2016 SDMX Experts meeting, An Alternative for implementing SDMX at IBGE, Luiz...StatsCommunications
The document summarizes alternatives for implementing the SDMX standard at IBGE to expose aggregated data. It discusses:
1) Mapping dimensions from SDMX data structure definitions to expressions in IBGE's SIDRA database to identify available indicators.
2) Querying SIDRA to process and format results in the SDMX style for response.
3) As a secondary option, mapping to IBGE's BME microdata database to generate custom aggregates if not available in SIDRA.
The document concludes SIDRA exposure would require less initial effort but mapping subjects to variables may not always be straightforward, requiring alternative approaches.
2016 SDMX Experts meeting, Implementation of SDMX RI at INS, Kamel AbdellaouiStatsCommunications
1. NIS Tunisia is implementing SDMX to standardize their data exchange and dissemination.
2. They are conducting training and building internal capacity on SDMX data modeling, reporting, and tools.
3. NIS Tunisia has created an SDMX action plan with three stages: testing and validating SDMX outputs internally, piloting data sharing with a national partner, and communicating SDMX to establish a national data hub.
2016 SDMX Experts meeting, An Alternative for implementing SDMX at IBGE, Luiz...StatsCommunications
The document summarizes alternatives for implementing the SDMX standard at IBGE to expose aggregated data. It discusses:
1) Mapping dimensions from SDMX data structure definitions to expressions in IBGE's SIDRA database to identify available indicators.
2) Querying SIDRA to process and format results in the SDMX style for response.
3) As a secondary option, mapping to IBGE's BME microdata database to generate custom aggregates if not available in SIDRA.
The document concludes SIDRA exposure would require less initial effort but mapping subjects to variables may not always be straightforward, requiring alternative approaches.
2016 SDMX Experts meeting, Implementation of SDMX RI at INS, Kamel AbdellaouiStatsCommunications
1. NIS Tunisia is implementing SDMX to standardize their data exchange and dissemination.
2. They are conducting training and building internal capacity on SDMX data modeling, reporting, and tools.
3. NIS Tunisia has created an SDMX action plan with three stages: testing and validating SDMX outputs internally, piloting data sharing with a national partner, and communicating SDMX to establish a national data hub.
The document discusses the 6th annual SIS-CC conference on creating and combining data experiences. It provides an overview of SIS-CC's growth over the past 6 years in building an open innovation ecosystem for data dissemination. Current product directions being discussed include developing an SDMX and Open Data strategy, streamlining data collection and dissemination processes, enabling new data experiences through reusable components, and providing details on ongoing SDMX initiatives.
2016 SDMX Experts meeting, SDMX Design & Modelling, Daniel SuranyiStatsCommunications
This document discusses guidelines for designing statistical data exchange artefacts using the SDMX standard. It describes an overall process that involves identifying exchange needs, developing a concept scheme, coding the concepts, creating a DSD matrix mapping data flows to concepts, optimizing the DSDs, and deriving final SDMX artefacts. It also suggests extending the guidelines to better support designing multi-domain exchanges by adding a step to derive concepts from statistical indicators.
2016 SDMX Experts meeting, National Accounts business case (validation, data ...StatsCommunications
This document discusses Eurostat's plans to implement SDMX standards to improve data sharing and reuse across statistical domains. Currently, Eurostat statistical production is organized in "stovepipes" by domain, using different conventions and IT tools. Eurostat aims to establish shared statistical services and an interoperability architecture using common standards like SDMX to enable cross-domain data usage, increase transparency, and allow efficient sharing of IT resources. SDMX tools will be implemented for tasks like metadata management, data validation, loading, and dissemination to achieve these goals and benefits like reduced production time, greater transparency, and economies of scale.
Experimental transformation of ABS data into Data Cube Vocabulary (DCV) form...Alistair Hamilton
Presentation by Al Hamilton and Cody Johnson to Canberra Semantic Web Meetup Group on why producers of official statistics are interested in semantic web community (including Linked Open Data) and outlining experimental work by Cody Johnson on transforming selected Population Census data released by the ABS in SDMX-ML to RDF Data Cube Vocabulary format.
Emerging Trends in Data Visualization and Dissemination discusses providing statistical data through application programming interfaces (APIs) and as a service rather than goods. It describes how mashups combine data from multiple sources into new applications and services. The document outlines benefits of mashups, how they work by retrieving data through APIs from different websites, and factors to consider when planning a mashup like data sources and programming languages. It provides examples of the United Nations' UNData and Comtrade initiatives that make international statistical databases freely available through APIs and web services.
