CLARIN CMDI use case and flexible metadata schemes vty
Presentation for CLARIAH IG Linked Open Data on the latest developments for Dataverse FAIR data repository. Building SEMAF workflow with external controlled vocabularies support and Semantic API. Using the theory of inventive problem solving TRIZ for the further innovation in Linked Data.
Presentation for CLARIAH IG Linked Open Data on the latest developments for Dataverse FAIR data repository. Building SEMAF workflow with external controlled vocabularies support and Semantic API.
Flexibility in Metadata Schemes and Standardisation: the Case of CMDI and DAN...vty
Presentation at ISKO Knowledge Organisation Research Observatory. RESEARCH REPOSITORIES AND DATAVERSE: NEGOTIATING METADATA, VOCABULARIES AND DOMAIN NEEDS
The presentation for the W3C Semantic Web in Health Care and Life Sciences community group by Slava Tykhonov, DANS-KNAW, the Royal Netherlands Academy of Arts and Sciences (October 2020). The recording is available https://www.youtube.com/watch?v=G9oiyNM_RHc
Flexible metadata schemes for research data repositories - Clarin Conference...Vyacheslav Tykhonov
The development of the Common Framework in Dataverse and the CMDI use case. Building AI/ML based workflow for the prediction and linking concepts from external controlled vocabularies to the CMDI metadata values.
Ontologies, controlled vocabularies and Dataversevty
Presentation on Semantic Web technologies for Dataverse Metadata Working Group running by Institute for Quantitative Social Science (IQSS) of Harvard University.
CLARIN CMDI use case and flexible metadata schemes vty
Presentation for CLARIAH IG Linked Open Data on the latest developments for Dataverse FAIR data repository. Building SEMAF workflow with external controlled vocabularies support and Semantic API. Using the theory of inventive problem solving TRIZ for the further innovation in Linked Data.
Presentation for CLARIAH IG Linked Open Data on the latest developments for Dataverse FAIR data repository. Building SEMAF workflow with external controlled vocabularies support and Semantic API.
Flexibility in Metadata Schemes and Standardisation: the Case of CMDI and DAN...vty
Presentation at ISKO Knowledge Organisation Research Observatory. RESEARCH REPOSITORIES AND DATAVERSE: NEGOTIATING METADATA, VOCABULARIES AND DOMAIN NEEDS
The presentation for the W3C Semantic Web in Health Care and Life Sciences community group by Slava Tykhonov, DANS-KNAW, the Royal Netherlands Academy of Arts and Sciences (October 2020). The recording is available https://www.youtube.com/watch?v=G9oiyNM_RHc
Flexible metadata schemes for research data repositories - Clarin Conference...Vyacheslav Tykhonov
The development of the Common Framework in Dataverse and the CMDI use case. Building AI/ML based workflow for the prediction and linking concepts from external controlled vocabularies to the CMDI metadata values.
Ontologies, controlled vocabularies and Dataversevty
Presentation on Semantic Web technologies for Dataverse Metadata Working Group running by Institute for Quantitative Social Science (IQSS) of Harvard University.
Building collaborative Machine Learning platform for Dataverse network. Lecture by Slava Tykhonov (DANS-KNAW, the Netherlands), DANS seminar series, 29.03.2022
Controlled vocabularies and ontologies in Dataverse data repositoryvty
External controlled vocabularies support implementation is one of the most asked features by research communities. Slides for the Dataverse Community Meeting 2021 at Harvard University
Clariah Tech Day: Controlled Vocabularies and Ontologies in Dataversevty
This presentation is about external CVs support in Dataverse, Open Source data repository. Data Archiving and Networked Services (DANS-KNAW) decided to use Dataverse as a basic technology to build Data Stations and provide FAIR data services for various Dutch research communities.
