Presentation given at the SIB training: Using the Semantic Web for faster (Bio-)Research
http://edu.isb-sib.ch/course/view.php?id=212
(http://sgtp.net/AndreaSplendiani)
Metrics Worth Measuring: Align Business Goals to Salesforce AdoptionSalesforce Admins
Adoption can mean different things to different people. Aligning on the right measures is critical to success and will drive not only acceptance of Salesforce but the achievement of key business goals. By ensuring that adoption is defined by key business metrics, Admins become the keystone to a successful software rollout and a bridge to greater success for the company.
Slide deck from BrightGen's Spring '23 Salesforce release webinar. Presented by Keir Bowden, CTO, and covering the key new features that are of interest to our clients. You can find the recording on our youtube channel at : https://www.youtube.com/watch?v=ONjv5BvXccY
Please use the below URL to view recording of this webinar:
http://wso2.com/library/webinars/2015/02/connected-retail-reference-architecture/
The key focus areas of this session are
An overview of the retail IT landscape
What is a connected retail IT architecture
How the WSO2 middleware platform enables a connected retail business
Connected retail L0 architecture
Connected retail L1 architecture with WSO2
We’re all busy—and it’s a common theme in most professional workplaces—with people trying to get more done with finite time and resources. For a lot of firms today, a major challenge is making sure we’re spending our precious time making the most of every business opportunity by maximizing client relationships. Marketing & BD teams need to know if they’re focusing on the opportunities, RFI’s and RFP’s with the best potential; that they are managing their firm pipeline effectively; and they are giving everyone on the team the best tools for the job—wherever they are.
That’s why firms today are focused on creating great client relationships – they need to try to reduce complexity and make it easier to maximize opportunities, provide excellent client experiences, and grow the firm.
Why should a legal or accounting firm care? Because client experience and knowledge is increasingly important for firms of all sizes – across all client interactions.
Client experience…
…is what differentiates your firm
…is how you win and keep clients for the long-term
…is how you grow your firm …and in a world where clients are mobile and social, your reputation (& brand) is more important than ever.
Today you don’t have as many contact points as you used to have, and you have to make every one count. To thrive in this ultra-competitive environment firms of all sizes have to make client experience a priority. That is why you need Dynamics 365 and xRM! Visit our websites www.xRM4Legal.com, www.xRM4Accounting.com and www.xRM4Finance.com or email Dynamics@xRM.email
Metrics Worth Measuring: Align Business Goals to Salesforce AdoptionSalesforce Admins
Adoption can mean different things to different people. Aligning on the right measures is critical to success and will drive not only acceptance of Salesforce but the achievement of key business goals. By ensuring that adoption is defined by key business metrics, Admins become the keystone to a successful software rollout and a bridge to greater success for the company.
Slide deck from BrightGen's Spring '23 Salesforce release webinar. Presented by Keir Bowden, CTO, and covering the key new features that are of interest to our clients. You can find the recording on our youtube channel at : https://www.youtube.com/watch?v=ONjv5BvXccY
Please use the below URL to view recording of this webinar:
http://wso2.com/library/webinars/2015/02/connected-retail-reference-architecture/
The key focus areas of this session are
An overview of the retail IT landscape
What is a connected retail IT architecture
How the WSO2 middleware platform enables a connected retail business
Connected retail L0 architecture
Connected retail L1 architecture with WSO2
We’re all busy—and it’s a common theme in most professional workplaces—with people trying to get more done with finite time and resources. For a lot of firms today, a major challenge is making sure we’re spending our precious time making the most of every business opportunity by maximizing client relationships. Marketing & BD teams need to know if they’re focusing on the opportunities, RFI’s and RFP’s with the best potential; that they are managing their firm pipeline effectively; and they are giving everyone on the team the best tools for the job—wherever they are.
That’s why firms today are focused on creating great client relationships – they need to try to reduce complexity and make it easier to maximize opportunities, provide excellent client experiences, and grow the firm.
Why should a legal or accounting firm care? Because client experience and knowledge is increasingly important for firms of all sizes – across all client interactions.
Client experience…
…is what differentiates your firm
…is how you win and keep clients for the long-term
…is how you grow your firm …and in a world where clients are mobile and social, your reputation (& brand) is more important than ever.
Today you don’t have as many contact points as you used to have, and you have to make every one count. To thrive in this ultra-competitive environment firms of all sizes have to make client experience a priority. That is why you need Dynamics 365 and xRM! Visit our websites www.xRM4Legal.com, www.xRM4Accounting.com and www.xRM4Finance.com or email Dynamics@xRM.email
== Blockchain and Angular (by Michael John Pena)
Blockchain has been a big buzz in the technology world lately. But why should it matter to web developers? In this session, MJ will walk you through on what is a Blockchain, Ethereum and Smart Contracts. This will then be followed on how you can interface your Angular web app to Ethereum with the use of Web3.js.
