Instituto Superior Técnico (IST), and coordinator of the IDSS Laboratory of the INESC-ID. His research interests are in conceptual modeling, requirements engineering, enterprise architecture and information management. He is the project manager of the ISO/TC 46/SC 11/WG 15 on Records Requirements in Enterprise Architecture, and is member of the coordination team of the of the eArchiving Building Block of the European CEF program. He was the CIO of the National Library of Portugal from 1998 to 2005.

Process Mining

This session will introduce the fundamental concepts of process mining, namely what is an event log and how to analyze an event log in order to discover, for example:

• the sequence of tasks;
• the interactions and collaborations between users;
• the average time that is spent on performing each task.

This session was originally presented by professor Diogo Ferreira at DELix 2018, and is based on this book:

A Primer on Process Mining: Practical Skills with Python and Graphviz, D. R. Ferreira (Springer, 2017) 

Luís Valadares Tavares is a professor emeritus of Systems and Management of the University of Lisbon (IST – Instituto Superior Técnico), President of OPET – Portuguese Observatory of Technology Foresight, President of APMEP – Portuguese Society of Portuguese Markets, Chairman of the European Conferences on E-Public Procurement, Non-Executive Member of the Board of Martifer.

Systems Sciences: From Optimization to Contracting in Digital Economy

João Gama is Associate Professor of the Faculty of Economy, University of Porto and researcher and vice-director of the INESC TEC research group LIAAD. He has researched on Incremental and Adaptive learning systems, Ubiquitous Knowledge Discovery, Learning from Massive, and Structured Data, etc. He is author of several books in Data Mining and authored a monograph on Knowledge Discovery from Data Streams.

Data Mining

Nowadays, there are applications where data is best modelled not as persistent tables, but rather as transient data streams. This keynote discusses:

• The limitations of current machine learning and data mining algorithms;
• The fundamental issues in learning in dynamic environments like learning decision models that evolve over time, learning and forgetting, concept drift and change detection.

Data streams are characterized by huge amounts of data that introduce new constraints in the design of learning algorithms: limited computational resources in terms of memory, processing time and CPU power. This talk will present some illustrative algorithms designed to taking these constrains into account. We identify the main issues and current challenges that emerge in learning from data streams, and present open research lines for further developments.

António Rito Silva is a professor of the Department of Computer Science and Engineering of Instituto Superior Técnico (IST), and researcher at INESC-ID, in the Software Engineering group, where he promotes activity on Social Software Engineering research, focusing on the interaction between people and software. He has been involved on the design and development of software systems for Digital Humanities, Flexible Workflow Systems, and Microservices architectures.

Adaptive Workflow

Business process management has been focusing on the optimization of work by enforcing a standard behavior shared across the organization. However, this emphasis on optimization and standardization is not suitable to the type of work where knowledge workers are involved due to limitations in the flexibility of the business processes. Therefore, this talk will present a set of proposals that relax the traditional approach to business processes based on the optimization, and provide to the knowledge workers the complete context of execution, such that they can take informed decisions when performing their work. 

Pedro Sousa is professor of the Department of Computer Science and Engineering of Instituto Superior Técnico (IST), and a researcher at INESC-ID, in the IDSS laboratory. He also work at Link Consulting, were is responsible for Enterprise Architecture and Cartography professional services in significant organizations in several industries, public and private, national and international.

Enterprise Cartography

Enterprise cartography deals with methods and tools to allow an organization to have updated representations of its architecture at any given moment, given a pipeline of ongoing and approved transformation initiatives. With so many changes underway, organizations have difficulty to keep track of the systems (components) and their dependencies along the time. As a consequence, organizations tend to delay as much as possible the detailed planning of transformation activities, with an impact on actual costs, time and risk. This talk presents a cartographic approach and the Atlas tool that enable organizations to keep enterprise architecture views up-to-date with near zero effort since the necessary information to perform the updates already exists in transformation initiatives plans.

Diogo Proença is a Post-Doctoral researcher at INESC-ID, in the IDSS laboratory, and lecturer at the Department of Computer Science and Engineering of Instituto Superior Técnico (IST). He is currently working in research projects in information retrieval and in technology transfer in long-term information assurance (this one in the scope of the eArchiving Building Block of the European CEF program).

Process Compliance and Maturity Assessment

This lecture will provide the fundamental concepts on process compliance and maturity models, and will show how this technique can be used to support process compliance. The lecture will make reference to the main standards in industry and the state of the art in research.