DataGraft: Data-as-a-Service for Open Datadapaasproject
The document provides an overview of Linked (Open) Data including RDF, RDFS and SPARQL. It defines key concepts such as Linked Data principles of using URIs to identify things on the web and describing relationships between them. It describes RDF's basic data model of subject-predicate-object triples to make statements about resources and the RDF serialization formats of Turtle and JSON-LD. It also mentions semantic query language SPARQL for querying RDF data.
TileDB webinars - Nov 4, 2021
The document summarizes a webinar about TileDB, a universal data management platform that represents data as dense and sparse multi-dimensional arrays. It addresses the data management problems in population genomics by storing variant call data as 3D sparse arrays. TileDB provides a unified storage and serverless computing model that allows efficient data access and analysis at global scale through its open source TileDB Embedded storage and TileDB Cloud platform. The webinar highlights how TileDB solves data production, distribution, and consumption problems and empowers data sharing and collaboration through its marketplace and security features.
BDE-SC6 Hangout - “Insight into Virtual Currency Ecosystems”BigData_Europe
Third SC6 webinar was held on 16 February 2017. It was organised by the Consortium of Social Science Data Archives (CESSDA) from Norway and the Semantic Web Company (SWC) from Austria. Theme of the webinar was “Insight into Virtual Currency Ecosystems” presented by Dr. Bernhard Haslhofer, Data Scientist at the Austrian Institute of Technology.
This document discusses relational databases and Microsoft Access. It explains that a relational database uses tables to organize related data and that Access is an example of a relational database management system (RDBMS) that can create, manage and query databases. It provides details on database objects in Access like tables, queries, forms and reports and how to work with tables, including adding fields and records.
How to use R in different professions: R In Finance (Speaker: Gabriel Foix, M...Zurich_R_User_Group
R is a popular statistical programming language that is well-suited for use in the financial industry. It has a large talent pool of users, strong academic and community support, and packages for tasks like data manipulation, domain-specific analysis, and integration with other systems. R can help financial organizations handle large and complex data, build models and prototypes quickly, and meet regulatory requirements through features like documentation, testing, and traceability of work.
20141030 LinDA Workshop echallenges2014 - State of the art in open data infra...LinDa_FP7
This document provides an overview of open data infrastructures for public sector information. It discusses various open data sources including national statistical offices, data government initiatives, ministries, and linked open data clouds. It also outlines different types of open data like catalogs, relational databases, and linked data. Standards for open data are presented along with some common obstacles to utilizing open data. Finally, several popular open data platforms are described including CKAN, DKAN, and Socrata.
HDL - Towards A Harmonized Dataset Model for Open Data PortalsAhmad Assaf
This document discusses the need for a harmonized dataset model for open data portals. It describes existing dataset models like DCAT, VoID, CKAN, and others. It proposes classifying metadata into information groups (resource, tag, group, organization) and types (general, ownership, provenance, etc.). The document outlines a process for harmonizing existing models which includes mapping these information groups and types and examining how extras fields are used across different models and portals. The goal is to define a minimum set of metadata needed to build dataset profiles and enable interoperability.
The document discusses UnifiedViews, an open source tool for managing RDF data processing tasks. It was used in two pilot projects - with the Slovak Environmental Agency and Czech Trade Inspection Authority. For both pilots, UnifiedViews successfully deployed data pipelines to extract, transform, enrich, and publish their data as Linked Open Data on the Open Data Node platform. The pilots demonstrated how UnifiedViews can help publish administrative data as RDF to increase its reuse.
A short way in introducing my IT experience during a large section of Companies i DK, all Big Conglomerates with several Business areas of interest. Evolving and changing during decades.
Meeting today’s dissemination challenges – Implementing International Standar...Jonathan Challener
This document discusses the .Stat system, which serves as a central repository for validated statistics and metadata. .Stat connects data production, sharing, and dissemination processes. It provides three key functional areas: a data upload engine, a data delivery engine, and a data browser. .Stat can be mapped to stages in the Generic Statistical Business Process Model and incorporates standards like SDMX for dissemination, data exchange, and internal data sharing. The document outlines .Stat's current role and future plans to further support SDMX artifacts, ingest, registries, and semantic web opportunities.
The document discusses the 6th annual SIS-CC conference on creating and combining data experiences. It provides an overview of SIS-CC's growth over the past 6 years in building an open innovation ecosystem for data dissemination. Current product directions being discussed include developing an SDMX and Open Data strategy, streamlining data collection and dissemination processes, enabling new data experiences through reusable components, and providing details on ongoing SDMX initiatives.
