Craig Neilson and Ray Matthews recently returned from North Carolina to learn about using DSpace, ePrints, and LOCKSS-Docs for providing permanent public access to state publications. OCLC has announced it is teaming with Google and MIT to harvest DSpace OAI-PMH metadata to turn it into a format which can be indexed and searched by Google. This will enable information about publications stored by governments and universities using this open source institutional archiving system to be readily retrievable.

A couple of months ago, we reported how Google Search will label if an image was AI-generated, edited by photo editing software or taken with a camera by working with Coalition for Content Provenance and Authenticity (C2PA) as a technical standard. Well, now Google officially supports C2PA metadata in the about this image feature.

Google wrote this morning, Google Search now supports this [C2PA] metadata in the "About this image" feature."

Google updated its image meta data documentation to add a new section for "How C2PA metadata can appear in Google Search results."

The new section reads:

If an image contains C2PA metadata, Google can extract those details and may show information in the "About this image" feature, such as how the image was created or if it was edited with AI tools. This metadata comes from a signer, which is usually an app, device, or service (for example, photo editing software, the camera itself, or other services that modify or create images) that meets the following conditions:

• The app, device, or service has adopted C2PA version 2.1 or later.
• The image's manifest must be signed by a certificate from a Certification Authority on the C2PA Trust List.

It does seem like Adobe products, like Photoshop, Illustrated, and others, do support this metadata.

I just wonder how it handles the image above, which I generate using Midjourney AI and then edit later in Photoshop.

Forum discussion at X.

November 19-22, 2013 Alexander Technological Educational Institute of Thessaloniki, Greece

Continuing the successful mission of previous MTSR Conferences (MTSR'05, MTSR'07, MTSR'09, MTSR'10, MTSR'11 and MTSR’12), the seventh International Conference on Metadata and Semantics Research (MTSR'13) aims to bring together scholars and practitioners that share a common interest in the interdisciplinary field of metadata, linked data and ontologies. Participants will share novel knowledge and best practice in the implementation of these semantic technologies across diverse types of Information Environments and applications. These include Cultural Informatics; Open Access Repositories & Digital Libraries; E-learning applications; Search Engine Optimisation & Information Retrieval; Research Information Systems and Infrastructures; e-Science and e-Social Science applications; Agriculture, Food and Environment; Bio-Health & Medical Information Systems.

Data collection and analysis are at the core of modern research, and often take months or even years during which researchers remain uncredited for their contribution. A new plugin to a workflow previously developed by the Global Biodiversity Information Facility (GBIF) and Pensoft, and tested with datasets shared through GBIF and DataONE, now makes it possible to convert metadata into a manuscript for scholarly publications, with a click of a button.

Pensoft has currently implemented the feature for biodiversity, ecological and environmental data. Such records are either published through GBIF or deposited at DataONE, from where the associated metadata can be converted directly into data paper manuscripts within the ARPHA Writing Tool, where the authors may edit and finalize it in collaboration with co-authors and peers and submit it to the Biodiversity Data Journal (BDJ) with another click. Until now, the GBIF metadata have been exported into an RTF file. The new feature will be also part of future Pensoft projects, including the recently announced Research Ideas & Outcomes (RIO) Journaland the forthcoming Ecology and Sustainability Data Journal.

The concept of the data paper was introduced in the early 2000's by the Ecological Society of America in order to solve issues of handling big data and to make the metadata and the corresponding datasets discoverable and citable. It was then brought to the attention of the biodiversity community in 2011 as a result of a joint GBIF and Pensoft project and later implemented in the routine publishing process in all Pensoft journals.

Since then, Pensoft has been working with GBIF, and subsequently DataONE to automate the process of converting metadata into a human-readable data paper format. The novel workflow means that with only a couple of clicks, publishers of datasets on either GBIF, DataONE or any other portal storing metadata in the same format, may submit a manuscript for peer-review and open access citable publication in BDJ.