Flexibility in Metadata Schemes and Standardisation: the Case of CMDI and the...Andrea Scharnhorst
Presentation given at ISKO UK: research observatory, November 24, 2021
RESEARCH REPOSITORIES AND DATAVERSE: NEGOTIATING METADATA, VOCABULARIES AND DOMAIN NEEDS
Vyacheslav Tykhonov, Jerry de Vries, Eko Indarto, Femmy Admiraal, Mike Priddy, and Andrea Scharnhorst: Flexibility in Metadata Schemes and Standardisation: the Case of CMDI and the DANS EASY Research Data Repository
Abstract:
The development of metadata schemes in data repositories (and other content providers) has always been a process of negotiation between the needs of the designated user communities and the content of the collection on the one side and standards developed in the field. Automatisation has both enabled and enforced standardisation and alignment of metadata schemes (see as an example). But, while designated user communities turned from being local users to global ones (due to web services), their specific needs have not vanished. Technology offers possibilities to give the aforementioned negotiation a new form. In this presentation, we present the Dataverse platform, used by many data repositories. We show - using the case of the CMDI metadata and the CLARIN (Common Language Resources and Technology Infrastructure)community - how the Dataverse common core set of metadata called Citation Block can be extended with custom fields defined as a discipline specific metadata block. In particular, we show how these custom fields can be connected to a distributed network of authoritative controlled vocabularies. So, that at the end semantic search is possible. The presentation highlights opportunities and challenges, based on our own experiences. Related work has been presented at the CLARIN Annual Conference 2021 (see Proceedings).
The Best of Both Worlds: Unlocking the Power of (big) Knowledge Graphs with S...Gezim Sejdiu
Over the past decade, vast amounts of machine-readable structured information have become available through the automation of research processes as well as the increasing popularity of knowledge graphs and semantic technologies.
A major and yet unsolved challenge that research faces today is to perform scalable analysis of large scale knowledge graphs in order to facilitate applications like link prediction, knowledge base completion, and question answering.
Most machine learning approaches, which scale horizontally (i.e. can be executed in a distributed environment) work on simpler feature vector based input rather than more expressive knowledge structures.
On the other hand, the learning methods which exploit the expressive structures, e.g. Statistical Relational Learning and Inductive Logic Programming approaches, usually do not scale well to very large knowledge bases owing to their working complexity.
This talk gives an overview of the ongoing project Semantic Analytics Stack (SANSA) which aims to bridge this research gap by creating an out of the box library for scalable, in-memory, structured learning.
DCMI Keynote: Bridging the Semantic Gaps and InteroperabilityMike Bergman
M. Bergman's presentation, 'Bridging the Gaps: Adaptive Approaches to Data Interoperabiity,' was a keynote at the DCMI's DC 2010 International Conference in Pittsburgh, PA, on October 22, 2010.
In the presentation, Bergman points to the Dublin Core Metadata Initiative as a unique and key player in plugging the semantics "gap" within the semantic Web. Some specific activities and roles are suggested.
Over the past decade, vast amounts of machine-readable structured information have become available through the automation of research processes as well as the increasing popularity of knowledge graphs and semantic technologies.
Today, we count more than 10,000 datasets made available online following Semantic Web standards.
A major and yet unsolved challenge that research faces today is to perform scalable analysis of large-scale knowledge graphs in order to facilitate applications in various domains including life sciences, publishing, and the internet of things.
The main objective of this thesis is to lay foundations for efficient algorithms performing analytics, i.e. exploration, quality assessment, and querying over semantic knowledge graphs at a scale that has not been possible before.
First, we propose a novel approach for statistical calculations of large RDF datasets, which scales out to clusters of machines.
In particular, we describe the first distributed in-memory approach for computing 32 different statistical criteria for RDF datasets using Apache Spark.
Many applications such as data integration, search, and interlinking, may take full advantage of the data when having a priori statistical information about its internal structure and coverage.
However, such applications may suffer from low quality and not being able to leverage the full advantage of the data when the size of data goes beyond the capacity of the resources available.
Thus, we introduce a distributed approach of quality assessment of large RDF datasets.
It is the first distributed, in-memory approach for computing different quality metrics for large RDF datasets using Apache Spark. We also provide a quality assessment pattern that can be used to generate new scalable metrics that can be applied to big data.
Based on the knowledge of the internal statistics of a dataset and its quality, users typically want to query and retrieve large amounts of information.
As a result, it has become difficult to efficiently process these large RDF datasets.
Indeed, these processes require, both efficient storage strategies and query-processing engines, to be able to scale in terms of data size.