2016 SDMX Experts meeting, SDMX Design & Modelling, Daniel SuranyiStatsCommunications
This document discusses guidelines for designing statistical data exchange artefacts using the SDMX standard. It describes an overall process that involves identifying exchange needs, developing a concept scheme, coding the concepts, creating a DSD matrix mapping data flows to concepts, optimizing the DSDs, and deriving final SDMX artefacts. It also suggests extending the guidelines to better support designing multi-domain exchanges by adding a step to derive concepts from statistical indicators.
2016 SDMX Experts meeting, National Accounts business case (validation, data ...StatsCommunications
This document discusses Eurostat's plans to implement SDMX standards to improve data sharing and reuse across statistical domains. Currently, Eurostat statistical production is organized in "stovepipes" by domain, using different conventions and IT tools. Eurostat aims to establish shared statistical services and an interoperability architecture using common standards like SDMX to enable cross-domain data usage, increase transparency, and allow efficient sharing of IT resources. SDMX tools will be implemented for tasks like metadata management, data validation, loading, and dissemination to achieve these goals and benefits like reduced production time, greater transparency, and economies of scale.
Experimental transformation of ABS data into Data Cube Vocabulary (DCV) form...Alistair Hamilton
Presentation by Al Hamilton and Cody Johnson to Canberra Semantic Web Meetup Group on why producers of official statistics are interested in semantic web community (including Linked Open Data) and outlining experimental work by Cody Johnson on transforming selected Population Census data released by the ABS in SDMX-ML to RDF Data Cube Vocabulary format.
Emerging Trends in Data Visualization and Dissemination discusses providing statistical data through application programming interfaces (APIs) and as a service rather than goods. It describes how mashups combine data from multiple sources into new applications and services. The document outlines benefits of mashups, how they work by retrieving data through APIs from different websites, and factors to consider when planning a mashup like data sources and programming languages. It provides examples of the United Nations' UNData and Comtrade initiatives that make international statistical databases freely available through APIs and web services.
DataGraft: Data-as-a-Service for Open Datadapaasproject
The document provides an overview of Linked (Open) Data including RDF, RDFS and SPARQL. It defines key concepts such as Linked Data principles of using URIs to identify things on the web and describing relationships between them. It describes RDF's basic data model of subject-predicate-object triples to make statements about resources and the RDF serialization formats of Turtle and JSON-LD. It also mentions semantic query language SPARQL for querying RDF data.
TileDB webinars - Nov 4, 2021
The document summarizes a webinar about TileDB, a universal data management platform that represents data as dense and sparse multi-dimensional arrays. It addresses the data management problems in population genomics by storing variant call data as 3D sparse arrays. TileDB provides a unified storage and serverless computing model that allows efficient data access and analysis at global scale through its open source TileDB Embedded storage and TileDB Cloud platform. The webinar highlights how TileDB solves data production, distribution, and consumption problems and empowers data sharing and collaboration through its marketplace and security features.
BDE-SC6 Hangout - “Insight into Virtual Currency Ecosystems”BigData_Europe
Third SC6 webinar was held on 16 February 2017. It was organised by the Consortium of Social Science Data Archives (CESSDA) from Norway and the Semantic Web Company (SWC) from Austria. Theme of the webinar was “Insight into Virtual Currency Ecosystems” presented by Dr. Bernhard Haslhofer, Data Scientist at the Austrian Institute of Technology.
This document discusses relational databases and Microsoft Access. It explains that a relational database uses tables to organize related data and that Access is an example of a relational database management system (RDBMS) that can create, manage and query databases. It provides details on database objects in Access like tables, queries, forms and reports and how to work with tables, including adding fields and records.
How to use R in different professions: R In Finance (Speaker: Gabriel Foix, M...Zurich_R_User_Group
R is a popular statistical programming language that is well-suited for use in the financial industry. It has a large talent pool of users, strong academic and community support, and packages for tasks like data manipulation, domain-specific analysis, and integration with other systems. R can help financial organizations handle large and complex data, build models and prototypes quickly, and meet regulatory requirements through features like documentation, testing, and traceability of work.
20141030 LinDA Workshop echallenges2014 - State of the art in open data infra...LinDa_FP7
This document provides an overview of open data infrastructures for public sector information. It discusses various open data sources including national statistical offices, data government initiatives, ministries, and linked open data clouds. It also outlines different types of open data like catalogs, relational databases, and linked data. Standards for open data are presented along with some common obstacles to utilizing open data. Finally, several popular open data platforms are described including CKAN, DKAN, and Socrata.
HDL - Towards A Harmonized Dataset Model for Open Data PortalsAhmad Assaf
This document discusses the need for a harmonized dataset model for open data portals. It describes existing dataset models like DCAT, VoID, CKAN, and others. It proposes classifying metadata into information groups (resource, tag, group, organization) and types (general, ownership, provenance, etc.). The document outlines a process for harmonizing existing models which includes mapping these information groups and types and examining how extras fields are used across different models and portals. The goal is to define a minimum set of metadata needed to build dataset profiles and enable interoperability.