Presented on NG-Sydney
Spark Summit EU 2015: Matei Zaharia keynoteDatabricks
2015 was a year of continued growth for Spark, with numerous additions to the core project and very fast growth of use cases across the industry. In this talk, I’ll look back at how the Spark community is has grown and changed in 2015, based on a large Apache Spark user survey conducted by Databricks. We see some interesting trends in the diversity of runtime environments (which are increasingly not just Hadoop); the types of applications run on Spark; and the types of users, now that features like R support and DataFrames are available in Spark. I’ll also cover the ongoing work in the upcoming releases of Spark to support new use cases.
Apache Kafka for Real-time Supply Chainin the Food and Retail IndustryKai Wähner
Use Cases, Architectures, and Real-World Examples for data in motion and real-time event streaming powered by Apache Kafka across the supply chain and logistics. Case studies and deployments include Baader, Walmart, Migros, Albertsons, Domino's Pizza, Instacart, Grab, Royal Caribbean, and more.
Salesforce Tableau CRM AKA Einstein Analytics helps customers to get predictive analysis of their data, scattered over multiple systems at one platform
How to Design Retail Recommendation Engines with Neo4jNeo4j
Recommendations are at the core of digital transformation in retail today. Whether you’re building features such as product recommendations, promotion recommendations, personalized customer experience, or re-imagining your supply chain to meet customer demands for same day delivery — you’re facing challenges that require the ability to leverage connections from many different data sources, in real-time. There’s no better technology to meet these challenges than a native graphDB technology such as Neo4j.
Watch full webinar here: https://bit.ly/3mdj9i7
You will often hear that "data is the new gold"? In this context, data management is one of the areas that has received more attention from the software community in recent years. From Artificial Intelligence and Machine Learning to new ways to store and process data, the landscape for data management is in constant evolution. From the privileged perspective of an enterprise middleware platform, we at Denodo have the advantage of seeing many of these changes happen.
In this webinar, we will discuss the technology trends that will drive the enterprise data strategies in the years to come. Don't miss it if you want to keep yourself informed about how to convert your data to strategic assets in order to complete the data-driven transformation in your company.
Watch this on-demand webinar as we cover:
- The most interesting trends in data management
- How to build a data fabric architecture?
- How to manage your data integration strategy in the new hybrid world
- Our predictions on how those trends will change the data management world
- How can companies monetize the data through data-as-a-service infrastructure?
- What is the role of voice computing in future data analytic
Salesforce was founded with a vision to redefine the Cloud CRM model. It sowed the seeds for a new era of cloud computing and brought in revolutionary changes to the concept of Customer Relationship Management. The USP of Salesforce is its presence across-the-board. It competes with Oracle, SAP, and Microsoft in the top-market. While these three competitors match Salesforce’s features, Salesforce offers far superior and flexible solutions with value for your money.
To get in touch, write to us at: jghosh@suyati.com
In this 30-minute webinar, Microsoft Data Platform MVP Kendra Little explores the key challenges and recommendations to prevent exposure of private data in your next data breach, featuring insight from Gartner’s 2018 Market Guide for Data Masking.
apidays Paris 2022 - Generating APIs from business models, Frederic Fontanet,...apidays
apidays Paris 2022 - APIs the next 10 years: Software, Society, Sovereignty, Sustainability
December 14, 15 & 16, 2022
Generating APIs from business models: high productivity and consistency
Frederic Fontanet, Architect / API designer at UMLTech
------
Check out our conferences at https://www.apidays.global/
Do you want to sponsor or talk at one of our conferences?
https://apidays.typeform.com/to/ILJeAaV8
Learn more on APIscene, the global media made by the community for the community:
https://www.apiscene.io
Explore the API ecosystem with the API Landscape:
https://apilandscape.apiscene.io/
Deep dive into the API industry with our reports:
https://www.apidays.global/industry-reports/
Subscribe to our global newsletter:
https://apidays.typeform.com/to/i1MPEW
== Blockchain and Angular (by Michael John Pena)
Blockchain has been a big buzz in the technology world lately. But why should it matter to web developers? In this session, MJ will walk you through on what is a Blockchain, Ethereum and Smart Contracts. This will then be followed on how you can interface your Angular web app to Ethereum with the use of Web3.js.