Therefore, we propose a scalable approach to evaluate SPARQL queries over distributed RDF datasets by translating SPARQL queries into Spark executable code.
We conducted several empirical evaluations to assess the scalability, effectiveness, and efficiency of our proposed approaches.
More importantly, various use cases i.e. Ethereum analysis, Mining Big Data Logs, and Scalable Integration of POIs, have been developed and leverages by our approach.
The empirical evaluations and concrete applications provide evidence that our methodology and techniques proposed during this thesis help to effectively analyze and process large-scale RDF datasets.
All the proposed approaches during this thesis are integrated into the larger SANSA framework.
M. Durco, M. Windhouwer. Semantic Mapping in CLARIN Component Metadata. In E. Garoufallou and J. Greenberg (eds.), Metadata and Semantics Research (MTSR 2013; mtsr2013.teithe.gr), CCIS Vol. 390, Springer, Thessaloniki, Greece, November 20-22, 2013.
Flexible metadata schemes for research data repositories - CLARIN Conference'21vty
The development of the Common Framework in Dataverse and the CMDI use case. Building AI/ML based workflow for the prediction and linking concepts from external controlled vocabularies to the CMDI metadata values.
Building collaborative Machine Learning platform for Dataverse network. Lecture by Slava Tykhonov (DANS-KNAW, the Netherlands), DANS seminar series, 29.03.2022
Controlled vocabularies and ontologies in Dataverse data repositoryvty
External controlled vocabularies support implementation is one of the most asked features by research communities. Slides for the Dataverse Community Meeting 2021 at Harvard University
Clariah Tech Day: Controlled Vocabularies and Ontologies in Dataversevty
This presentation is about external CVs support in Dataverse, Open Source data repository. Data Archiving and Networked Services (DANS-KNAW) decided to use Dataverse as a basic technology to build Data Stations and provide FAIR data services for various Dutch research communities.
Flexibility in Metadata Schemes and Standardisation: the Case of CMDI and the...Andrea Scharnhorst
Presentation given at ISKO UK: research observatory, November 24, 2021
RESEARCH REPOSITORIES AND DATAVERSE: NEGOTIATING METADATA, VOCABULARIES AND DOMAIN NEEDS
Vyacheslav Tykhonov, Jerry de Vries, Eko Indarto, Femmy Admiraal, Mike Priddy, and Andrea Scharnhorst: Flexibility in Metadata Schemes and Standardisation: the Case of CMDI and the DANS EASY Research Data Repository
Abstract:
The development of metadata schemes in data repositories (and other content providers) has always been a process of negotiation between the needs of the designated user communities and the content of the collection on the one side and standards developed in the field. Automatisation has both enabled and enforced standardisation and alignment of metadata schemes (see as an example). But, while designated user communities turned from being local users to global ones (due to web services), their specific needs have not vanished. Technology offers possibilities to give the aforementioned negotiation a new form. In this presentation, we present the Dataverse platform, used by many data repositories. We show - using the case of the CMDI metadata and the CLARIN (Common Language Resources and Technology Infrastructure)community - how the Dataverse common core set of metadata called Citation Block can be extended with custom fields defined as a discipline specific metadata block. In particular, we show how these custom fields can be connected to a distributed network of authoritative controlled vocabularies. So, that at the end semantic search is possible. The presentation highlights opportunities and challenges, based on our own experiences. Related work has been presented at the CLARIN Annual Conference 2021 (see Proceedings).
The Best of Both Worlds: Unlocking the Power of (big) Knowledge Graphs with S...Gezim Sejdiu
Over the past decade, vast amounts of machine-readable structured information have become available through the automation of research processes as well as the increasing popularity of knowledge graphs and semantic technologies.
A major and yet unsolved challenge that research faces today is to perform scalable analysis of large scale knowledge graphs in order to facilitate applications like link prediction, knowledge base completion, and question answering.
Most machine learning approaches, which scale horizontally (i.e. can be executed in a distributed environment) work on simpler feature vector based input rather than more expressive knowledge structures.