The document discusses UnifiedViews, an open source tool for managing RDF data processing tasks. It was used in two pilot projects - with the Slovak Environmental Agency and Czech Trade Inspection Authority. For both pilots, UnifiedViews successfully deployed data pipelines to extract, transform, enrich, and publish their data as Linked Open Data on the Open Data Node platform. The pilots demonstrated how UnifiedViews can help publish administrative data as RDF to increase its reuse.
A short way in introducing my IT experience during a large section of Companies i DK, all Big Conglomerates with several Business areas of interest. Evolving and changing during decades.
Meeting today’s dissemination challenges – Implementing International Standar...Jonathan Challener
This document discusses the .Stat system, which serves as a central repository for validated statistics and metadata. .Stat connects data production, sharing, and dissemination processes. It provides three key functional areas: a data upload engine, a data delivery engine, and a data browser. .Stat can be mapped to stages in the Generic Statistical Business Process Model and incorporates standards like SDMX for dissemination, data exchange, and internal data sharing. The document outlines .Stat's current role and future plans to further support SDMX artifacts, ingest, registries, and semantic web opportunities.
Advanced Analytics and Machine Learning with Data VirtualizationDenodo
This document summarizes a webinar on data virtualization presented by Denodo. It discusses common data challenges faced by data scientists, including spending significant time locating, transforming, and preparing data from various sources. It then introduces data virtualization as a solution, which provides a centralized catalog and logical view of data that reduces the data science workflow from months to days. Examples are given of customers like a healthcare company and industrial real estate company using Denodo's data virtualization platform to more easily discover, access, and analyze their diverse data sources. Key benefits highlighted include increased data and analytics agility, reduced data preparation time, and enabling self-service analytics.
This document describes d-Wise, a technology consulting company founded in 2003 that provides services for life sciences and healthcare companies. It offers systems implementation, data warehousing, standards implementation, business intelligence, and data analytics services. The company has experience with clinical data standards, clinical systems integration, and SAS solutions. It also describes d-Wise's experience implementing data warehousing and analytics projects for pharmaceutical, biotech, healthcare, and insurance companies.
Lecture at an event "SEEDS Kick-off meeting", FORS, Lausanne, Switzerland.
Related materials: http://www.snf.ch/en/funding/programmes/scopes/Pages/default.aspx
http://seedsproject.ch/?page_id=368
Standard Safeguarding Dataset - overview for CSCDUG.pptxRocioMendez59
13 July, 2023 - CSCDUG Online Event
Presenting the Sector-led Standard Safeguarding Dataset
Colleagues from Data to Insight, the LA-led service for children’s safeguarding data professionals, are delivering a DfE-funded project in partnership with LAs to define a new “standard safeguarding dataset” which all LAs will be able to produce from their safeguarding information systems.
At this session, they shared what they’ve learned so far from user research with LA colleagues and discussed their early thinking about what a better standard dataset might look like. Participants shared their own thoughts about how to improve these systems and processes.
Presenters
Alistair Herbert
Alistair is the lead officer for Data to Insight, the LA-led service for children’s safeguarding data professionals. With a career focused on local authority children’s services data work, he knows about safeguarding data, information systems, and cross-organisation collaboration.
John Foster
John is a Data Manager for Data to Insight. He has supported a range of children’s services data work, most recently at Shropshire Council. He led Data to Insight’s project to introduce the first national benchmarking dataset for Early Help, and is the user research lead for Data to Insight’s Standard Safeguarding Dataset project.
Rob Harrison and Joe Cornford-Hutchings
Rob and Joe are new Data Managers joining Data to Insight from the private and public sector respectively. They bring between them a wealth of experience and technical expertise, and will be working together to support design and implementation of the new Standard Safeguarding Dataset through 2023-24.
This document provides an overview and strategy for big and fast data initiatives in 2017. It discusses the data landscape including volume, velocity, variety and validity. It evaluates different data platform technologies and outlines requirements. The vision is described as "Business Insights at the Speed of Light". The strategy focuses on speed and leveraging key technologies like Spark. A roadmap with initiatives around insights, infrastructure, ingestion and big BI is presented. High level architectures for streaming and data flow are shown. Finally, data preparation vendors are compared.
The document describes an architecture for semantically integrating enterprise data lakes. It proposes a knowledge graph that links metadata, data models and key performance indicators to provide a common meaning for data. Raw data is stored in a data lake and ingested from various sources. A metadata layer captures dataset metadata, ontologies and integration rules to link disparate data. An interface allows users to access consolidated views generated by executing queries on Hadoop. The process involves cataloging, discovering, lifting, linking and validating datasets to integrate them based on rules into the knowledge graph.
