Science base usage analysis - AGU2016 - in21d08Sky Bristol
ScienceBase is a research infrastructure developed and operated by the U.S. Geological Survey with users and uses across a number of other agency and organization partners. Over four years ago, we released an Application Programming Interface (API) as the foundation of the system and took on the mindset that our progress would be measured by the uptake of the API by others beyond ourselves in developing interesting applications. We now measure success more by someone finding ScienceBase, organizing their data and information, developing an innovative API-driven application and then serendipitous discovery through a science meeting. Because of the way we built the RESTful API, we can characterize what parts of the system are employed. Analysis of usage data helps us take the supposition out of what works and guides design and funding decisions. This analytics-based process facilitates regular adjustments to our thinking and allows us to test design decisions as hypotheses rather than untestable aspirations.
In this paper we compare two alternate machine-learning techniques from the Apache Mahout stable, namely: Apache Sparks’, spark-item similarity, and its counterpart Apache Hadoop’s MapReduce. We compare these both qualitatively as well as quantitatively in the context of two e-commerce stores with different behavior to determine which one is more effective and efficient in a given context.
When and Why to Use Shiny for Commercial ApplicationsTanya Cashorali
Building data products is no easy feat. At TCB Analytics, we always start with the question(s) we want to answer and then immediately identify relevant data sets. At what point though, does it make sense to build something? We discuss various examples of client work in which we used Shiny to rapidly protoype, pull data from APIs, leverage Google Vision's image recognition service and more.
In our last paper we compared two alternate machine-learning techniques from
the Apache Mahout stable, namely: Apache Sparks’, spark-itemsimilarity, and its
counterpart Apache Hadoop’s MapReduce. We saw how Apache Spark was better
both qualitatively as well as quantitatively even for moderately sized sites.
In this paper, we look at how we can further optimize the efficiency of these runs
without compromising on quality. We determine how the two algorithms we
studied last time perform when run on all data available and when run only with
success data. In the e-commerce domain, success data is defined, as a subset of
the total data, which we heuristically believe, does not include noise.
Science base usage analysis - AGU2016 - in21d08Sky Bristol
ScienceBase is a research infrastructure developed and operated by the U.S. Geological Survey with users and uses across a number of other agency and organization partners. Over four years ago, we released an Application Programming Interface (API) as the foundation of the system and took on the mindset that our progress would be measured by the uptake of the API by others beyond ourselves in developing interesting applications. We now measure success more by someone finding ScienceBase, organizing their data and information, developing an innovative API-driven application and then serendipitous discovery through a science meeting. Because of the way we built the RESTful API, we can characterize what parts of the system are employed. Analysis of usage data helps us take the supposition out of what works and guides design and funding decisions. This analytics-based process facilitates regular adjustments to our thinking and allows us to test design decisions as hypotheses rather than untestable aspirations.
In this paper we compare two alternate machine-learning techniques from the Apache Mahout stable, namely: Apache Sparks’, spark-item similarity, and its counterpart Apache Hadoop’s MapReduce. We compare these both qualitatively as well as quantitatively in the context of two e-commerce stores with different behavior to determine which one is more effective and efficient in a given context.
When and Why to Use Shiny for Commercial ApplicationsTanya Cashorali
Building data products is no easy feat. At TCB Analytics, we always start with the question(s) we want to answer and then immediately identify relevant data sets. At what point though, does it make sense to build something? We discuss various examples of client work in which we used Shiny to rapidly protoype, pull data from APIs, leverage Google Vision's image recognition service and more.
In our last paper we compared two alternate machine-learning techniques from
the Apache Mahout stable, namely: Apache Sparks’, spark-itemsimilarity, and its
counterpart Apache Hadoop’s MapReduce. We saw how Apache Spark was better
both qualitatively as well as quantitatively even for moderately sized sites.
In this paper, we look at how we can further optimize the efficiency of these runs
without compromising on quality. We determine how the two algorithms we
studied last time perform when run on all data available and when run only with
success data. In the e-commerce domain, success data is defined, as a subset of
the total data, which we heuristically believe, does not include noise.