On the other hand, the learning methods which exploit the expressive structures, e.g. Statistical Relational Learning and Inductive Logic Programming approaches, usually do not scale well to very large knowledge bases owing to their working complexity.
This talk gives an overview of the ongoing project Semantic Analytics Stack (SANSA) which aims to bridge this research gap by creating an out of the box library for scalable, in-memory, structured learning.
DCMI Keynote: Bridging the Semantic Gaps and InteroperabilityMike Bergman
M. Bergman's presentation, 'Bridging the Gaps: Adaptive Approaches to Data Interoperabiity,' was a keynote at the DCMI's DC 2010 International Conference in Pittsburgh, PA, on October 22, 2010.
In the presentation, Bergman points to the Dublin Core Metadata Initiative as a unique and key player in plugging the semantics "gap" within the semantic Web. Some specific activities and roles are suggested.
Over the past decade, vast amounts of machine-readable structured information have become available through the automation of research processes as well as the increasing popularity of knowledge graphs and semantic technologies.
Today, we count more than 10,000 datasets made available online following Semantic Web standards.
A major and yet unsolved challenge that research faces today is to perform scalable analysis of large-scale knowledge graphs in order to facilitate applications in various domains including life sciences, publishing, and the internet of things.
The main objective of this thesis is to lay foundations for efficient algorithms performing analytics, i.e. exploration, quality assessment, and querying over semantic knowledge graphs at a scale that has not been possible before.
First, we propose a novel approach for statistical calculations of large RDF datasets, which scales out to clusters of machines.
In particular, we describe the first distributed in-memory approach for computing 32 different statistical criteria for RDF datasets using Apache Spark.
Many applications such as data integration, search, and interlinking, may take full advantage of the data when having a priori statistical information about its internal structure and coverage.
However, such applications may suffer from low quality and not being able to leverage the full advantage of the data when the size of data goes beyond the capacity of the resources available.
Thus, we introduce a distributed approach of quality assessment of large RDF datasets.
It is the first distributed, in-memory approach for computing different quality metrics for large RDF datasets using Apache Spark. We also provide a quality assessment pattern that can be used to generate new scalable metrics that can be applied to big data.
Based on the knowledge of the internal statistics of a dataset and its quality, users typically want to query and retrieve large amounts of information.
As a result, it has become difficult to efficiently process these large RDF datasets.
Indeed, these processes require, both efficient storage strategies and query-processing engines, to be able to scale in terms of data size.
Therefore, we propose a scalable approach to evaluate SPARQL queries over distributed RDF datasets by translating SPARQL queries into Spark executable code.
We conducted several empirical evaluations to assess the scalability, effectiveness, and efficiency of our proposed approaches.
More importantly, various use cases i.e. Ethereum analysis, Mining Big Data Logs, and Scalable Integration of POIs, have been developed and leverages by our approach.
The empirical evaluations and concrete applications provide evidence that our methodology and techniques proposed during this thesis help to effectively analyze and process large-scale RDF datasets.
All the proposed approaches during this thesis are integrated into the larger SANSA framework.
M. Durco, M. Windhouwer. Semantic Mapping in CLARIN Component Metadata. In E. Garoufallou and J. Greenberg (eds.), Metadata and Semantics Research (MTSR 2013; mtsr2013.teithe.gr), CCIS Vol. 390, Springer, Thessaloniki, Greece, November 20-22, 2013.
Flexible metadata schemes for research data repositories - CLARIN Conference'21vty
The development of the Common Framework in Dataverse and the CMDI use case. Building AI/ML based workflow for the prediction and linking concepts from external controlled vocabularies to the CMDI metadata values.
Decentralised identifiers and knowledge graphs vty
Building an Operating System for Open Science: data integration challenges, Dataverse data repository and knowledge graphs. Lecture by Slava Tykhonov, DANS-KNAW, for the Journées Scientifiques de Rochebrune 2023 (JSR'23).
There have been many changes in the use of container technology over the last year. Data from a recent survey demonstrates how those changes are manifesting themselves in terms of the tools and vendors being used to manage containers. In addition, details are provided about the products being used for storage, networking and containers as a service.
An introduction to {code} by Dell EMC, our mission on containers, and our core project REX-Ray. This will give the audience an understanding of why REX-Ray is important and where you can go to learn more.
