IEEE Big Data Conference 2017: take home messages from the keynote speakers

I collected here the list of my write-ups of the first three keynote speeches of the conference:

Modeling, Modeling, Modeling: From Web to Enterprise to Crowd to Social

This is our perspective on the world: it’s all about modeling. 

So, why is it that model-driven engineering is not taking over the whole technological and social eco-system?

Let me make the case that it is.

A Comprehensive Guide Through the Italian Database Research Over the Last 25 YearsIn the occasion of the 25th edition of the Italian Symposium of Database Systems (SEBD 2017) we (Stefano Ceri and I) have been asked to write a retrospective on the last years of database and systems research from our perspective, published in a dedicated volume by Springer. After some brainstorming, we agreed that it all boils down to this: modeling, modeling, modeling.

Long time ago, in the past century, the International DB Research Community used to meet for assessing new research directions, starting the meetings with 2-minutes gong shows  to tell each one’s opinion and influencing follow-up discussion. Bruce Lindsay from IBM had just been quoted for his message:

There are 3 important things in data management: performance, performance, performance.

Stefano Ceri had a chance to speak out immediately after and to give a syntactically similar but semantically orthogonal message:

There are 3 important things in data management: modeling, modeling, modeling.

Data management is continuously evolving for serving the needs of an increasingly connected society. New challenges apply not only to systems and technology, but also to the models and abstractions for capturing new application requirements.

In our retrospective paper, we describe several models and abstractions which have been progressively designed to capture new forms of data-centered interactions in the last twenty five years – a period of huge changes due to the spreading of web-based applications and the increasingly relevant role of social interactions.

We initially focus on Web-based applications for individuals, then discuss applications among enterprises, and this is all about WebML and IFML; then we discuss how these applications may include rankings which are computed using services or using crowds, and this is related to our work on crowdsourcing (liquid query and crowdsearcher tool); we conclude with hints to a recent research discussing how social sources can be used for capturing emerging knowledge (the social knowledge extractor perspective and tooling).

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All in all, modeling as a cognitive tool is all around us, and is growing in terms of potential impact thanks to formal cognification.

It’s also true that model-driven engineering is not necessarily the tool of choice for this to happen. Why? As technician, we always tend to blame the customer for not understanding our product. But maybe we should look into ourselves and the kind of tools (conceptual and technical) the MDE community is offering. I’m pretty sure we could find plenty of space for improvement.

Any idea on how to do this?

 

Keynote from Google Research on Building Knowlege Bases at #ICWE2016

I report here some highlights of the keynote speech by Xin Luna Dong at the 16th International Conference on Web Engineering (ICWE 2016). Incidentally, she is now moving to Amazon for starting a new project on building an Amazon knowledge base.
Building knowledge bases still remains a challenging task.
First, one has to decide how to build the knowledge: automatically or manually?
A survey in 2014 reported the following list of large efforts in knowledge building: the top 4 approaches are manually curated, the bottom 3 are automatic.
Google’s knowledge vault and knowledge Graph are the big winners in terms of volume.
When you move to long tail content, curation does not scale. Automation must be viable and precise.
This is in line with our own research line we are starting on Extracting Changing Knowledge (we presented a short paper at a Web Science 2016 workshop last month). Here is a summary of our approach:
Where knowledge can be extracted from? In Knowledge Valut:
  • largest share of the content comes from DOM structured documents
  • then textual content
  • then annotated content
  • and a small share from web tables

Knowledge Vault is a matrix based approach to knowledge building, with rows = entities and columns= attributes.

It assumes the entities to be available (e.g. in Freebase), and builds a training over that.
One can build KBs by building buckets of triples, with similar probability of being correct. It’s important to precisely estimate correctness probability.
Errors can include mistakes on:
  • triple identification
  • entity linkage
  • predicate linkage
  • source data

Besides general purpose KBs, Google built lightweight vertical knowledge bases (more than 100 available now).

When extracting knowledge, the ingredients are: datasource, extractor approach, the data items themselves, facts and their probability of truth.

Several models can be used for extracting knowledge. Two extremes of the spectrum are:

  1. Single-truth model. Every fact has only one truth. We trust the value of the highest number of datasources.
  2. Multilaeyer model. separates source quality from extractor quality and data errors from extraction errors. One can build a knowledge-based trust model, defining trustworthiness of web pages. One can compare this measure with respect to page rank of web pages:

In general, the challenge is to move from individual information and data points, to integrated and connected knowledge. Building the right edges is really hard though.
Overall, a lot of ingredients influence the correctness of knowledge: temporal aspects, data source correctness, capability of extraction and validation, and so on–

In summary: Plenty of research challenges to be addressed, both by the datascience and modeling communities!

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Modeling and data science for citizens: multicultural diversity and environmental monitoring at ICWSM

This year we decided to be present at ICWSM 2016 in Cologne, with two contributions that basically blend model driven software engineering and big data analysis, to provide value to users and citizens both in terms of high quality software and added value information provision.