Presented on NG-Sydney
Spark Summit EU 2015: Matei Zaharia keynoteDatabricks
2015 was a year of continued growth for Spark, with numerous additions to the core project and very fast growth of use cases across the industry. In this talk, I’ll look back at how the Spark community is has grown and changed in 2015, based on a large Apache Spark user survey conducted by Databricks. We see some interesting trends in the diversity of runtime environments (which are increasingly not just Hadoop); the types of applications run on Spark; and the types of users, now that features like R support and DataFrames are available in Spark. I’ll also cover the ongoing work in the upcoming releases of Spark to support new use cases.
Apache Kafka for Real-time Supply Chainin the Food and Retail IndustryKai Wähner
Use Cases, Architectures, and Real-World Examples for data in motion and real-time event streaming powered by Apache Kafka across the supply chain and logistics. Case studies and deployments include Baader, Walmart, Migros, Albertsons, Domino's Pizza, Instacart, Grab, Royal Caribbean, and more.
Salesforce Tableau CRM AKA Einstein Analytics helps customers to get predictive analysis of their data, scattered over multiple systems at one platform
How to Design Retail Recommendation Engines with Neo4jNeo4j
Recommendations are at the core of digital transformation in retail today. Whether you’re building features such as product recommendations, promotion recommendations, personalized customer experience, or re-imagining your supply chain to meet customer demands for same day delivery — you’re facing challenges that require the ability to leverage connections from many different data sources, in real-time. There’s no better technology to meet these challenges than a native graphDB technology such as Neo4j.
Watch full webinar here: https://bit.ly/3mdj9i7
You will often hear that "data is the new gold"? In this context, data management is one of the areas that has received more attention from the software community in recent years. From Artificial Intelligence and Machine Learning to new ways to store and process data, the landscape for data management is in constant evolution. From the privileged perspective of an enterprise middleware platform, we at Denodo have the advantage of seeing many of these changes happen.
In this webinar, we will discuss the technology trends that will drive the enterprise data strategies in the years to come. Don't miss it if you want to keep yourself informed about how to convert your data to strategic assets in order to complete the data-driven transformation in your company.
Watch this on-demand webinar as we cover:
- The most interesting trends in data management
- How to build a data fabric architecture?
- How to manage your data integration strategy in the new hybrid world
- Our predictions on how those trends will change the data management world
- How can companies monetize the data through data-as-a-service infrastructure?
- What is the role of voice computing in future data analytic
Salesforce was founded with a vision to redefine the Cloud CRM model. It sowed the seeds for a new era of cloud computing and brought in revolutionary changes to the concept of Customer Relationship Management. The USP of Salesforce is its presence across-the-board. It competes with Oracle, SAP, and Microsoft in the top-market. While these three competitors match Salesforce’s features, Salesforce offers far superior and flexible solutions with value for your money.
To get in touch, write to us at: jghosh@suyati.com
In this 30-minute webinar, Microsoft Data Platform MVP Kendra Little explores the key challenges and recommendations to prevent exposure of private data in your next data breach, featuring insight from Gartner’s 2018 Market Guide for Data Masking.
apidays Paris 2022 - Generating APIs from business models, Frederic Fontanet,...apidays
apidays Paris 2022 - APIs the next 10 years: Software, Society, Sovereignty, Sustainability
December 14, 15 & 16, 2022
Generating APIs from business models: high productivity and consistency
Frederic Fontanet, Architect / API designer at UMLTech
------
Check out our conferences at https://www.apidays.global/
Do you want to sponsor or talk at one of our conferences?
https://apidays.typeform.com/to/ILJeAaV8
Learn more on APIscene, the global media made by the community for the community:
https://www.apiscene.io
Explore the API ecosystem with the API Landscape:
https://apilandscape.apiscene.io/
Deep dive into the API industry with our reports:
https://www.apidays.global/industry-reports/
Subscribe to our global newsletter:
https://apidays.typeform.com/to/i1MPEW
Text Analytics & Linked Data Management As-a-ServiceMarin Dimitrov
slides from the talk on "Text Analytics & Linked Data Management As-a-Service with S4" from the ESWC'2015 workshop on Semantic Web Enterprise Adoption & Best Practices
full paper available at http://2015.wasabi-ws.org/papers/wasabi15_1.pdf
An evaluation of SimRank and Personalized PageRank to build a recommender sys...Paolo Tomeo
The Web of Data is the natural evolution of the World Wide Web from a set of interlinked documents to a set of interlinked entities. It is a graph of information resources interconnected by semantic relations, thereby yielding the name Linked Data. The proliferation of Linked Data is for sure an opportunity to create a new family of data-intensive applications such as recommender systems. In particular, since content-based recommender systems base on the notion of similarity between items, the selection of the right graph-based similarity metric is of paramount importance to build an effective recommendation engine. In this paper, we review two existing metrics, SimRank and PageRank, and investigate their suitability and performance for computing similarity between resources in RDF graphs and investigate their usage to feed a content-based recommender system. Finally, we conduct experimental evaluations on a dataset for musical artists and bands recommendations thus comparing our results with two other content-based baselines
measuring their performance with precision and recall, catalog coverage, items distribution and novelty metrics.