Organizing Scientific Competitions on the Semantic WebSayoko Shimoyama
[Abstract]
Semantic web techniques for Linked Open Data (LOD) are expected to enhance the use of scientific data, and several data repositories for LOD have been launched. Modifiable “Forkable Open-source programs” on code sharing platforms make applications (Apps) utilizing data ready for reuse. In order to organize a web-based scientific competition, platforms for both semantic data resources and application programs need to be integrated so as to yield a crea- tive cycle between data publication and application development. We devel- oped the LinkData.org platform to integrate both data and application publish- ing platforms by recording dependency graphs, the utility of which we tested by organizing a scientific competition for synthetic biology on the platform. It was found that participants to the competition generated many dependency graphs by forking pre-existing applications or reusing schema of pre-existing datasets. These creative activities could not be observed explicitly without being record- ed such as by dependency graphs among the datasets and applications on the platform. Hence we suggest a worldwide system needs to be established to re- cord and harvest such dependency graphs from distributed data platforms and application-development platforms around the world, so that our intellectual and creative activities using open datasets for application development may be recorded properly.
http://link.springer.com/chapter/10.1007%2F978-3-642-40285-2_27
Game-Changing Power of React Native for Businesses in 2024Andolasoft Inc
React native apps provide the perfect solution as businesses can create apps for all mobile devices cost-effective . With this cross-platform development technology, developers write the code-base once and deploy it on all mobile OS.
Data has been around for a long time. But only in two formats ANALOG and DIGITAL. Recently at an ever increasing rate DIGITAL DATA is growing exponentially year over year. Understand the best practice in Data Integration.
PERFORMANCE ENHANCEMENT OF WEBPAGE USING PROGRESSIVE WEB APP FEATURESAM Publications
The progressive web application combines the best of web and mobile apps. It is a website built using web technologies that acts like an app. Recent advancements in the browser, availability of service workers, Cache and Push APIs have enabled web developers to allow users to install web apps to their home screen, receive push notifications and even work offline. To use a traditional app, the user must install it beforehand which includes multiple clicks making the app unappealing to the user. This problem is solved by using PWA enabled webpage. The user is given the advantage of accessing the webpage app-like by creating a desktop icon which eliminates the need for multiple clicks. The primary characteristic of this progressive web app is that it must work on all devices and must enhance on devices and browsers that allow it. They take advantage of the much larger web ecosystem, plugins and community and the relative ease of deploying and maintaining a website when compared to a native application in the respective app stores.
https://www.youtube.com/watch?v=nvlHJgRE3pU
Won ITAC Graduation Projects Competition, ITAC ID: GP2015.R10.75
A web application that analyze big volumes of product reviews, social networks posts and tweets related to a given product. Then, present these results of this big data analytical job in a user friendly, understandable, and easily interpreted manner that can be used by different customers for different purposes.
Technologies used:
1- Hadoop
2- Hadoop Streaming
3- R Statistical
4- PHP
5- Google Charts API
Is the buzz around Progressive Web Apps real or are they simply the latest fad? In this talk, you’ll learn exactly what Progressive Web Apps are, what problems they solve, and what new design challenges they present. Jason will show how organizations are using Progressive Web Apps to provide better and faster user experiences.
Organizing Scientific Competitions on the Semantic WebSayoko Shimoyama
[Abstract]
Semantic web techniques for Linked Open Data (LOD) are expected to enhance the use of scientific data, and several data repositories for LOD have been launched. Modifiable “Forkable Open-source programs” on code sharing platforms make applications (Apps) utilizing data ready for reuse. In order to organize a web-based scientific competition, platforms for both semantic data resources and application programs need to be integrated so as to yield a crea- tive cycle between data publication and application development. We devel- oped the LinkData.org platform to integrate both data and application publish- ing platforms by recording dependency graphs, the utility of which we tested by organizing a scientific competition for synthetic biology on the platform. It was found that participants to the competition generated many dependency graphs by forking pre-existing applications or reusing schema of pre-existing datasets. These creative activities could not be observed explicitly without being record- ed such as by dependency graphs among the datasets and applications on the platform. Hence we suggest a worldwide system needs to be established to re- cord and harvest such dependency graphs from distributed data platforms and application-development platforms around the world, so that our intellectual and creative activities using open datasets for application development may be recorded properly.
http://link.springer.com/chapter/10.1007%2F978-3-642-40285-2_27
Game-Changing Power of React Native for Businesses in 2024Andolasoft Inc
React native apps provide the perfect solution as businesses can create apps for all mobile devices cost-effective . With this cross-platform development technology, developers write the code-base once and deploy it on all mobile OS.