1. Thailand's National Statistical Office implemented .Stat Suite, an open-source SDMX platform, to more efficiently produce and disseminate statistical data according to international standards.
2. Key benefits of .Stat Suite included being open-source, supporting global statistical standards and processes, and facilitating data sharing through connections to tools like Power BI, Excel, R and Python.
3. Moving forward, Thailand plans to further promote data integration and exchange between government agencies using SDMX standards, and support agencies in creating machine-readable data files that can be disseminated through a central Government Data Catalog platform.
Advanced Analytics and Machine Learning with Data VirtualizationDenodo
Watch here: https://bit.ly/3719Bi7
Advanced data science techniques, like machine learning, have proven an extremely useful tool to derive valuable insights from existing data. Platforms like Spark, and complex libraries for R, Python and Scala put advanced techniques at the fingertips of the data scientists. However, these data scientists spent most of their time looking for the right data and massaging it into a usable format. Data virtualization offers a new alternative to address these issues in a more efficient and agile way.
Attend this webinar and learn:
-How data virtualization can accelerate data acquisition and massaging, providing the data scientist with a powerful tool to complement their practice
- How popular tools from the data science ecosystem: Spark, Python, Zeppelin, Jupyter, etc. integrate with Denodo
- How you can use the Denodo Platform with large data volumes in an efficient way
-About the success McCormick has had as a result of seasoning the Machine Learning and Blockchain Landscape with data virtualization
IRJET - A Framework for Tourist Identification and Analytics using Transport ...IRJET Journal
This document presents a framework for identifying and analyzing tourists using transport data. Big data technologies are used to monitor tourist movement and evaluate travel behavior in scenic areas. Transport data is isolated using Hadoop tools like HDFS, MapReduce, Sqoop, Hive and Pig. This allows processing large transport data sets without data loss issues. The data is analyzed to represent tourist hotspots, locations and preferences. Visualization tools like R are then used to provide insights into the analytics results. The framework aims to provide better information and perspectives to stakeholders like tour companies and transport operators using transport data.
This document discusses how big data analytics can be used in the baking sector. It defines big data as large, complex datasets that are difficult to process and store using traditional databases. Sources of big data include social media, sensors, online shopping, and data from various companies. Big data is characterized by its volume, velocity, and variety. Analytics involves applying mathematical and statistical tools to build predictive models from data. Hadoop is an open-source framework that can analyze big data cheaper and faster using clustered commodity hardware. Using big data analytics allows banks to detect fraud, manage risk, optimize customer service, target offers, and improve credit scoring.
The document contains the resume of S Mahabhoob Basha. It summarizes his career experience working for various companies over 9+ years developing applications using technologies like SSIS, SSRS, SQL Server, VB.Net and C#.Net. It lists his roles and responsibilities in multiple projects for clients like Microsoft, Bank of America, and Unilever. It also provides details of his technical skills, qualifications, and personal details.
How to use NCI's national repository of big spatial data collectionsARDC
This document provides an overview of how to access spatial data collections through the National Computational Infrastructure (NCI). It describes NCI's data catalog that contains various climate, satellite, and other geoscience datasets. The document outlines how users can browse the catalog, search for specific collections like CMIP5, and view metadata. It also explains that datasets are stored on NCI's global filesystems and made available through data services like THREDDS, which provides OPeNDAP, WMS, WCS, and other access methods. Users can find datasets, view them visually through Godiva, or download files through these services.
Manish Sharma is a MSBI/SQL developer with over 4 years of experience working with tools like SQL Server, SSIS, SSRS and QlikView. He has worked on projects for clients like Accenture, Harmony Information Systems, and ICICI Prudential. Currently he works as a MSBI/QlikView developer for Accenture Services Pvt. Ltd. in Mumbai, India.
Similar to 2016 SDMX Experts meeting, Using SDMX to build the SDGs Database, Abdulla Gozalov (20)
Globally inclusive approaches to measurement_Shigehiro Oishi.pdfStatsCommunications
This document discusses measurement issues in comparing well-being and culture across countries. It covers 5 main issues: 1) Response styles may not fully explain differences in life satisfaction scores between countries. 2) Well-being items do not always function the same way across cultures, though lack of measurement equivalence only partly explains score differences. 3) Self-presentation and 4) judgmental/memory biases may also contribute to differences to a small-moderate degree. 5) The meaning and desirability of happiness differs across cultures, which can further impact scores. The document also advocates developing indigenous well-being measures that are meaningful within each local context.