20141030 LinDa Workshop echallenges2014 - Linked Data AnalyticsLinDa_FP7
LinDA Workshop eChallenges2014 - Business Value Creation from Linked Data Analytics: The LinDA Approach by Anastasios Zafeiropoulos and Eleni Fotopoulou
20140902 LinDa Workshop Semantincs2014 - LinDA Project OverviewLinDa_FP7
LinDa Project presentation - Challenges, tools, workplan and objectives
Presentation at LinDA Workshop on 2nd September 2014 at Semantics2014 by Spiros Mouzakitis
Slides from my talk on Personalised Access to Linked Data. Presented at the EKAW 2014 conference. The poster to this paper won the best poster award at the conference!
Smarter search drives value to your business. Delivering search that matches users to the right content is what you care about. But organizations often get stuck getting there. It turns out that you need quite a number of very different ingredients to deliver tremendous search. It can make your head spin! To help you think through where your team is on its road to smarter search, Pugh introduces the maturity model used by OpenSource Connections and walks you through a very concrete method to inventory needed skills and translate that into search roles for your team. He shows how to measure your capabilities in key areas of search to drive better ROI from search.
Triplestores and inference, applications in Finance, text-mining. Projects and solutions for financial media and publishers.
Keystone Industrial Panel, ISWC 2014, Riva del Garda, 18 Oct 2014.
Thanks to Atanas Kiryakov for this presentation, I just cut it to size.
The presentation aims to emphasize the need for more applications and prototypes in the area of the Semantic Web that will showcase the various research findings and technologies.
This presentation gives a brief overview on achievements and challenges of the Data Web and describes different aspects of using the Semantic Data Wiki OntoWiki for Linked Data management.
On-Demand RDF Graph Databases in the CloudMarin Dimitrov
slides from the S4 webinar "On-Demand RDF Graph Databases in the Cloud"
RDF database-as-a-service running on the Self-Service Semantic Suite (S4) platform: http://s4.ontotext.com
video recording of the talk is available at http://info.ontotext.com/on-demand-rdf-graph-database
A (vintage) presentation about a database system for the study of gene expression data. Including distributed metadata annotation and some interactive analytics. Some ideas are still actual today.
A set of ideas on the use of artificial intelligence for data curation that has been presented at the Pharma-IT conference (London, 2017), in the artificial intelligence track.
It begins with some broad discussion about semantic web, knowledge representation, machine learning and artificial intelligence. It the focus on how a "data curation" problem can be framed and hints at some possible examples.
Professional air quality monitoring systems provide immediate, on-site data for analysis, compliance, and decision-making.
Monitor common gases, weather parameters, particulates.
DERIVATION OF MODIFIED BERNOULLI EQUATION WITH VISCOUS EFFECTS AND TERMINAL V...Wasswaderrick3
In this book, we use conservation of energy techniques on a fluid element to derive the Modified Bernoulli equation of flow with viscous or friction effects. We derive the general equation of flow/ velocity and then from this we derive the Pouiselle flow equation, the transition flow equation and the turbulent flow equation. In the situations where there are no viscous effects , the equation reduces to the Bernoulli equation. From experimental results, we are able to include other terms in the Bernoulli equation. We also look at cases where pressure gradients exist. We use the Modified Bernoulli equation to derive equations of flow rate for pipes of different cross sectional areas connected together. We also extend our techniques of energy conservation to a sphere falling in a viscous medium under the effect of gravity. We demonstrate Stokes equation of terminal velocity and turbulent flow equation. We look at a way of calculating the time taken for a body to fall in a viscous medium. We also look at the general equation of terminal velocity.
Comparing Evolved Extractive Text Summary Scores of Bidirectional Encoder Rep...University of Maribor
Slides from:
11th International Conference on Electrical, Electronics and Computer Engineering (IcETRAN), Niš, 3-6 June 2024
Track: Artificial Intelligence
https://www.etran.rs/2024/en/home-english/
THE IMPORTANCE OF MARTIAN ATMOSPHERE SAMPLE RETURN.Sérgio Sacani
The return of a sample of near-surface atmosphere from Mars would facilitate answers to several first-order science questions surrounding the formation and evolution of the planet. One of the important aspects of terrestrial planet formation in general is the role that primary atmospheres played in influencing the chemistry and structure of the planets and their antecedents. Studies of the martian atmosphere can be used to investigate the role of a primary atmosphere in its history. Atmosphere samples would also inform our understanding of the near-surface chemistry of the planet, and ultimately the prospects for life. High-precision isotopic analyses of constituent gases are needed to address these questions, requiring that the analyses are made on returned samples rather than in situ.