Data has been around for a long time. But only in two formats ANALOG and DIGITAL. Recently at an ever increasing rate DIGITAL DATA is growing exponentially year over year. Understand the best practice in Data Integration.
PERFORMANCE ENHANCEMENT OF WEBPAGE USING PROGRESSIVE WEB APP FEATURESAM Publications
The progressive web application combines the best of web and mobile apps. It is a website built using web technologies that acts like an app. Recent advancements in the browser, availability of service workers, Cache and Push APIs have enabled web developers to allow users to install web apps to their home screen, receive push notifications and even work offline. To use a traditional app, the user must install it beforehand which includes multiple clicks making the app unappealing to the user. This problem is solved by using PWA enabled webpage. The user is given the advantage of accessing the webpage app-like by creating a desktop icon which eliminates the need for multiple clicks. The primary characteristic of this progressive web app is that it must work on all devices and must enhance on devices and browsers that allow it. They take advantage of the much larger web ecosystem, plugins and community and the relative ease of deploying and maintaining a website when compared to a native application in the respective app stores.
https://www.youtube.com/watch?v=nvlHJgRE3pU
Won ITAC Graduation Projects Competition, ITAC ID: GP2015.R10.75
A web application that analyze big volumes of product reviews, social networks posts and tweets related to a given product. Then, present these results of this big data analytical job in a user friendly, understandable, and easily interpreted manner that can be used by different customers for different purposes.
Technologies used:
1- Hadoop
2- Hadoop Streaming
3- R Statistical
4- PHP
5- Google Charts API
Is the buzz around Progressive Web Apps real or are they simply the latest fad? In this talk, you’ll learn exactly what Progressive Web Apps are, what problems they solve, and what new design challenges they present. Jason will show how organizations are using Progressive Web Apps to provide better and faster user experiences.
今回ご紹介するソフトウェア工学の新技術『逆マッシュアップ技術』は(独)理化学研究所の科学技術研究から生まれました
震災をきっかけに、多くの皆様、地方自治体に活用していただき、『オープンデータで助けあえる社会文化の創造』に向けて、この技術の普及に努めてまいりました
このたび、防災をテーマとしたEarth Communication Award 2013で『最優秀賞』をいただきました
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdfPaige Cruz
Monitoring and observability aren’t traditionally found in software curriculums and many of us cobble this knowledge together from whatever vendor or ecosystem we were first introduced to and whatever is a part of your current company’s observability stack.
While the dev and ops silo continues to crumble….many organizations still relegate monitoring & observability as the purview of ops, infra and SRE teams. This is a mistake - achieving a highly observable system requires collaboration up and down the stack.
I, a former op, would like to extend an invitation to all application developers to join the observability party will share these foundational concepts to build on:
Generative AI Deep Dive: Advancing from Proof of Concept to ProductionAggregage
Join Maher Hanafi, VP of Engineering at Betterworks, in this new session where he'll share a practical framework to transform Gen AI prototypes into impactful products! He'll delve into the complexities of data collection and management, model selection and optimization, and ensuring security, scalability, and responsible use.
Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...SOFTTECHHUB
The choice of an operating system plays a pivotal role in shaping our computing experience. For decades, Microsoft's Windows has dominated the market, offering a familiar and widely adopted platform for personal and professional use. However, as technological advancements continue to push the boundaries of innovation, alternative operating systems have emerged, challenging the status quo and offering users a fresh perspective on computing.
One such alternative that has garnered significant attention and acclaim is Nitrux Linux 3.5.0, a sleek, powerful, and user-friendly Linux distribution that promises to redefine the way we interact with our devices. With its focus on performance, security, and customization, Nitrux Linux presents a compelling case for those seeking to break free from the constraints of proprietary software and embrace the freedom and flexibility of open-source computing.
GraphSummit Singapore | The Art of the Possible with Graph - Q2 2024Neo4j
Neha Bajwa, Vice President of Product Marketing, Neo4j
Join us as we explore breakthrough innovations enabled by interconnected data and AI. Discover firsthand how organizations use relationships in data to uncover contextual insights and solve our most pressing challenges – from optimizing supply chains, detecting fraud, and improving customer experiences to accelerating drug discoveries.