Alberto Cunha is a professor of the Department of Computer Science and Engineering of Instituto Superior Técnico (IST). He was a researcher at INESC were he was involved in the design, development, and technology transfer, of innovative systems for office automation and electronic ticketing. He was member of the BoD of the Aitec-Link group with particular responsibility in the design of solutions and products for the Transports and Mobility sector. In 2009 he co-founded YouMove-Card4Business which developed many of the electronic ticketing systems for public transport in Portugal. From 2010 to 2013 he was member of the BoD of Taguspark, the main Science and Technology Park in Portugal, responsible for the bootstrap and operation of Taguspark business Incubator for technology-based startups.

IoT Challenges

Electronics and sensor technologies enable mobile and personal devices and equipment (smartphones, smart cards and tags) with considerable computing and communication power, and will enrich our surrounding environment with sensory and reactive capabilities. The orchestration of all this potential, integrating Internet-based as well as specialized heterogeneous sub-systems, is the foundation of cyber-physical systems able to adapt in time to the context of use. In this lesson we will address:

• the architecture of intelligent sensors and embedded systems, its processing and communications constraints;
• the basic models for local cyber-physical interaction;
• models for data integration from sensor to IT infrastructure.

Finally we will analyze some cases of application of these technologies to monitor human activities and services.

Miguel Coimbra is currently a PhD student at Instituto Superior Técnico  (IST) hosted as a researcher at INESC-ID. He is researching distributed graph processing techniques, in the scope and with the support of the Distributed Systems Group (GSD) and the Decision Support Systems (IDSS) laboratory of the INESC-ID. He has been teaching assistant at the IST in several courses (Operating Systems, Network and Computer Security and Distributed Systems). He also has interest in data visualisation software.

Monitoring IoT with Grafana Dashboards (demo)

In the Internet-of-Things (IoT)  devices are ubiquitous and all interconnected. Everyday we see new applications of technology such as wearable devices, smart houses, smart grids, smart agriculture, Industry 4.0, etc. With a volume increase of the data surrounding us, we need to be able to understand it better and faster, in order to be informed, so visualisation can be very helpful.

Cláudia Antunes is a professor of the Department of Computer Science and Engineering of Instituto Superior Técnico (IST). She has been working on algorithms and methodologies for pattern mining, from transactional to structured data. Her main interests are centered on mining complex knowledge from complex data, with emphasis on the incorporation of background knowledge in the data mining process. Her work has been around the usage of domain ontologies to represent that knowledge, and she has been working on methods to efficiently mine patterns, guided by that knowledge. 

Data Science Fundamentals

What is data science and how does it work? Is it the new saint Graal and the solution for all problems? On a time, when everything is ‘intelligent’ and automatic, what is the role of humans? This talk tries to give some answers to those questions, demystifying the terms and the differences to artificial intelligence and machine learning.

Miguel Won is a Post-Doctoral researcher at INESC-ID, in the IDSS laboratory. He is currently working in the domain of Natural Language Processing (NLP) applied to Political and Communication Sciences.

Named Entity Recognition in Text-as-data (demo)

Within the context of text-as-data paradigm, new type of analysis and metrics are today available to the political science research, allowing new and different approaches that previously were virtually impossible. In this short talk Miguel will show how text processing, in particular named entity recognition and key-phrase extraction tools, can help and guide political scientists in their research questions.

Rui Henriques is professor of the Department of Computer Science and Engineering of Instituto Superior Técnico (IST), and a researcher at INESC-ID, in the IDSS laboratory. He was AI and Data Science team leader at Tekever, and a Post-Doctoral Researcher at Kyushu University.

Mining Event Data

This lecture will provide the essential principles and a structured view on how to learn from complex temporal data.
Although time series data and sequence data are pervasive within organizations, many of the collected data are not adequately described by these simplistic data structures. As such, this lecture will recover basic principles from time series data analysis and process mining in order to establish more advanced principles for the unsupervised and supervised learning from collections of heterogeneous events and multi-dimensional databases.

Luis Cruz is currently a Ph.D. Student at the University of Porto, hosted as a researcher of the Information and Decision Support Systems Lab at INESC-ID. He is also a member of the Green Software Lab. His research interests are mainly Green Software, Mobile Development, Machine Learning and Living Analytics. He has been involved in data science projects with companies such as PARC, a Xerox company, and Procter & Gamble.Luis is currently applying data science principles and techniques in his Ph.D. to improve mobile development processes concerning energy consumption of smartphone applications.