Globally inclusive approaches to measurement_Erhabor Idemudia.pdfStatsCommunications
This document discusses considerations for developing quality of life measures from an African perspective. It notes that many existing QoL instruments were developed for Western populations and do not account for cultural differences. In Africa, concepts like happiness are more closely tied to collective well-being and social harmony rather than individualism. The document also outlines some key African beliefs, like Ubuntu, which emphasizes interconnectedness. It argues that QoL measures for Africa must assess both objective and subjective domains, and be grounded in cultural values like family, community, and spirituality rather than only Western individualistic norms. Developing culturally appropriate QoL measures is important for capturing well-being in a meaningful way.
Globally inclusive approaches to measurement_Rosemary Goodyear.pdfStatsCommunications
Stats NZ has taken several steps to incorporate Māori perspectives when measuring quality of life and well-being in New Zealand. This includes developing the Te Kupenga Māori social survey, incorporating some concepts from Te Kupenga into the General Social Survey, working with partners on using administrative data for Māori, and trialling iwi-led data collections for the Census. Te Kupenga uses frameworks like Whare Tapu Whā and focuses on cultural well-being areas like spirituality, customs, te reo Māori, and social connectedness. It provides statistics on these areas as well as demographics, paid work, health, and other topics from a Māori
A better understanding of domain satisfaction: Validity and policy use_Alessa...StatsCommunications
The document discusses Italy's inclusion of domain satisfaction indicators in its framework for measuring well-being (BES). It provides background on Italy's system of social surveys and outlines the development of the BES project, which aims to measure equitable and sustainable well-being. The BES framework includes 12 domains of well-being and over 150 indicators, including subjective well-being indicators and indicators measuring satisfaction within other domains like health, work, relationships, safety, environment and more. The document presents examples of domain satisfaction indicators and trends over time in areas like friends relations and landscape satisfaction.
A better understanding of domain satisfaction: Validity and policy use_Anthon...StatsCommunications
Domain satisfaction measures provide valid and useful information about people's lives beyond overall life satisfaction. Research has found that domain satisfaction captures different aspects of well-being than objective indicators alone, and that different life domains contribute differently to individual happiness. While domain satisfaction may be socially constructed and culturally variable, current policy efforts can still benefit from considering subjective experiences of satisfaction across life domains. Future research opportunities include exploring the multidimensional relationships between domain satisfaction and broader concepts of well-being.
A better understanding of domain satisfaction: Validity and policy use_Marian...StatsCommunications
Domains of life are important for understanding life satisfaction and informing better policymaking. The document discusses four key points:
1) It is important to consider multiple domains of life, not just economic factors, to understand people's overall well-being.
2) Domains of life represent different areas that people spend their time and where they make decisions, such as family, health, work, community.
3) Considering domains of life can provide insight into life satisfaction and help create more effective policies in areas like health, education, and social programs.
4) Current government institutions and policies can be better aligned to impact the domains of life that influence overall life satisfaction.
Measuring subjective well-being in children and young people_Sabrina Twilhaar...StatsCommunications
This document summarizes Sabrina Twilhaar's presentation on new frontiers in subjective well-being measurement for children. It discusses Bronfenbrenner's ecological systems theory and how children's well-being is influenced by multiple levels including micro (family, peers), meso (school), exo (neighborhood), and macro (culture, economy) systems. It then reviews literature on conceptualizing and measuring hedonic and eudaimonic well-being in children, noting gaps like a focus on life satisfaction over affect. Research finds children's well-being varies by age and sex, and is associated with family relationships and bullying. Overall, more work is needed to develop valid cross-cultural measures of multiple
Towards a more comprehensive measure of eudaimonia_Nancy Hey.pdfStatsCommunications
This document summarizes recent research on measuring subjective well-being, with a focus on measuring how worthwhile people feel the things they do in life are. Some key findings include:
- In the UK, on average people rate their sense that the things they do are worthwhile at 7.86 out of 10, while 3.8% rate it between 0-4 out of 10.
- People in their late 60s and early 70s report the highest sense of worthwhile, while people over 85 and those aged 18-24 report the lowest.
- Factors associated with a higher sense of worthwhile include being older than 45/55, female, white, belonging to a religion, home ownership, higher income
Towards a more comprehensive measure of eudaimonia_Carol Graham.pdfStatsCommunications
1) The document discusses measuring hope as a distinct dimension of well-being, in addition to evaluative, hedonic, and eudaimonic measures. Hope is strongly linked to future-oriented behavior and investing in one's future.
2) Research has found unequal distributions of hope can act as a barrier to health and prosperity. People with higher hope are more likely to aspire to and achieve education and avoid risky behaviors. They also earn more, have stronger social connections, and live longer, healthier lives.