How to Get CNIC Information System with Paksim Ga.pptxdanishmna97
Pakdata Cf is a groundbreaking system designed to streamline and facilitate access to CNIC information. This innovative platform leverages advanced technology to provide users with efficient and secure access to their CNIC details.
UiPath Test Automation using UiPath Test Suite series, part 6DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 6. In this session, we will cover Test Automation with generative AI and Open AI.
UiPath Test Automation with generative AI and Open AI webinar offers an in-depth exploration of leveraging cutting-edge technologies for test automation within the UiPath platform. Attendees will delve into the integration of generative AI, a test automation solution, with Open AI advanced natural language processing capabilities.
Throughout the session, participants will discover how this synergy empowers testers to automate repetitive tasks, enhance testing accuracy, and expedite the software testing life cycle. Topics covered include the seamless integration process, practical use cases, and the benefits of harnessing AI-driven automation for UiPath testing initiatives. By attending this webinar, testers, and automation professionals can gain valuable insights into harnessing the power of AI to optimize their test automation workflows within the UiPath ecosystem, ultimately driving efficiency and quality in software development processes.
What will you get from this session?
1. Insights into integrating generative AI.
2. Understanding how this integration enhances test automation within the UiPath platform
3. Practical demonstrations
4. Exploration of real-world use cases illustrating the benefits of AI-driven test automation for UiPath
Topics covered:
What is generative AI
Test Automation with generative AI and Open AI.
UiPath integration with generative AI
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
zkStudyClub - Reef: Fast Succinct Non-Interactive Zero-Knowledge Regex ProofsAlex Pruden
This paper presents Reef, a system for generating publicly verifiable succinct non-interactive zero-knowledge proofs that a committed document matches or does not match a regular expression. We describe applications such as proving the strength of passwords, the provenance of email despite redactions, the validity of oblivious DNS queries, and the existence of mutations in DNA. Reef supports the Perl Compatible Regular Expression syntax, including wildcards, alternation, ranges, capture groups, Kleene star, negations, and lookarounds. Reef introduces a new type of automata, Skipping Alternating Finite Automata (SAFA), that skips irrelevant parts of a document when producing proofs without undermining soundness, and instantiates SAFA with a lookup argument. Our experimental evaluation confirms that Reef can generate proofs for documents with 32M characters; the proofs are small and cheap to verify (under a second).
Paper: https://eprint.iacr.org/2023/1886
Dr. Sean Tan, Head of Data Science, Changi Airport Group
Discover how Changi Airport Group (CAG) leverages graph technologies and generative AI to revolutionize their search capabilities. This session delves into the unique search needs of CAG’s diverse passengers and customers, showcasing how graph data structures enhance the accuracy and relevance of AI-generated search results, mitigating the risk of “hallucinations” and improving the overall customer journey.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
Unlocking Productivity: Leveraging the Potential of Copilot in Microsoft 365, a presentation by Christoforos Vlachos, Senior Solutions Manager – Modern Workplace, Uni Systems
1. LinkData.org
“Reverse Mash-up” Support Tool
For those who want to play an active part in a Hackathon
– even without being able to program
Tetsuro Toyoda, Sayoko Shimoyama
October 21, 2013
For Japanese version, please see http://www.slideshare.net/tetsurotoyoda/ss-27381991
2. 11/8/2013
2
LinkData.org ~ Reverse Mash-up Support Tool ~
If it’s a “Reverse Mash-up”, Anyone can make an App
Mash-up
Reverse Mash-up
• Program Creation is
very difficult
• Existing data API is
re-used
• Program is re-used
• New data is turned into
an API and Inserted
Data
API
Data
API
Program
Creation
Data
API
Easy!
Mash-up
Program
Data Creation
turned into API
Reverse Mash-up
3. 11/8/2013
LinkData.org ~ Reverse Mash-up Support Tool ~
3
“Reverse Direction” Mash-up from Data to App
A
Companies
Data API
Forward Mash-up
Program
B
Companies
Data API
Reverse Mash-up
One’s
own
Data
Turn into API and Insert
If one’s own data is turned into an API and Reversely Mashed-up,
Already the Program and also Forward Mashed-up API
are indirectly mashed up
4. 11/8/2013
LinkData.org ~ Reverse Mash-up Support Tool ~
4
The Programmer limits the rate in conventional mash-up work
Forward Mash-up
Data Publisher
Programmer
Published by
Programmer
Reverse Mash-up
Data Publisher
Published by
Data Publisher
Reverse Mash-up Quickly without going through Programmer
5. 11/8/2013
LinkData.org ~ Reverse Mash-up Support Tool ~
Basic Technologies required for Mash-up
The possibility to easily turn data into an API and publish
Existing app and new API can be combined easily
The Data API is standardized (JSON /RDF/ SPARQL, etc.)