{code} and Containers - Open Source Infrastructure within Dell TechnologiesThe {code} Team
Learn how The {code} Team is building new infrastructure possibilities for persistent storage in all the major container ecosystems such as Kubernetes, Docker, and Mesos with native integrations and contributing the Container Storage Interface
@mire presentation at the 2014 CGSpace partner meeting. The presentation lists a number of new features in the upcoming DSpace 5 release as well as a call for participation to DCAT, the DSpace Community Advisory Team.
The DSpace 5 features that are covered include:
- ORCID
- Sherpa Romeo
- The Mirage 2 responsive theme for the XML User Interface
Tutorial Workgroup - Model versioning and collaborationPascalDesmarets1
Hackolade Studio has native integration with Git repositories to provide state-of-the-art collaboration, versioning, branching, conflict resolution, peer review workflows, change tracking and traceability. Mostly, it allows to co-locate data models and schemas with application code, and further integrate with DevOps CI/CD pipelines as part of our vision for Metadata-as-Code.
Co-located application code and data models provide the single source-of-truth for business and technical stakeholders.
We will take a deep dive into ArangoDB (https://www.arangodb.com/) together with Max (https://www.linkedin.com/in/maxneunhoeffer) one of the core developers of the product.
ArangoDB is a multi-model database, which means that it is a document store, a key/value store and a graph database, all in one engine and with a query language that supports all three data models, as well as joins and transactions. Queries can use a single data model or can even mix them.
ArangoDB scales out horizontally with convenient cluster deployment using Apache Mesos. Furthermore, the HTTP API can easily be extended by server-side JavaScript code using high performance access to the C++ database core.
During the talk I will show all these features using several different cloud deployments, since in most projects one will not deploy a ArangoDB monolith, but rather multiple instances, each either a possibly replicated single server, or a cluster. This demonstrates that all these properties together make ArangoDB a very useful and valuable tool in modern microservice oriented architectures.
Building data pipelines for modern data warehouse with Apache® Spark™ and .NE...Michael Rys
This presentation shows how you can build solutions that follow the modern data warehouse architecture and introduces the .NET for Apache Spark support (https://dot.net/spark, https://github.com/dotnet/spark)
Choosing PaaS: Cisco and Open Source Options: an overviewCisco DevNet
A session in the DevNet Zone at Cisco Live, Berlin. Confused by all the open source PaaS options out there? What criteria should you use to evaluate them? We seek to answer these questions in a systematic manner and will explore top technologies such as Mesos, Apprenda, Cloud Foundry and Kubernetes along with Cisco's Project Shipped and open source Mantl. The aim of this session will be to shed light on which platforms add value to your needs, applications and workloads.
Making Distributed Data Persistent Services Elastic (Without Losing All Your ...C4Media
Video and slides synchronized, mp3 and slide download available at URL http://bit.ly/1L2FXLC.
Joe Stein introduces Mesos and managing data services on it, presenting use cases for replacing classic solutions (like cold storage) with new functionality based on these technology. Filmed at qconnewyork.com.
Joe Stein is the CEO of Elodina, a startup focusing on the support & maintenance of third party open source software (like Mesos frameworks) as well as its own open source products & SaaS solutions. He is also the Founder and Principal Consultant of Big Data Open Source Security.
Decentralised identifiers for CLARIAH infrastructure vty
Slides of the presentation for CLARIAH community on the ideas how to make controlled vocabularies sustainable and FAIR (Findable, Accessible, Interoperable, Reusable) with the help of Decentralized Identifiers (DIDs).
Dataverse repository for research data in the COVID-19 Museumvty
The Covid-19 Museum has an ambition to create a platform to deposit, consult, aggregate and study heterogeneous data about the pandemics using features of a distributed web service. To achieve this purpose, Dataverse has been selected as a reliable FAIR data repository with built-in search engine and functionality that allows adding computing resources to explore archived resources both on data and metadata. Presentation by
Slava Tykhonov, DANS-KNAW (The Royal Netherlands Academy of Arts and Sciences). Université Paris Cité, 19 April 2022.