3) Areas and communities with high despair show vulnerabilities like increased deaths of despair, misinformation, and radicalization. Restoring hope is important for mental health recovery and addressing societal threats
Towards a more comprehensive measure of eudaimonia_Carol Ryff.pdfStatsCommunications
This document summarizes Carol Ryff's presentation on bringing measures of eudaimonia or human flourishing to OECD measures of subjective well-being. Ryff discusses defining eudaimonia based on Aristotle and modern views, developing scales to measure six dimensions of eudaimonia, and scientific findings linking higher eudaimonia to better health outcomes. Ryff also notes growing inequality in measures of well-being and calls for credible measurement of select eudaimonic factors like purpose in life and personal growth to be included in large-scale studies like those by OECD to better inform public policy. There is potential for synergies between longitudinal cohort studies providing evidence and OECD's focus on policy issues.
Revisiting affect: Which states to measure, and how_Lucia Macchia.pdfStatsCommunications
This document discusses the relationship between physical pain and subjective well-being. It notes that physical pain can negatively impact subjective well-being through physical, socioeconomic, psychosocial, and behavioral factors. The document reviews several studies that have examined the links between pain and subjective well-being. It also presents data from the Gallup World Poll that shows trends in physical pain between 2009-2021 across 146 countries, and correlations between indicators of subjective well-being and physical pain. The document argues that governments should consider measuring physical pain when assessing societal well-being.
Revisiting affect: Which states to measure, and how_Conal Smith.pdfStatsCommunications
1) The document discusses the use of experienced wellbeing measures in cost-wellbeing analysis and recent developments in this area. It notes key challenges in obtaining meaningful income coefficients for experienced wellbeing measures compared to life satisfaction measures.
2) Regression results are presented analyzing the relationship between life satisfaction, experienced wellbeing measures like happiness, and factors like income, location, and life events. Income is found to have a smaller effect on experienced wellbeing than life satisfaction.
3) An application of using experienced wellbeing data to value urban green space is described, with results suggesting experienced wellbeing may provide different valuations than typical hedonic pricing estimates.
Revisiting affect: Which states to measure, and how_Arthur Stone.pdfStatsCommunications
This document summarizes Arthur Stone's presentation on the OECD's recommendations for measuring affective subjective well-being. Stone argues that the OECD's original strategy of measuring positive and negative affect using a yesterday recall period was sound. However, he suggests broadening the definition of affective well-being to include self-reported pain. Stone presents research showing monitoring pain in populations over time can provide insights, such as revealing increased rates of pain in younger generations without college degrees. He concludes by recommending the expansion of affective well-being measures in line with considering a broader definition and the drivers of its components.
Presentation from Tatsuyoshi Oba, Executive Manager of Group HR Division, Persol Holdings during the OECD WISE Centre & Persol Holdings Workshop on Advancing Employee Well-being in Business and Finance, 22 November 2023
Presentation from Amy Browne, Stewardship Lead, CCLA Investment Management, during the OECD WISE Centre & Persol Holdings Workshop on Advancing Employee Well-being in Business and Finance, 22 November 2023
06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Data and AI
Round table discussion of vector databases, unstructured data, ai, big data, real-time, robots and Milvus.
A lively discussion with NJ Gen AI Meetup Lead, Prasad and Procure.FYI's Co-Found
Learn SQL from basic queries to Advance queriesmanishkhaire30
Dive into the world of data analysis with our comprehensive guide on mastering SQL! This presentation offers a practical approach to learning SQL, focusing on real-world applications and hands-on practice. Whether you're a beginner or looking to sharpen your skills, this guide provides the tools you need to extract, analyze, and interpret data effectively.
Key Highlights:
Foundations of SQL: Understand the basics of SQL, including data retrieval, filtering, and aggregation.
Advanced Queries: Learn to craft complex queries to uncover deep insights from your data.
Data Trends and Patterns: Discover how to identify and interpret trends and patterns in your datasets.
Practical Examples: Follow step-by-step examples to apply SQL techniques in real-world scenarios.
Actionable Insights: Gain the skills to derive actionable insights that drive informed decision-making.
Join us on this journey to enhance your data analysis capabilities and unlock the full potential of SQL. Perfect for data enthusiasts, analysts, and anyone eager to harness the power of data!
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The Building Blocks of QuestDB, a Time Series Databasejavier ramirez
Talk Delivered at Valencia Codes Meetup 2024-06.
Traditionally, databases have treated timestamps just as another data type. However, when performing real-time analytics, timestamps should be first class citizens and we need rich time semantics to get the most out of our data. We also need to deal with ever growing datasets while keeping performant, which is as fun as it sounds.