Seminar of U.V. Spectroscopy by SAMIR PANDASAMIR PANDA
Spectroscopy is a branch of science dealing the study of interaction of electromagnetic radiation with matter.
Ultraviolet-visible spectroscopy refers to absorption spectroscopy or reflect spectroscopy in the UV-VIS spectral region.
Ultraviolet-visible spectroscopy is an analytical method that can measure the amount of light received by the analyte.
2. Semantic Web @Novartis
2
Topics
§ Semantic Web @Novartis
• Context (Where in Novartis)
• Semantic Web in production
• Semantic Web in research
• Semantic Web under the hood
§ Semantic Web in “Real Life”: open questions
| Semantic Web technologies: experiences in Novartis| Andrea Splendiani | 2nd December 2015| Technology | Public use
3. Semantic Web uptake in time
| Semantic Web technologies: experiences in Novartis| Andrea Splendiani | 2nd December 2015| Technology | Public use3
Context
Metastore/RDF
prep. production
“Semantic Web in pubmed”
preparation
prep
Query federation
Visualisation
Other semantic technologies
CTMF p. p.
4. Semantic Web usage within the organization
4
Context
Activities of TMS:
§ Text mining
§ Ontology development
§ Ontology provision
§ Data curation
| Semantic Web technologies: experiences in Novartis| Andrea Splendiani | 2nd December 2015| Technology | Public use
5. Semantic Web @Novartis
5
Topics
§ Semantic Web @Novartis
• Context (Where in Novartis)
• Semantic Web in production
• Semantic Web in research
• Semantic Web under the hood
§ Semantic Web in “Real Life”: open questions
| Semantic Web technologies: experiences in Novartis| Andrea Splendiani | 2nd December 2015| Technology | Public use
6. Metastore: a central repository for ontologies
6
Semantic Web in production: Metastore
§ Consists of a semantic data federation layer based on controlled terminologies
extracted from scientific data repositories
§ Organized around scientific concepts: Genes, Proteins, Indications, Anatomy etc…;
some hierarchically organized and classified
§ Complemented by referential knowledge (cross references to internal and external
knowledge repositories)
§ Supports different use cases, including text mining, data curation, data integration,
search
§ Accessible through SPARQL endpoint, dedicated service layer and reusable
widgets; full integrated application (MS Viewer) released to visualize all Metastore
content.
§ Based on an RDF data model
| Semantic Web technologies: experiences in Novartis| Andrea Splendiani | 2nd December 2015| Technology | Public use
7. Metastore: content and usage
7
Semantic Web in production: Metastore
Approximately >2M accesses per month
March 2013
| Semantic Web technologies: experiences in Novartis| Andrea Splendiani | 2nd December 2015| Technology | Public use
8. Metastore data model
8
Semantic Web in production: Metastore
| Semantic Web technologies: experiences in Novartis| Andrea Splendiani | 2nd December 2015| Technology | Public use
9. Metastore technology I
9
Semantic Web in production: Metastore
| Semantic Web technologies: experiences in Novartis| Andrea Splendiani | 2nd December 2015| Technology | Public use
10. Metastore technology II
10
Semantic Web in production: Metastore
| Semantic Web technologies: experiences in Novartis| Andrea Splendiani | 2nd December 2015| Technology | Public use
Staging
Table
T_STABLE
RDF Triple
store
Materialized
Views
SPARQL end
Point Joseki
Relational
Tables
• Pointers
• History
• Versions
• Logs
• Reference
tables
Jena
Query SQL and
PL/SQL APIs
D
A
T
A
-
S
e
r
v
i
c
e
s
RDF/XML
files
11. Metastore Widgets (suggest example)
11
Semantic Web in production: Metastore
| Semantic Web technologies: experiences in Novartis| Andrea Splendiani | 2nd December 2015| Technology | Public use
12. Metastore applications (Metastore viewer: summary)
12
Semantic Web in production: Metastore
| Semantic Web technologies: experiences in Novartis| Andrea Splendiani | 2nd December 2015| Technology | Public use
13. Metastore applications (Metastore viewer: links)
13
Semantic Web in production: Metastore
| Semantic Web technologies: experiences in Novartis| Andrea Splendiani | 2nd December 2015| Technology | Public use
14. Metastore applications (Metastore viewer: explorer)
14
Semantic Web in production: Metastore
| Semantic Web technologies: experiences in Novartis| Andrea Splendiani | 2nd December 2015| Technology | Public use
15. Semantic Web @Novartis
15
Topics
§ Semantic Web @Novartis
• Context (Where in Novartis)
• Semantic Web in production
• Semantic Web in research
- Query federation
- Visualization/interaction
- Other projects
• Semantic Web under the hood
§ Semantic Web in “Real Life”: open questions
| Semantic Web technologies: experiences in Novartis| Andrea Splendiani | 2nd December 2015| Technology | Public use
16. Query federation: why and how
16
Semantic Web in Research: query federation
• Internal and external
data already in RDF
• Large datasets in
relational systems
• Proprietary datasets
with license restrictions
(e.g.: one server only)
• Relational 2 RDF
mapping (materialised
and virtualised)
• Bridge ontologies (work
in progress)
• Distributed queries
(service)
Why ? How ?