The process is simple, yet it brings a lot of benefits. Publishing data does not only mean a citable publication and, thus, credit to the authors and the repository itself, but it also provides the option to improve your work and collect opinion though peer-review. BDJ also shortens the distance between "narrative (text)" and "data" publishing.

"Metadata descriptions (e.g., data about the data) are of primary importance for data dissemination, sharing and re-use, as they give essential information on content, scope, purpose, fitness for use, authorship, usage rights, etc. to any potential user. Authoring detailed metadata in repositories can seem a tedious process, however DataONE users will now benefit from direct export of already created metadata into data paper manuscripts and have even better exposure of their work through discoverability mechanisms and scholarly citations," commented Dr Amber Budden, DataONE Director for Community Engagement and Outreach

"It is great to reap the fruits of a process that started back in 2010. The automated streamlining of biodiversity data between repositories and publisher is an elegant feature that makes publishing a data paper an easy and rewarding process to crown scientists data collection efforts and ensure its use and re-use," added Prof. Lyubomir Penev, Managing Director of Pensoft.

More detailed information on how data authors could use the workflow can be found on the Pensoft blog.

References:

Chavan V, Penev L (2011) The data paper: a mechanism to incentivize data publishing in biodiversity science. BMC Bioinformatics. 12(Suppl 15):S2. DOI: 10.1186/1471-2105-12-S15-S2

The work has been partially supported by the EC-FP7 EU BON project (ENV 308454, Building the European Biodiversity Observation Network) and the ITN Horizon 2020 project BIG4(Biosystematics, informatics and genomics of the big 4 insect groups: training tomorrow's researchers and entrepreneurs), under Marie Sklodovska-Curie grant agreement No. 542241.

 

Continuing the successful mission of previous MTSR Conferences (MTSR'05, MTSR'07, MTSR'09, MTSR'10, MTSR'11 and MTSR’12), the seventh International Conference on Metadata and Semantics Research (MTSR'13) aims to bring together scholars and practitioners that share a common interest in the interdisciplinary field of metadata, linked data and ontologies. Participants will share novel knowledge and best practice in the implementation of these semantic technologies across diverse types of Information Environments and applications. These include Cultural Informatics; Open Access Repositories & Digital Libraries; E-learning applications; Search Engine Optimisation & Information Retrieval; Research Information Systems and Infrastructures; e-Science and e-Social Science applications; Agriculture, Food and Environment; Bio-Health & Medical Information Systems. 

ONVIF working groups are subsets of the ONVIF Technical Committee and Technical Services Committee, and any ONVIF member company at the full or contributing membership level is encouraged to participate in this work. 

Active Guard ensures that the metadata describing the unique attributes of humans and vehicles captured by i-PRO cameras are seamlessly delivered to popular video management systems (VMS) from Milestone, Genetec, and others.

Cryo-electron microscopy (cryo-EM) has witnessed radical progress in the past decade, driven by developments in hardware and software. While current software packages include processing pipelines that simplify the image-processing workflow, they do not prioritize the in-depth analysis of crucial metadata, limiting troubleshooting for challenging data sets. The widely used RELION software package lacks a graphical native representation of the underlying metadata. Here, two web-based tools are introduced: relion_live.py, which offers real-time feedback on data collection, aiding swift decision-making during data acquisition, and relion_analyse.py, a graphical interface to represent RELION projects by plotting essential metadata including interactive data filtration and analysis. A useful script for estimating ice thickness and data quality during movie pre-processing is also presented. These tools empower researchers to analyse data efficiently and allow informed decisions during data collection and processing.

Suppose Pandora's music magic is a passion in your pastime. In that case, you must take advantage of the jaw-dropping opportunities to save online Pandora passion for your offline pleasure with the recently launched TuneFab Pandora Music Converter.