Richard's entangled aventures in wonderlandRichard Gill
Since the loophole-free Bell experiments of 2020 and the Nobel prizes in physics of 2022, critics of Bell's work have retreated to the fortress of super-determinism. Now, super-determinism is a derogatory word - it just means "determinism". Palmer, Hance and Hossenfelder argue that quantum mechanics and determinism are not incompatible, using a sophisticated mathematical construction based on a subtle thinning of allowed states and measurements in quantum mechanics, such that what is left appears to make Bell's argument fail, without altering the empirical predictions of quantum mechanics. I think however that it is a smoke screen, and the slogan "lost in math" comes to my mind. I will discuss some other recent disproofs of Bell's theorem using the language of causality based on causal graphs. Causal thinking is also central to law and justice. I will mention surprising connections to my work on serial killer nurse cases, in particular the Dutch case of Lucia de Berk and the current UK case of Lucy Letby.
Multi-source connectivity as the driver of solar wind variability in the heli...Sérgio Sacani
The ambient solar wind that flls the heliosphere originates from multiple
sources in the solar corona and is highly structured. It is often described
as high-speed, relatively homogeneous, plasma streams from coronal
holes and slow-speed, highly variable, streams whose source regions are
under debate. A key goal of ESA/NASA’s Solar Orbiter mission is to identify
solar wind sources and understand what drives the complexity seen in the
heliosphere. By combining magnetic feld modelling and spectroscopic
techniques with high-resolution observations and measurements, we show
that the solar wind variability detected in situ by Solar Orbiter in March
2022 is driven by spatio-temporal changes in the magnetic connectivity to
multiple sources in the solar atmosphere. The magnetic feld footpoints
connected to the spacecraft moved from the boundaries of a coronal hole
to one active region (12961) and then across to another region (12957). This
is refected in the in situ measurements, which show the transition from fast
to highly Alfvénic then to slow solar wind that is disrupted by the arrival of
a coronal mass ejection. Our results describe solar wind variability at 0.5 au
but are applicable to near-Earth observatories.
This presentation explores a brief idea about the structural and functional attributes of nucleotides, the structure and function of genetic materials along with the impact of UV rays and pH upon them.
Deep Behavioral Phenotyping in Systems Neuroscience for Functional Atlasing a...Ana Luísa Pinho
Functional Magnetic Resonance Imaging (fMRI) provides means to characterize brain activations in response to behavior. However, cognitive neuroscience has been limited to group-level effects referring to the performance of specific tasks. To obtain the functional profile of elementary cognitive mechanisms, the combination of brain responses to many tasks is required. Yet, to date, both structural atlases and parcellation-based activations do not fully account for cognitive function and still present several limitations. Further, they do not adapt overall to individual characteristics. In this talk, I will give an account of deep-behavioral phenotyping strategies, namely data-driven methods in large task-fMRI datasets, to optimize functional brain-data collection and improve inference of effects-of-interest related to mental processes. Key to this approach is the employment of fast multi-functional paradigms rich on features that can be well parametrized and, consequently, facilitate the creation of psycho-physiological constructs to be modelled with imaging data. Particular emphasis will be given to music stimuli when studying high-order cognitive mechanisms, due to their ecological nature and quality to enable complex behavior compounded by discrete entities. I will also discuss how deep-behavioral phenotyping and individualized models applied to neuroimaging data can better account for the subject-specific organization of domain-general cognitive systems in the human brain. Finally, the accumulation of functional brain signatures brings the possibility to clarify relationships among tasks and create a univocal link between brain systems and mental functions through: (1) the development of ontologies proposing an organization of cognitive processes; and (2) brain-network taxonomies describing functional specialization. To this end, tools to improve commensurability in cognitive science are necessary, such as public repositories, ontology-based platforms and automated meta-analysis tools. I will thus discuss some brain-atlasing resources currently under development, and their applicability in cognitive as well as clinical neuroscience.
Professional air quality monitoring systems provide immediate, on-site data for analysis, compliance, and decision-making.
Monitor common gases, weather parameters, particulates.