| Semantic Web technologies: experiences in Novartis| Andrea Splendiani | 2nd December 2015| Technology | Public use
17. Data and systems architecture: example
17
Semantic Web in Research: query federation
Different arrangements possible (with caveats)
Export!
triplest !
SERVICE!
Dynamic translation!
Persist
triples!
Ontop!
SPARQL
End Point!
NIBR!
Data
Warehouse!
!
Ontop!
API!
Assay
Repository!
RDBMS!
Allegrograph!
!
Triplestore &
End point!
UNIPROT/EBI
SPARQL End
Point!
METASTORE!
Oracle Spatial &
graphs!
R2RML!
+ reasoning!
Metastore!
| Semantic Web technologies: experiences in Novartis| Andrea Splendiani | 2nd December 2015| Technology | Public use
18. Federated query example
18
Semantic Web in Research: query federation
Assays
UNIPROT
Metastore
| Semantic Web technologies: experiences in Novartis| Andrea Splendiani | 2nd December 2015| Technology | Public use
19. Federated queries: logical model
19
Semantic Web in Research: query federation
| Semantic Web technologies: experiences in Novartis| Andrea Splendiani | 2nd December 2015| Technology | Public use
20. RDF virtualization via OnTop
20
Semantic Web in Research: query federation
| Semantic Web technologies: experiences in Novartis| Andrea Splendiani | 2nd December 2015| Technology | Public use
21. Semantic Web @Novartis
21
Topics
§ Semantic Web @Novartis
• Context (Where in Novartis)
• Semantic Web in production
• Semantic Web in research
- Query federation
- Visualization/interaction
- Other projects
• Semantic Web under the hood
§ Semantic Web in “Real Life”: open questions
| Semantic Web technologies: experiences in Novartis| Andrea Splendiani | 2nd December 2015| Technology | Public use
22. Visualization: why and how
22
Semantic Web in research: visulization and interaction
• Accessibility of RDF
data by end users
• Complexity (or
unfamiliarity) with
SPARQL
• General lack of
knowledge on the
structure of data, at
query time
• Visual, interactive
environment
• Pre-configuration to
optimize interaction
styles
• Combination of tools
and exploration
paradigms
• Data access through
SPARQL endpoints
Why ? How ?
| Semantic Web technologies: experiences in Novartis| Andrea Splendiani | 2nd December 2015| Technology | Public use
23. RDF data explorer configuration
23
Semantic Web in research: visulization and interaction
§ Visualisation features are tuned to
the datasets via a semi-automatic
configuration.