We've listened to your feedback and are excited to announce the introduction of metadata variables in Auphonic for more advanced use of our Basic and Extended Metadata.
This new feature allows you to use metadata fields from your input files to automate workflows. You can easily reference any field by using { curly brackets } and typing the field name, such as {title}, {artist}, {album}, {track}, and more.
To get started, take a look at our Formatting Examples and the Table of all Variables to see all the available options.

Whether you are using the Auphonic Web Service or our API, metadata variables can be applied whenever metadata values are set. They are particularly helpful when working with Presets, Batch Productions, or Watch Folders!

For instance, consider the left column of the following table as input ending up in the metadata as shown in the right column:

Field	Input	Output
Album	MyPodcast	MyPodcast
Track	25	25
Title	Episode No. {track} of {album}!	Episode No. 25 of MyPodcast!

Note:
Please mind that fields can not refer to each other in cycles (e.g., if {title} refers to {album}, {album} may not refer to {title}). While the input form will not show any errors, the metadata will most likely not be correct and the production will generate a warning.

Formatting Examples

1. Generating Output File Basenames

With metadata variables you can automatically generate your output file basename based on the input filename and podcast metadata, like album, track, and title.
If you have, for example, a podcast preset or input file with the album name "The Placeholder Podcast", you can automatically name your episode title like your input filename. By combining the metadata variables "album" name and your generated episode "title" with any text patterns, like "denoised" in this case, you can create your individual output file basename:

Field	Input	Output
Album	The Placeholder Podcast	The Placeholder Podcast
Title	{input_filename}	interview_jane_doe.wav
Output File Basename	{album}-{title}-denoised	The Placeholder Podcast-interview_jane_doe.wav-denoised

The next example shows how you can create truly unique output file basenames with timestamps. Here, a track number is, together with the input file basename, added up as episode title. So, your unique output file basename could be a combination of this generated episode title with the time and date, when your Auphonic production was started:

Field	Input	Output
Input File Basename	interview_jane_doe	interview_jane_doe
Track	25	25
Title	{track}{input_basename}	25interview_jane_doe
Output File Basename	{title}_{production_created_at:%H:%M_%m/%d}	25interview_jane_doe_19-05_01-30

See example 3 for more time formatting examples, and this table for the full list of symbols that can be used for formatting dates.

2. Deriving "Title" and "Summary" from Podcast Metadata

If the input file metadata contains a track number (alternatively, provided by API or web form), it can be referenced in other fields. Along with the name of the podcast, stored in the "album" field, a value for the title can be created as well as a value for a summary containing all the information:

Field	Input	Output
Track	25	25
Album	The Placeholder Podcast	The Placeholder Podcast
Tags	Anniversary	Anniversary
Title	{album}, Episode No. {track}	The Placeholder Podcast, Episode No. 25
Summary	{title} - {tags.0}	The Placeholder Podcast, Episode No. 25 - Anniversary

3. Adding Time and Date

The following time and date example outputs would be possible for a production created at 7:05 pm on Saturday, January 30th in 1999:

Field	Input	Output
(any)	example-{production_created_at}	example-1999-01-30
(any)	podcast-{production_created_at:%H:%M-%m/%d/%Y}	podcast-19:05-01/30/1999
(any)	output-{production_created_at:%I:%M%p-%m%d%y}	output-7:05PM-013099
(any)	record-{production_created_at:%a-%Y-%b-%d}	record-Sat-1999-Jan-30

See this table for the full list of symbols that can be used for formatting dates.