Data Cleaning

Clean your data if you care about its quality. Data wrangling is crucial to ensure that data is appropriate and ready to be used for analytic purposes. Often raw data comes with a myriad of different types of errors and inconsistencies. Thus, data transformations have to be performed before we can extract meaningful knowledge from our data. Raw data has to be transformed until we reach a criteria of data quality. This is why data wrangling comes with a distinct but no less important task: data quality assessment. In this lesson, we will first introduce the notion of data quality as an activity that encompasses two main tasks:

1. data quality assessment; and
2. data wrangling.

Second, we will explain the notion of data profiling which enables to assess the quality of a data set. Third, we will describe one of the main tasks of a data cleaning process that consists on the identification and consolidation of records that concern the same real world entity, also called approximate duplicate records. Finally, we will list some of the main data quality tools.

Francisco Santos is a professor of the Department of Computer Science and Engineering of Instituto Superior Técnico (IST) and researcher at the Group on Artificial Intelligence for People and Society (GAIPS) of the INESC-ID. He is interested in applying and developing modelling tools to understand collective dynamics in social and life sciences. He has been working on problems related to the evolution of cooperation, human social norms, network science, and environmental governance, among others. Francisco was distinguished with the 2017 Young Scientist Award for Socio- and Econophysics of the German Physical Society.

Alexandre Francisco is a professor of the Department of Computer Science and Engineering of Instituto Superior Técnico (IST), and a researcher and co-coordinator of the IDSS Laboratory of the INESC-ID. He is interested in algorithm engineering and computational science, and has been involved in several projects on computational biology, bioinformatics, graph mining, data and network analysis.

An Introduction to Network Science + Graph Analysis and Mining

These two coordinated lectures will provide the fundamental concepts and techniques on network analysis and graph mining. In particular, we will discuss large graph representations, the computation of many vertex/edge centralities, community detection and pattern mining on graphs.

Elsa Cardoso is Assistant Professor at Instituto Universitário de Lisboa (ISCTE-IUL), in the Information Sciences and Technologies Department of the School of Technology and Architecture, and a researcher of the IDSS Laboratory of the INESC-ID. She is the Director of the Master in Integrated Business Intelligence Systems at the same university and the leader of the Business Intelligence Task Force of EUNIS (European University Information Systems organization). She is also a researcher at the IIDSS Group of INESC-ID. Elsa has a PhD in Information Sciences and Technologies from ISCTE-IUL, with a specialization in Business Intelligence. Her research interests include business intelligence and data warehouse, data visualization, and strategic information systems (balanced scorecard) applied to Higher Education, Healthcare and Digital Humanities.

Business Intelligence and Analytics

We have been developing Business Intelligence (BI) systems for decades and BI techniques have become pervasive in many areas, including business process management. Current demands in terms of the massive volume and variety of data that is being generated poses new challenges to existing architectures. How can organizations adapt to this “data-rich environment” and effectively use data for decision making? In this talk we will address this issue and discuss different types of analytics projects.

Daniel Gonçalves is a professor of the Department of Computer Science and Engineering of Instituto Superior Técnico (IST),and a researcher at the Visualization and Multimodal Interfaces Group of INESC-ID. His research encompasses the areas of Information Visualization, Personal Information Management and Accessibility. He has published over 160 peer-reviewed papers publications in those areas, as well as being the co-author of a textbook on Human-Computer Interaction.

Data Visualization

One of the most effective ways to make sense of a dataset is to leverage our ability to visually identify interesting items patterns, by using Information Visualization (InfoVis) techniques. In this lesson we will focus on how Information Visualization can be effectively used to make sense of, for example, time-dependent data (such as streams). We will cover the following topics:

• Introduction to InfoVis
• Basic Perceptual Principles
• Representing Time-Dependent data
• Dealing with complexity

Bruno Horta Soares is Leading Executive Advisor at IDC Portugal, for Digital Transformation, Governance, Strategy and Security. He has a 5 years degree in Management and Computer Science, from ISCTE and a post-degree in Project Management, from ISLA Campus Lisboa. He is certified in Project Management Professional (PMP), from PMI, Certified Information Systems Auditor (CISA), Certified in the Governance of Enterprise IT (CGEIT) and Certified in Risk and Information Systems Control (CRISC) and COBIT 5 Foundation from ISACA, ITIL® version 3 Foundation and ISO/IEC 27001 LA . He’s also APMG individual accredited trainer for COBIT 5. He is the founding President of the ISACA Lisbon Chapter, member of several professional associations in the areas of Auditing (IIA), IT Governance (ISACA, IPCG), and Project Management (PMI) and keynote speaker at various conferences and seminars.