§ Structure discovery:
• ontology
• queries
• sampling
• manual specification/overriding
§ Manual tuning of the ontology and
other interaction parameters
| Semantic Web technologies: experiences in Novartis| Andrea Splendiani | 2nd December 2015| Technology | Public use
24. Data overview
24
Semantic Web in research: visulization and interaction
| Semantic Web technologies: experiences in Novartis| Andrea Splendiani | 2nd December 2015| Technology | Public use
25. Interaction: query builder + suggest
25
Semantic Web in research: visulization and interaction
| Semantic Web technologies: experiences in Novartis| Andrea Splendiani | 2nd December 2015| Technology | Public use
26. Interaction: path suggestions
26
Semantic Web in research: visulization and interaction
Assisted query formulation
| Semantic Web technologies: experiences in Novartis| Andrea Splendiani | 2nd December 2015| Technology | Public use
27. Visulization and graph navigation
27
Semantic Web in research: visulization and interaction
Detail, Augmentation, Filtering, query re-formulation
| Semantic Web technologies: experiences in Novartis| Andrea Splendiani | 2nd December 2015| Technology | Public use
28. Exploration, layouts, graphic clues
28
Semantic Web in research: visulization and interaction
Detail, Augmentation, Filtering, query re-formulation
| Semantic Web technologies: experiences in Novartis| Andrea Splendiani | 2nd December 2015| Technology | Public use
29. Multiple exports, sharing
29
Semantic Web in research: visulization and interaction
§ “queries” can be saved and shared
as files or links
§ Query history
§ Download of partial or total datasets
| Semantic Web technologies: experiences in Novartis| Andrea Splendiani | 2nd December 2015| Technology | Public use
30. Semantic Web @Novartis
30
Topics
§ Semantic Web @Novartis
• Context (Where in Novartis)
• Semantic Web in production
• Semantic Web in research
- Query federation
- Visualization/interaction
- Other projects
• Semantic Web under the hood
§ Semantic Web in “Real Life”: open questions
| Semantic Web technologies: experiences in Novartis| Andrea Splendiani | 2nd December 2015| Technology | Public use
31. 31
Example: provision of “phenotype ontologies”
Semantic Web in Research: other projects
| Semantic Web technologies: experiences in Novartis| Andrea Splendiani | 2nd December 2015| Technology | Public use
<owl:Class rdf:about="http://purl.obolibrary.org/obo/HP_0001636">
<rdfs:label rdf:datatype="http://www.w3.org/2001/XMLSchema#string">Tetralogy of Fallot</rdfs:label>
<owl:equivalentClass>
<owl:Restriction>
<owl:onProperty rdf:resource="http://purl.obolibrary.org/obo/BFO_0000051"/>
<owl:someValuesFrom>
<owl:Class>
<owl:intersectionOf rdf:parseType="Collection">
<rdf:Description rdf:about="http://purl.obolibrary.org/obo/PATO_0000001"/>
<owl:Restriction>
<owl:onProperty rdf:resource="http://purl.obolibrary.org/obo/BFO_0000051"/>
<owl:someValuesFrom rdf:resource="http://purl.obolibrary.org/obo/HP_0001629"/>
</owl:Restriction>
<owl:Restriction>
<owl:onProperty rdf:resource="http://purl.obolibrary.org/obo/BFO_0000051"/>
<owl:someValuesFrom rdf:resource="http://purl.obolibrary.org/obo/HP_0001642"/>
</owl:Restriction>
…
What systems can understand:
HP_0001636 hasPart HP_0001629
32. 32
Example: provision of “phenotype ontologies”
Semantic Web in Research: other projects
| Semantic Web technologies: experiences in Novartis| Andrea Splendiani | 2nd December 2015| Technology | Public use
<owl:Class rdf:about="http://purl.obolibrary.org/obo/HP_0001636">
<rdfs:label rdf:datatype="http://www.w3.org/2001/XMLSchema#string">Tetralogy of Fallot</
rdfs:label>
<owl:equivalentClass>
<owl:Restriction>
<owl:onProperty rdf:resource="http://purl.obolibrary.org/obo/BFO_0000051"/>
<owl:someValuesFrom>
<owl:Class>
<owl:intersectionOf rdf:parseType="Collection">
<rdf:Description rdf:about="http://purl.obolibrary.org/obo/PATO_0000001"/>
<owl:Restriction>
<owl:onProperty rdfresource="http://purl.obolibrary.org/obo/BFO_0000051"/>
<owl:someValuesFrom rdf:resource="http://purl.obolibrary.org/obo/HP_0001629"/>
</owl:Restriction>
<owl:Restriction>
<owl:onProperty rdf:resource="http://purl.obolibrary.org/obo/BFO_0000051"/>
<owl:someValuesFrom rdf:resource="http://purl.obolibrary.org/obo/HP_0001642"/>
</owl:Restriction>
What systems can understand:
HP_0001636 hasPart HP_0001629
Imports closure
Classification
Extraction
33. Semantic Web @Novartis
33
Topics
§ Semantic Web @Novartis
• Context (Where in Novartis)
• Semantic Web in production
• Semantic Web in research
- Query federation
- Visualization/interaction
- Other projects
• Semantic Web under the hood
§ Semantic Web in “Real Life”: open questions
| Semantic Web technologies: experiences in Novartis| Andrea Splendiani | 2nd December 2015| Technology | Public use
34. CTMF: Collaborative Terminology Management
34
Semantic web under the hood: CTMF
§ The CTMF is a system designed to allow a distributed
“editing of ontologies”.
§ Users can request new “terms” via a web interface or
within an application.
§ “Content owners” can “assess” whether the requested
terms are new concepts or synonyms (or errors!) and
update the ontologies.