4. Using List Field "Outputfiles"

For the list fields "tags", "chapters", "outputfiles", and multitrack "input_filename/basename", you need to reference every value separately by adding .N to your variable – Where N stands for ascending ordinal numbers starting from 0.
Combined with the .N you can refer to the format, bitrate, suffix, and ending of every selected output file, for example {outputfiles.0.format} refers to the format of the first output file in your list of outputfiles:

• Output File 1 – format: WAV 16-bit PCM, bitrate: optimal, suffix: lossless, ending: wav
• Output File 2 – format: MP3, bitrate: 112 kbps, suffix: lossy, ending: mp3

Field	Input	Output
(any)	file1-{outputfiles.0.suffix}-{outputfiles.0.ending}	file1-lossless-wav
(any)	file2-{outputfiles.1.format}-{outputfiles.1.bitrate}kbps	file2-lossy-mp3-112kbps
(any)	file2-bitrate-{outputfiles.1.bitrate:04}	file2-bitrate-0112

The bitrate output of the last row is formatted with 4 digits, defined by the suffix :04 attached to the variable.

For all available options, please see the Table of List Variables.

All Metadata Variables

The following variables are available:

Variable	Referring to Field
{input_filename}	Full filename of the input file in a singletrack production
{input_basename}	Basename of the input file in a singletrack production (inputfile.wav becomes inputfile)
{title}	Title
{artist}	Artist
{album}	Album
{track}	Track
{genre}	Genre
{year}	Year
{subtitle}	Subtitle
{publisher}	Publisher
{url}	URL
{license}	License (Copyright)
{license_url}	License URL
{summary}	Summary (Description)
{output_basename}	Output File Basename
{production_created_at}	Time and date of production creation
{production_modified_at}	Time and date of production modification

List Variables	Referring to List Field
{input_filename.N}	Full filename of the input file of N-th track in a multitrack production
{input_basename.N}	Basename of the input file of N-th track in a multitrack production (inputfile.wav becomes inputfile)
{tags.N}	N-th Element in Tags
{chapters.N.start}	Start time of N-th Chapter
{chapters.N.title}	Title of N-th Chapter
{chapters.N.url}	URL of N-th Chapter
{chapters.N.image}	Image file name of N-th Chapter
{outputfiles.N.format}	Format of N-th Output File
{outputfiles.N.bitrate}	Bitrate of N-th Output File
{outputfiles.N.suffix}	Suffix of N-th Output File
{outputfiles.N.ending}	Format ending of N-th Output File

For detailed use, please see Formatting Examples.

Conclusion

Metadata Variables are a powerful tool for organizing your productions whenever metadata values are set. Those field references are very convenient when distinguishing between different files at a glance, particularly when working with Presets, Batch Productions, or Watch Folders.

Please do not hesitate to contact us if you have any questions or feedback!

LAS VEGAS, Nev. -- NAB Show today announced that a new report from the North American Broadcasters Association (NABA) on hybrid radio, metadata and service providers will be unveiled during the Broadcast Engineering and IT Conference (BEITC) session "Broadcasters and Hybrid Radio – It's All About the Metadata" on April 16 at 10 a.m. An expert panel will discuss the report, "Insights on Hybrid Radio and Metadata for Broadcasters," as well as the changing automotive media and entertainment landscape and the service providers helping broadcasters create a great media experience with metadata in the car.

Scene-based metadata for IPTV services

Scenarios, framework and metadata for digitalized artwork images display system

Functions and metadata of spatiotemporal information service for smart cities

Authentication step-up protocol and metadata Version 1.0

"It's too early for us to be realistic," David Weinberger says in closing is2k7. Where reality is binary, forcing us to categorize each piece of information, digital networked storage lets us add metadata along multiple axes. We shouldn't rush to cram it all back into real boxes. Instead, we can build new structures, sometimes adding metadata to digital contents, sometimes using the "contents" as metadata with regard to another question we're asking.

That lack of hierarchy sounds threatening to some, perhaps including universities, who are accustomed to being the authorities. Online, we find new sources of authority, though we also have to learn and re-learn when not to trust both online and offline sources. The university's challenge, and all of ours, is to engage with these new sources of information and meta-information. The answer to "too much information" is likely not to shut off the spigot but to hand out better filters and filter-building toolkits (aggregators, search engines, databases, social network tools, and mashups).

I'm headed to Everything Is Miscellaneous for more.