That the correspondence of the data and the app using the
data can be seen in both directions
That the interface is friendly and anyone can use easily
5
6. 11/8/2013
LinkData.org ~ Reverse Mash-up Support Tool ~
6
Reverse Mash-up Support Tool LinkData.org
http://linkdata.org
Target Users:
Those who promote data release
Not programmers, so they can’t make a
high quality application
Want to publish their own data by
mashing up with an existing great App
Even though they can’t program, want
to contribute to making data
Convinced that they can’t mash-up if
they can’t program
7. 11/8/2013
LinkData.org ~ Reverse Mash-up Support Tool ~
Reverse Mash-up Tutorial
① Choose the Reverse Mash-up target App
② Upload your own data
③ Copy the target App for yourself
④ Publish the combined Data and App
7
8. 11/8/2013
LinkData.org ~ Reverse Mash-up Support Tool ~
8
① Choose the Reverse Mash-up target App
Example: App that immediately sees congested spots
For each spot included
in the data set, the app
displays nearby
estimated numbers with
ranking in descending
order
Zenrin “Always NAVI
development kit API” is
used.
http://app.linkdata.org/
run/app1s420i
→ Reverse Mash-up with your own support data
9. 11/8/2013
LinkData.org ~ Reverse Mash-up Support Tool ~
② Upload your own data
1.
In the Target App details page
(http://app.linkdata.org/app/app1s420i)
Click on the “Input your own data”
button
2.
Create Data Template(Excel Format)
3.
Upload the template with the data
added to LinkData.org
9
10. 11/8/2013
LinkData.org ~ Reverse Mash-up Support Tool ~
③ Copy the target App for yourself
• On the target application detail page
(http://app.linkdata.org/app/app1s420i)
Click the “Create a new application by
forking this App” Button
10
11. 11/8/2013
LinkData.org ~ Reverse Mash-up Support Tool ~
11
④Publish the combined Data and App
1.
To open the “Input Data” tab,
click on the “Add Data” button
2.
Add data found using keywords
3.
Edit the Title or description with
“Configuring App”, and click the
“Finish Editing” button
The new App
is Complete!!
12. 2013/11/8
LinkData.org ~ Reverse Mash-up Support Tool ~
12
Open Data Era Software Engineering
It’s preferable if anyone is able to make Apps from Open Data
Publisher could quickly make disaster emergency data into App
What kind of Software Engineering is needed for this?
It’s also possible to rely on a programmer for an Open Data App,
but if there already is a good App, it’s preferable to be able to
insert data into it on the initiative of the data publisher side.
LinkData.org was born from our idea that in order to make Open
Data into an App there should be a “Reverse Mash-Up”
technology system as software engineering for this.
13. 11/8/2013
LinkData.org ~ Reverse Mash-up Support Tool ~
13
Using scientific technology to create a new culture
(Social Knowledge)
• The new Reverse Mash-up Technology
of the software engineering originally
introduced at this time was born from
the science and technology research of
Tetsuro Toyoda’s lab in RIKEN, Japan.
• We have committed our work to the
spread of this technology towards the
use of Open Data to help meet the
creation of social culture.
• I’m honored on this occasion
to have received the “Grand Prize”
of Earth Communication Award 2013
on the theme of disaster prevention.
14. 11/8/2013
LinkData.org ~ Reverse Mash-up Support Tool ~
14
【Acknowledgements】
“Reverse Mash-Up Technology” was developed in the RIKEN Toyoda Laboratory
as information technology infrastructure for Life Science Research
For Life Science Research...
Experimental results
between various species
need to be
compared and verified
Example: “PromoterCAD” App
in order to design plant genomic
sequences
The need for availability
of an App
to switch between the data
of various organisms
Achieved by
Reverse Mash-up
http://nar.oxfordjournals.org/content/41/W1/W569
We also had a research grant from the Japan Science and Technology Agency