§ Resolution is asynchronous and the term request is non-
blocking for applications
| Semantic Web technologies: experiences in Novartis| Andrea Splendiani | 2nd December 2015| Technology | Public use
35. CTMF web application (new request form)
35
Semantic web under the hood: CTMF
| Semantic Web technologies: experiences in Novartis| Andrea Splendiani | 2nd December 2015| Technology | Public use
36. CTMF: integration in applications
36
Semantic web under the hood: CTMF
| Semantic Web technologies: experiences in Novartis| Andrea Splendiani | 2nd December 2015| Technology | Public use
37. CTMF: term status page and discussion
37
Semantic web under the hood: CTMF
| Semantic Web technologies: experiences in Novartis| Andrea Splendiani | 2nd December 2015| Technology | Public use
38. CTMF: process (use of temporary ID)
38
Semantic web under the hood: CTMF
| Semantic Web technologies: experiences in Novartis| Andrea Splendiani | 2nd December 2015| Technology | Public use
39. Under the hood
39
Semantic web under the hood: CTMF
§ Basic principle of the Semantic Web: identity comes first.
• What “people can talk about” is give an URI, and information is built around it.
§ The CTMF adopts the same approach:
• a “term” request is in itself identifying a concept: what the requestor had in mind at the time of the
request. We give this idea a URI (the term status page)
• Information is built around this request (clarification).
• A “content owner” can assess whether the concept is identical to something already in metastore
(most likely what was requested for was a synonym), or whether a new concept should be
introduced.
| Semantic Web technologies: experiences in Novartis| Andrea Splendiani | 2nd December 2015| Technology | Public use
40. Semantic Web @Novartis
40
Topics
§ Semantic Web @Novartis
• Context (Where in Novartis)
• Semantic Web in production
• Semantic Web in research
• Semantic Web under the hood
§ Semantic Web in “Real Life”: open questions
| Semantic Web technologies: experiences in Novartis| Andrea Splendiani | 2nd December 2015| Technology | Public use
41. Semantic Web @Novartis
41
Topics
§ Semantic Web @Novartis
• Context (Where in Novartis)
• Semantic Web in production
• Semantic Web in research
- Query federation
- Visualization/interaction
- Other projects
• Semantic Web under the hood
§ Semantic Web in “Real Life”: open questions
| Semantic Web technologies: experiences in Novartis| Andrea Splendiani | 2nd December 2015| Technology | Public use
42. Semantic Web in Real Life: Open questions
42
Data trumps everything
§ If there is a choice between better technology to access
data, and better data, the latter prevails.
• Corollary: interest is often where there is little data, especially in the
public domain.
| Semantic Web technologies: experiences in Novartis| Andrea Splendiani | 2nd December 2015| Technology | Public use
43. Semantic Web in Real Life: Open questions
43
Industry (or real life) is big
§ Areas that look nearby on paper may be very distant
organization-wise.
• Bench-to-bedside data integration
| Semantic Web technologies: experiences in Novartis| Andrea Splendiani | 2nd December 2015| Technology | Public use
44. Semantic Web in Real Life: Open questions
44
You don’t know the semantics of your data
§ The semantic expressiveness of RDF may be too much
for what is represented in your data.
• You don’t always make your data
| Semantic Web technologies: experiences in Novartis| Andrea Splendiani | 2nd December 2015| Technology | Public use
45. Semantic Web in Real Life: Open questions
45
Is data integration really a shared goal ?
§ Not all stakeholders have interest in “opening” their data.
• When does a data producer gain in making its data more
accessible ?
| Semantic Web technologies: experiences in Novartis| Andrea Splendiani | 2nd December 2015| Technology | Public use
46. Semantic Web in Real Life: Open questions
46
Many people are doing SemWeb without knowing it
§ “My project is not based on RDF, it is based on a graph
with properties from controlled vocabularies.”
• Why not RDF?
- Too academic
- Need something that works
- URIs are too long
| Semantic Web technologies: experiences in Novartis| Andrea Splendiani | 2nd December 2015| Technology | Public use
47. § Therese Vachon
§ Pierre Parisot
§ Katia Vella
§ Frederic Sutter
§ Daniel Cronenberger
§ Fatma Oezdemir-Zaech
§ Anosha Siripala
§ Olivier Kreim
§ Gilles Hubert
§ Laurentiu Stanculescu
§ Marc Lieber
§ Martin Rezk (OnTop)
§ Andrea Splendiani
47
Semantic Web technologies
experiences in Novartis
| Semantic Web technologies: experiences in Novartis| Andrea Splendiani | 2nd December 2015| Technology | Public use