We joined with two papers, respectively:
Model Driven Development of Social Media Environmental Monitoring Applications presented at the SWEEM (Workshop on the Social Web for Environmental and Ecological Monitoring) workshop.

Slides here:

and:

Studying Multicultural Diversity of Cities and Neighborhoods through Social Media Language Detection, presented at the CityLab workshop at ICWSM 2016. The focus of this work is to study cities as melting pots of people with different culture, religion, and language. Through multilingual analysis of Twitter contents shared within a city, we analyze the prevalent language in the different neighborhoods of the city and we compare the results with census data, in order to highlight any parallelisms or discrepancies between the two data sources. We show that the officially identified neighborhoods are actually representing significantly different communities and that the use of the social media as a data source helps to detect those weak signals that are not captured from traditional data. Slides here:

We now continuously look for new dataset and computational challenges. Feel free to ask or to propose ideas!

To keep updated on my activities you can subscribe to the RSS feed of my blog or follow my twitter account (@MarcoBrambi).

How Mature is of Model-driven Engineering as an Engineering Discipline? – Panel with Manfred Broy, Paola Inverardi and Lionel Briand

Within ModelsWard 2016, just after the opening speech I gave on February 19 in Rome, the opening panel has been about the current maturity of model-driven engineering. I also hosted a poll on twitter on this matter (results are available in this other post).  

I’m happy the panelists raised several issues I pointed out myself in the introduction to the conference: as software modelling scientists, we are facing big challenges nowadays, as the focus of modelling is shifting, due to the fact that now software is more and more pervasive, in fields like IoT, social network and social media, personal and wearable devices, and so on.

Panel included the keynote speakers of the conference: Manfred Broy, Paola Inverardi and Lionel Briand, three well known names in the Software Engineering and Modeling community.

Manfred Broy highlighted:

  • there is a different between scientific maturity and practical maturity. Sometimes, the latter in companies is far beyond the former.
  • a truck company in Germany has been practicing modelling for years, and now has this take on the world: whatever is not in the models, doesn’t exist
  • The current challenges are about how to model cyber-physical systems
  • The flow of model must be clarified: traceability, refinement, model integration are crucial. You must grant syntactic and semantic coherence
  • You also need a coherent infrastructure of tools and artefacts, that grants logic integration. You cannot obtain coherence of models without coherence of tools.
  • You need a lot of automation, otherwise you won’t get practical maturity. This doesn’t mean to have end-to-end, or round-trip complete model transformations, but you need to push automaton as much as possible

Lionel Briand clarified that:

  • by definition, engineering underpins deep mathematical background as a foundation and implies application of the scientific method to solving problems
  • maturity can be evaluated in terms of: how much math underpinning is foundational, how many standards and tools exist and are used, whether the scientific approach is used
  •  Tools, methods, engineers, and scale of MDE are increasing (aka. MDE is increasingly more difficult to avoid)
Paola Inverardi recalled a position by Jean Bezivin:
  • we need to split Domain Engineering (where the problem is) and Support Engineering (where the solution will be)
  • MDE is the application of modelling principles and tools to any engineering field
  • So: is actually SOFTWARE the main field of interest of model-driven engineering?
  • In the modern interpretation of life, covering from smart cities to embedded, wearable, and cyber-physical systems, is the border between the environment and the system still relevant?
  • In the future we will need to rely less and less on the “creativity” of engineers when building models, and more and more on the scientific/ quantitative/ empirical methods for building models

The debate obviously stirred around this aspects, starting from Bran Selic who asked a very simple question:

Isn’t it the case that the real problem is about the word “modeling”? In any other fields (architecture, mechanics, physics) modelling is implicit and obvious. Why not in our community? At the end, what we want to achieve is to raise abstraction and increase automation, nothing else.

Other issues have been raised too:

  • why is there so much difference in attitude towards modelling between Europe and US?
  • what’s the role of notations and standards in the success / failure of MDE?

What’s your take on this issue?
Feel free to share your thoughts here or on Twitter, mentioning me  (@MarcoBrambi).
AND:
Respond to my poll on twitter!

To keep updated on my activities you can subscribe to the RSS feed of my blog or follow my twitter account (@MarcoBrambi).

ECMFA: 12th European Conference on Modelling Foundations and Applications

This year I’m involved in the program committee of the Foundations track of ECMFA.
ECMFA 2016 is the 12th European Conference on Modelling Foundations and Applications and is co-located with STAF 2016, on 4-8 July, 2016, in Vienna, Austria. Here are some core excerpts from the call for papers, which could be of interest for software modelling practitioners.

The ECMFA conference series is dedicated to advancing the state of knowledge and fostering the industrial application of Model-Based Engineering (MBE, an approach to the design, analysis and development of software and systems based on high-level models and computer-based automation). Its focus is on engaging the key figures of research and industry in a dialog which will result in stronger and more effective practical application of MBE, hence producing more reliable software based on state-of-the-art research results.