José Tribolet is a professor of the Department of Computer Science and Engineering of Instituto Superior Técnico (IST), and a researcher of the IDSS Laboratory of the INESC-ID. He co-founded in 1980 the INESC – Institute for Systems and Computer Engineering, the first not-for-profit, non-state-owned contract based research organization of Portugal, which he presides ever since. His research interests are in the fields of organizational modeling, business process engineering and information systems architecture.

Ricardo Pires is Partner and Business Intelligence Lead at Xpand IT. He has over 10 years’ experience on the implementation of business intelligence solutions. During this period, he has implemented and managed many projects using mainly agile methodologies and also performed training sessions and workshops worldwide. Currently as the business intelligence unit leader at Xpand IT he manages this practice, ensuring its’ strategic planning and alignment with the company goals as well as overseeing the team. He is a data enthusiast as well as a Tableau and Pentaho fan.

Data Visualization with Plateau

Tableau is the leading software for BI & analytics, allowing people to see and understand their data. Data is at the heart of organizations and the fact that Tableau is so intuitive allows users to answer questions about their business faster than ever.  During this presentation you will see Tableau in action, going from data to business insights in minutes and even how to leverage Tableau extensions to bring business processes into this modern BI environment. 

Andre Lopes took is degree from the University of Coimbra, Departamento de Engenharia Informática. He is a Principal Consultant of Hitachi Vantara, with several years of experience in Pentaho Software, Data Modelling and Business Intelligence. Before Hitachi Vantara, he worked in a big consulting company in projects in the Financial industry related with customer data, and also in one of the biggest Portuguese companies that sells a product to Telco companies worldwide. As a Principal Consultant in Hitachi Vantara, he is responsible to meet with the customers, understand their problems, position the company and its products and define and agree to a solution which will be implemented by the Services team, which he also supports.

Business Intelligence with Pentaho

Pentaho is one of the main products of Hitachi Vantara and is the leading open source end to end framework in Analytics. Pentaho provides data preparation, enrichment and analysis with a GUI approach using the PDI tool, and complements that functionality with a rich visualization layer where that data is presented. On this presentation you will see how to onboard data using PDI, transform that data, and make it available to be consumed for other tools and processes. Additionally, you will also see some pre built dashboards to see how Pentaho can help you visualize your data.

Ricardo Galante is a Senior Analytics Systems Engineer at the SAS Sales Division, at the Portugal subsidiary of SAS Institute Southern Europe. He has over 15 years of experience in analytics, with solid background in statistical, data mining and text mining techniques and also large experience in SAS programing language, SAS solutions, SAS University Edition, R, Python, S-Plus, Weka, Statistica and others tools. He was a Statistical Training Specialist Leader in the SAS Education Division, at the Brazilian subsidiary of SAS Institute, where I instructed and consulted with professionals and analysts from financial, market research, heath care, insurance, retail and oil and gas industries. Also, was Senior Consultant Pre and Post Sale in the SAS Sales Division, at the Brazilian subsidiary of SAS Institute, where I supported the Sales Team developing solutions to customers that focus on big data and analytical solutions, statistical modeling, forecast, CRM, data mining and text analytics.

Ricardo is also visiting lecturer at the Universidade Europeia (Portugal) and also at University Institute of Management – FIA (Brazil), in Postgraduate courses teaching the subjects Statistics, Data Mining, Machine Learning and Text Analytics in Postgraduate courses.

SAS analytics

40+ years of analytics innovation – SAS is a trusted analytics powerhouse for organizations seeking immediate value from their data. A deep bench of analytics solutions and broad industry knowledge makes possible to discover insights from data and make sense of it all (identify what’s working and fix what isn’t, make more intelligent decisions, and drive relevant change).

Rafaela Nunes is IT Senior Project Manager, experienced in ERP SAP implementation and maintenance, in various business sectors. Rafaela is skilled in project coordination and management, team management, external providers coordination, internal procedures and methodology monitoring. She has a deep understanding of financial processes and also logistics/ production processes.

NOESIS and CELONIS

Celonis is a Process Mining technology solution using sophisticated Big Data algorithms. Smart algorithms reconstruct, analyse and understand the real process, allowing you to view and reconstruct business processes in real time based on the digital footprint left in IT systems.