In this wide-ranging interview with Monica Williams, NBCUniversal's SVP of digital products and operations for the company's content distribution business, we discuss how the proliferation of digital platforms across the OTT, CTV, and online ecosystems has brought new content distribution challenges, the boon of metadata for improving customer experiences, and the 17-day everything-must-go-perfectly marathon of distributing the Olympics.

You encounter this issue when the table metadata matches the data source. In this scenario, no metadata update is required.

You might receive a Segmentation Violation when opening a database table in SAS. The SAS Log contains the error and traceback:

When you publish a model to SAS Metadata Repository by using SAS Model Manager, the publishing process fails and the following error is generated: "The model model-name has a function of ';Transformation';, which is not supported for

Decision makers need to analyze, exchange, and disseminate statistical information effectively in today’s data-driven world. See how Statistical Data and Metadata eXchange (SDMX) standards are helping create robust data links across the globe.

IEEE / Institute of Electrical and Electronics Engineers Incorporated

Responsible for access to digital resources and collections, including identifying and resolving access issues related to resources Perform original and complex copy cataloging and classification of materials in all formats and languages following natio......

Processing metadata includes storing, in a data storage system, a specification for each of multiple sources, each specification including information identifying one or more data elements of the corresponding source; and processing, in a data processing system coupled to the data storage system, data elements from the sources, including generating a set of rules for each source based on a corresponding one of the stored specifications, and matching data elements of different sources and determining a quality metric characterizing a given match between a first data element of a first source and a second data element of a second source according to the set of rules generated for the first source and the set of rules generated for the second source.

Embodiments of the invention provide systems and methods for managing an enabler and dependencies of the enabler. According to one embodiment, a method of managing an enabler can comprise requesting a management function via a management interface of the enabler. The management interface can provide an abstraction of one or more management functions for managing the enabler and/or dependencies of the enabler. In some cases, prior to requesting the management function metadata associated with the management interface can be read and a determination can be made as to whether the management function is available or unavailable. Requesting the management function via the management interface of the enabler can be performed in response to determining the management function is available. In response to determining the management function is unavailable, one or more alternative functions can be identified based on the metadata and the one or more alternative functions can be requested.

A method and an apparatus for generating metadata for digital content are described, which allow to review the generated metadata already in course of ongoing generation of metadata. The metadata generation is split into a plurality of processing tasks, which are allocated to two or more processing nodes. The metadata generated by the two or more processing nodes is gathered and visualized on an output unit.

An information processing apparatus includes a transmission unit transmitting a command of a second operating system to the second operating system when receiving the command via a communication path which communicates under a control based on a first operating system, an extraction unit extracting data for the second operating system by analyzing the command transmitted from the transmission unit, and a writing unit writing the data extracted by the extraction unit as data constituting file system metadata of the second operating system.

Techniques are described for automatic interval metadata determination for intermittent time series data. In one example, a method for determining intermittent time series interval metadata includes detecting one or more time variables in a time series data set. The method further includes determining whether the one or more time variables are intermittently regular. The method further includes determining one or more respective time intervals for the one or more time variables. The method further includes determining the parameters of intermittency for the one or more time variables. The method further includes generating an output comprising information about the one or more time variables based on the one or more respective time intervals and the parameters of intermittency for the time variable.

New Standard Supports More Detailed Information On Compositions, Contributors, Artist Nicknames, Historic Chart Positions, Focus Track Data, Journalistic Material, And More

The ACT government has defended its right to seek access to Canberrans' private phone and internet records without a warrant.

A new internet messaging tool that sidesteps the federal government's metadata collection regime to help journalists protect whistle blowers and assists human rights activists has received a tick of approval from security experts.

When you register an Oracle table to the metadata, it might fail and generate an error similar to the following: "ERROR: An exception has been encountered...ERROR: Read Access Violation METALIB..."

The METADATA procedure might return an error similar to one of the following:

ERROR: Missing root element definition.

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