The official conference web site is available at: http://ecmfa2016.itu.dk/

ECMFA 2016 will be co-located with ICMT, TAP, SEFM, ICGT and TTC as part of
the STAF federation of conferences, leading conferences on software
technologies (http://stafconferences.info). The joint organization of
these prominent conferences provides a unique opportunity to gather
practitioners and researchers interested in all aspects of software
technology, and allow them to interact with each other.

ECMFA has two distinct Paper Tracks: one for research papers (Track F)
dealing with the foundations for MBE, and one for industrial/applications
papers (Track A) dealing with the applications of MBE, including experience
reports on MBE tools.

Research Papers (Track F)
In this track, we are soliciting papers presenting original research on all
aspects of MBE. Typical topics of interest include, among others:

  • Foundations of (Meta)modelling
  • Domain Specific Modelling Languages and Language Workbenches
  • Model Reasoning, Testing and Validation
  • Model Transformation, Code Generation and Reverse Engineering
  • Model Execution and Simulation
  • Model Management aspects such as (Co-)Evolution, Consistency, Synchronization
  • Model-Based Engineering Environments and Tool Chains
  • Foundations of Requirements Modelling, Architecture Modelling, Platform Modelling
  • Foundations of Quality Aspects and Modelling non-functional System Properties
  • Scalability of MBE techniques
  • Collaborative Modeling

Industrial Papers (Track A)
In this track, we are soliciting papers representing views, innovations and
experiences of industrial players in applying or supporting MBE. In
particular, we are looking for papers that set requirements on the
foundations, methods, and tools for MBE. We are also seeking experience
reports or case studies on the application, successes or current
shortcomings of MBE. Quantitative results reflecting industrial experience
are particularly appreciated. All application areas of MBE are welcomed
including but not limited to any of the following:

  • MBE for Large and Complex Industrial Systems
  • MBE for Safety-Critical Systems
  • MBE for Cyber-Physical Systems
  • MBE for Software and Business Process Modelling
  • MBE Applications in Transportation, Health Care, Cloud & Mobile computing, etc. …
  • Model-Based Integration and Simulation
  • Model-Based System Analysis
  • Application of Modeling Standards
  • Comparative Studies of MBE Methods and Tools
  • Metrics for MBE Development
  • MBE Training

Research papers should be up to 16 pages long; Industrial
papers should be 12 pages long (full papers), or 2 pages long (short
papers). Short papers will be given shorter presentation slots.
The authors of selected best papers from the foundations track will be
invited to submit extended version to a special issue of the SoSyM journal
(with another review process).

Important dates for authors:

Abstract submission deadline: February 15, 2016 AoE
Papers submission deadline: March 1, 2016 AoE
Notification to authors: April 7, 2016
Camera ready versions due: April 28, 2016

The complete call for papers is available here in text and here as pdf.

To keep updated on my activities you can subscribe to the RSS feed of my blog or follow my twitter account (@MarcoBrambi).

Keynote speech on User Interaction Modeling at Modelsward 2015 in Angers

On February 10, 2015 I gave a keynote at Modelsward in Angers, France.

The speech focuses on the modeling of software UIs through graphical domain-specific languages and in particular shows the new standard adopted by OMG called IFML (Interaction Flow Modeling Language) at work. My presentation illustrates the basic concepts of IFML, presents the design best practices and integration with other modelling languages, and discusses some large-scale industrial experiences (also featuring quantitative measures of productivity) achieved through IFML and associated full code generation techniques.

The full video of my presentation (1 hour long, if you can endure it!) is available on Vimeo thanks to the Insticc service. See it here too:

WebRatio BPM – preview and presentation at Eclipse-IT 2009, Bergamo, Italy

On September 28th, 2009 in Bergamo we will present the following demosntration and paper:

Title: Demonstration of WebRatio BPM, an innovative BP modeling tool for the Web
Authors: Marco Brambilla, Stefano Butti, Piero Fraternali
Affiliation: Web Models Srl, Como, Italy

WebRatio BPM is an innovative Eclipse-based tool that supports the design and deployment of business processes on the Web. The commercial version of the tool will be released in late fall 2009 by Web Models Srl (www.webratio.com).

The tool applies Model Driven Engineering techniques to complex, multi-actor business processes, mixing tasks executed by humans and by machines. It adopts the standard BPMN 1.2 notation, extended with information on task assignment and escalation policies, activity semantics, and typed dataflows

We will present our two-step generative approach: first the BPMN Process Model is automatically transformed into a WebML Web Application Model; second, the Application Model is fed to an automatic code generation transformation that produces state of the practice J2EE web applications. We will demonstrate the tool features that increase the productivity and the quality of the resulting application, including: one-click generation of a running prototype of the process from the BPMN model; fine-grained refinement of the resulting application at the WebML modeling level; and support of continuous evolution of the application design after requirements changes.