It is no wonder time-series databases are now more popular than ever before. Join me in this session to learn about the internal architecture and building blocks of QuestDB, an open source time-series database designed for speed. We will also review a history of some of the changes we have gone over the past two years to deal with late and unordered data, non-blocking writes, read-replicas, or faster batch ingestion.
ViewShift: Hassle-free Dynamic Policy Enforcement for Every Data LakeWalaa Eldin Moustafa
Dynamic policy enforcement is becoming an increasingly important topic in today’s world where data privacy and compliance is a top priority for companies, individuals, and regulators alike. In these slides, we discuss how LinkedIn implements a powerful dynamic policy enforcement engine, called ViewShift, and integrates it within its data lake. We show the query engine architecture and how catalog implementations can automatically route table resolutions to compliance-enforcing SQL views. Such views have a set of very interesting properties: (1) They are auto-generated from declarative data annotations. (2) They respect user-level consent and preferences (3) They are context-aware, encoding a different set of transformations for different use cases (4) They are portable; while the SQL logic is only implemented in one SQL dialect, it is accessible in all engines.
#SQL #Views #Privacy #Compliance #DataLake
Unleashing the Power of Data_ Choosing a Trusted Analytics Platform.pdfEnterprise Wired
In this guide, we'll explore the key considerations and features to look for when choosing a Trusted analytics platform that meets your organization's needs and delivers actionable intelligence you can trust.
2. December 2015: Interagency and Expert
Group for SDG Indicators (IAEG-SDGs)
submits its report to the 47th United Nations
Statistical Commission
March 2016: UNSC agrees the SDGs indicator
framework
April 2016: UNSD requests SDGs data from
specialized agencies
May 2016: SDGs indicator data begin to arrive
18 July 2016: SDGs report and database due
to be released
3. May 2016: SDGs data
begin to arrive
18 July 2016:
Release database
?
4. April 2016: No certainty over indicators and
disaggregation to be received even in the short
term; relative clarity only reached in June
To be completed in less than two months:
◦ Receive and catalogue the data
◦ Carry out data entry
◦ Validate and release the data
To be developed:
◦ SDGs database
◦ Data entry tools
◦ Data validation tools
◦ Data dissemination
5. Because of time pressure, traditional data
systems development would not work
SDMX tools had the promise of making it
possible to configure a database system from
building blocks, with little or no software
development involved
6. MDG DSD was used as a foundation for the
SDGs database
Concepts and dimensionality were retained
Code lists were replaced to match the SDGs
dataset
The DSD had to be updated multiple times
throughout the exercise as data arrived and
codes had to be added for indicators and
their breakdowns, units of measure, etc.
7. IStat Loader was used to create the SDGs
database
◦ Automatically creates a database from a DSD
◦ Automatically configures mappings in SDMX
Reference Infrastructure for dissemination
The internal SDGs DSD was fed to Istat Loader
to create and update the database
8. Eurostat’s SDMX Converter used for data
entry
Excel data entry spreadsheets were created
and mappings configured between their cells
and the SDGs DSD
9. The data entry team copied SDGs data from
loosely formatted incoming Excel files to the
data entry spreadsheets and added codes for
series, dimensions, etc
SDMX Converter was used to retrieve data
from the Excel data entry spreadsheets and
format it as SDMX messages
Istat Loader was used to upload the SDMX
messages to the database
10. Eurostat’s SDMX Reference Infrastructure
(SDMX-RI) was used to retrieve data from the
database
Istat loader configures SDMX-RI mappings
automatically
11. SDMX-ML Data retrieved from the database was
then converted to JSON, from which presentation
was built for the SDGs Data and Visualization
Platform
Dissemination at UNSD’s UnData Platform was
configured by adapting procedures developed for
data exchange with UNESCO, which used a DSD
with the same concepts as MDG
SDMX dissemination through UnData API will be
available shortly
◦ And will then be used to power the Data and
Visualization Platform
13. Issues with special characters and extended
Latin characters in the tools used
◦ Sometimes took a lot of effort to investigate and
resolve
Updating the database from an updated DSD
was tedious and error-prone
These are teething problems, likely to be
overcome soon
14. Data processing and content validation had to
be done in Excel, outside of the system
◦ Validation and Transformation Language will
address this issue
Conversion from SDMX-ML to JSON had to be
developed manually using a non-standard
JSON format
◦ Will be resolved when SDMX-JSON support is added
to SDMX-RI
15. A high-profile database system was created
in a few weeks and populated with over
300,000 observations
Technology already exists to set up data
systems from building blocks
Dramatically lower cost of development,
dramatically higher productivity
Promise of more to come