(May 29th, 2024) Advancements in Intravital Microscopy- Insights for Preclini...Scintica Instrumentation
Intravital microscopy (IVM) is a powerful tool utilized to study cellular behavior over time and space in vivo. Much of our understanding of cell biology has been accomplished using various in vitro and ex vivo methods; however, these studies do not necessarily reflect the natural dynamics of biological processes. Unlike traditional cell culture or fixed tissue imaging, IVM allows for the ultra-fast high-resolution imaging of cellular processes over time and space and were studied in its natural environment. Real-time visualization of biological processes in the context of an intact organism helps maintain physiological relevance and provide insights into the progression of disease, response to treatments or developmental processes.
In this webinar we give an overview of advanced applications of the IVM system in preclinical research. IVIM technology is a provider of all-in-one intravital microscopy systems and solutions optimized for in vivo imaging of live animal models at sub-micron resolution. The system’s unique features and user-friendly software enables researchers to probe fast dynamic biological processes such as immune cell tracking, cell-cell interaction as well as vascularization and tumor metastasis with exceptional detail. This webinar will also give an overview of IVM being utilized in drug development, offering a view into the intricate interaction between drugs/nanoparticles and tissues in vivo and allows for the evaluation of therapeutic intervention in a variety of tissues and organs. This interdisciplinary collaboration continues to drive the advancements of novel therapeutic strategies.
Slide 1: Title Slide
Extrachromosomal Inheritance
Slide 2: Introduction to Extrachromosomal Inheritance
Definition: Extrachromosomal inheritance refers to the transmission of genetic material that is not found within the nucleus.
Key Components: Involves genes located in mitochondria, chloroplasts, and plasmids.
Slide 3: Mitochondrial Inheritance
Mitochondria: Organelles responsible for energy production.
Mitochondrial DNA (mtDNA): Circular DNA molecule found in mitochondria.
Inheritance Pattern: Maternally inherited, meaning it is passed from mothers to all their offspring.
Diseases: Examples include Leber’s hereditary optic neuropathy (LHON) and mitochondrial myopathy.
Slide 4: Chloroplast Inheritance
Chloroplasts: Organelles responsible for photosynthesis in plants.
Chloroplast DNA (cpDNA): Circular DNA molecule found in chloroplasts.
Inheritance Pattern: Often maternally inherited in most plants, but can vary in some species.
Examples: Variegation in plants, where leaf color patterns are determined by chloroplast DNA.
Slide 5: Plasmid Inheritance
Plasmids: Small, circular DNA molecules found in bacteria and some eukaryotes.
Features: Can carry antibiotic resistance genes and can be transferred between cells through processes like conjugation.
Significance: Important in biotechnology for gene cloning and genetic engineering.
Slide 6: Mechanisms of Extrachromosomal Inheritance
Non-Mendelian Patterns: Do not follow Mendel’s laws of inheritance.
Cytoplasmic Segregation: During cell division, organelles like mitochondria and chloroplasts are randomly distributed to daughter cells.
Heteroplasmy: Presence of more than one type of organellar genome within a cell, leading to variation in expression.
Slide 7: Examples of Extrachromosomal Inheritance
Four O’clock Plant (Mirabilis jalapa): Shows variegated leaves due to different cpDNA in leaf cells.
Petite Mutants in Yeast: Result from mutations in mitochondrial DNA affecting respiration.
Slide 8: Importance of Extrachromosomal Inheritance
Evolution: Provides insight into the evolution of eukaryotic cells.
Medicine: Understanding mitochondrial inheritance helps in diagnosing and treating mitochondrial diseases.
Agriculture: Chloroplast inheritance can be used in plant breeding and genetic modification.
Slide 9: Recent Research and Advances
Gene Editing: Techniques like CRISPR-Cas9 are being used to edit mitochondrial and chloroplast DNA.
Therapies: Development of mitochondrial replacement therapy (MRT) for preventing mitochondrial diseases.
Slide 10: Conclusion
Summary: Extrachromosomal inheritance involves the transmission of genetic material outside the nucleus and plays a crucial role in genetics, medicine, and biotechnology.
Future Directions: Continued research and technological advancements hold promise for new treatments and applications.
Slide 11: Questions and Discussion
Invite Audience: Open the floor for any questions or further discussion on the topic.
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.
This pdf is about the Schizophrenia.
For more details visit on YouTube; @SELF-EXPLANATORY;
https://www.youtube.com/channel/UCAiarMZDNhe1A3Rnpr_WkzA/videos
Thanks...!
4. Out of the box CV support in Dataverse (1)
Source: Dataverse Metadata Schema
5. Out of the box CV support in Dataverse (2)
Internal vocabularies are stored in Dataverse, we need more CVs!
6. Semantic interoperability on the infrastructure level
Dataverse Semantic API in release 5.6: https://github.com/IQSS/dataverse/releases/tag/v5.6
“Dataset metadata can be retrieved, set, and updated using a new, flatter JSON-LD format -
following the format of an OAI-ORE export (RDA-conformant Bags), allowing for easier transfer of
metadata to/from other systems (i.e. without needing to know Dataverse's metadata block and field
storage architecture). This new API also allows for the update of terms metadata“.
External controlled vocabularies support is being developed by DANS in SSHOC project and
already integrated in Dataverse core in the release 5.7.
Proposal: https://docs.google.com/document/d/1txdcFuxskRx_tLsDQ7KKLFTMR_r9IBhorDu3V_r445w/
Interfaces: http://github.com/gdcc/dataverse-external-vocab-support
Integrations: Wikidata, ORCID, MeSH, Skosmos vocabularies
7. Building block: Skosmos to host ontologies
7
● SKOSMOS is developed in
Europe by the National Library
of Finland (NLF)
● active global user community
● search and browsing interface
for SKOS concept
● multilingual vocabularies
support
● used for different use cases
(publish vocabularies, build
discovery systems, vocabulary
visualization)
10. Dataverse deposit form with connection to
ontologies
Every field can be linked to the appropriate controlled vocabularies in FAIR way!
11. One metadata field can be linked to many ontologies
Language switch in Dataverse will change the language of suggested terms!
12. Configuration to add external controlled vocabularies
Pull Request to Dataverse core https://github.com/IQSS/dataverse/pull/7712
13. Javascript interface
CV interface implemented as
Javascript and placed outside of
Dataverse application.
internal:
“js-url”: “/resources/js/cvoc-interface.js”
External:
“js-url”:
“https://raw.githubusercontent.com/Dans-
labs/semantic-
gateway/main/static/js/interface.js”
14. Example of the CV configuration in Dataverse
Configuration in plugable JavaScript:
● Field cvocDemo connected to “unesco”
controlled vocabulary hosted by
Skosmos
● 4 languages available (en, fr, es, ru)
● js-url pointing to javascript gateway to
read and transform output from
external API endpoint
● every Skosmos concept cached
internally in Dataverse to increase the
sustainability
17. Suggestions for the usage of FAIR CVs
● Dutch Digital Heritage Network https://netwerkdigitaalerfgoed.nl
● Skosmos instances, for example, https://bartoc-skosmos.unibas.ch/en/
Skosmos client to access vocabularies https://pypi.org/project/skosmos-client/
● ORCID API to link CMDI records to identifiers of researchers
https://info.orcid.org
● CESSDA CV Service https://vocabularies.cessda.eu
More are coming! https://github.com/CLARIAH/awesome-humanities-
ontologies
18. Known issues with support of external CVs
● how CV support could be applied to any field
● support and ownership available vocabularies
● backward compatibility with fields from the old metadata schema
● clean UI experience (one selection can fill 1, 2 or 4 child fields)
● can we use non-managed vocabularies or free-text values in same field
● concept drift (the change of meaning of concepts)
● interoperability across all Dataverse instances
● how to ensure CVs are coming from authoritative services
19. Future plans
● Dataverse will be offered as an easy to install and maintain “archive in the
box” solution available for all data providers
● External controlled vocabularies will be available out-of-the-box and will be
included within CESSDA Metadata Schema (CMM) and CLARIN CMDI
● Dataverse administrators should be able to turn on external CV support for
any specific metadata field
● The same functionality will be implemented on the datafiles level to get
variables linked to external CVs
20. Future plans: linking data (files) to external CVs
Source: Scholars Portal’ Data Curation Tool (Canada)