«Without Frames» Media on Moscow Exhibitions and Visual Art

Concept

The Telegram media outlet «Bez Ram» covers exhibitions and visual art in Moscow, helping people quickly decide where to go, understand the purpose of attending a specific show, and gain basic context before visiting. The channel aggregates timely recommendations, curated exhibition selections, and brief art materials covering artists, individual works, genres, and movements. The information is presented concisely, clearly, and without overly academic art jargon. Users can not only learn about an event but immediately determine if it is right for them.

Essence

User Problem

Information about exhibitions is scattered across museums' websites, flyers, city media, and social networks. The user sees many different events but doesn’t always know which exhibition is right for them or if it’s worth their time and money. Exhibition descriptions are often either too brief and formal or written for an audience already well-versed in art. Because of this, the individual has to seek out additional information about the artist, the movement, or the exhibition itself.

Solution

«Without Frames» brings together the listing, the recommendation, and the explanation into a single format. Instead of a long list of events, the platform curates content editorially and answers the user’s core questions: what is this exhibition, who is it for, how much time should I allocate for it, and what should I know before visiting? A crucial part of the project is that art is explained through relatable scenarios and familiar experiences. For instance, instead of a lengthy text about genres, the project can illustrate the connection between a portrait and modern selfies, or provide three facts before an exhibition to help viewers interpret what they see more deeply.

Naming

«Without Frames» plays on both the literal frame of a painting and the idiom «to go beyond the boundaries.» The title reflects the project’s core idea: to view art more broadly than the conventional notion of a museum, free from restrictive jargon and academic explanations.The word «frame» also becomes part of the project’s visual system. Dotted frames are used in the identity, cards, and navigation, while individual images and elements are visually allowed to extend beyond them.

Data Sources for Media

To populate the channel, we combine automated data scraping from open sources with manual editing. The main sources of information about exhibitions are:

Official Museum and Gallery Websites

Most major institutions (Pushkin Museum, Tretyakov Gallery, GES-2, Moscow Museum, Tsartchino, Biological Museum, etc.) publish announcements for their exhibitions, including dates, descriptions, tickets, and photographs.

City Posters and Aggregators

Special portals for cultural events in Moscow (such as Afisha.ru, Yandex.Afisha, TimeOut Moscow, KudaGo, etc.) feature exhibition calendars with filters for dates and genres. For example, the «Afisha» portal compiles a complete list of current and future exhibitions in its «Exhibitions in Moscow» section. Yandex.Afisha also maintains a page listing exhibition schedules («Moscow Exhibition Schedule»), where each event is detailed with its title, venue, and dates. These aggregators allow users to quickly obtain summarized information about city-wide events.

Museum Open Data

Some museums publish their collections and events in machine-readable formats. For example, the Pushkin Museum provides JSON files containing catalogs of «masterpieces, ” collection sections, and so on—data ready for automated processing. You can also access datasets on museum exhibits and holdings through the Ministry of Culture portal (opendata.mkrf.ru). This data can be used to populate project databases and create context.

Social Media and Mass Media

Museums often announce exhibitions on social media and through press releases, which can also provide various information for the channel. This also includes articles from city media, art blogs, and event listings featuring interviews with artists and reviews—these are sources of facts and quotes for extended content (biographies, artwork descriptions, etc.).

Data diagram separated for human and machine processing

Original size 1672x941

The «Frameless» media project draws from several types of sources: social media and news outlets, open museum data, city event listings and aggregators, as well as official museum and gallery websites. From these sources, the system gathers basic information about exhibitions, venues, dates, tickets, and event descriptions.

During the machine processing phase, the data is automatically collected and standardized into a unified format so that information from different sources can be compared. The system also removes duplicates, extracts official descriptions, and prepares images for publication. Drafts for audio and video can also be automatically generated based on the already gathered information.

This is followed by human data processing. The editor verifies facts and dates, shortens and rewrites official annotations to fit the «Frameless» tone, and crafts the «Why Go» and «What to Know» sections. The human reviewer also selects images, monitors the accuracy of captions, and determines the appropriate category and publication format.

After the final editing, the material is published on the «Frameless» Telegram channel. Feedback is then collected regarding views, reactions, saves, polls, and audience responses. This data is fed back into the system to help refine future topics, formats, and publication frequency.

Guidelines for Automated Services in the Scheme

Original size 1672x941

Guidelines for Automated Services

Automated services within the «Bez Ram» project are utilized for routine and formalizable tasks: gathering information, structuring data, drafting initial content, planning publications, and basic analytics. They help maintain the regularity of the Telegram channel’s output but do not replace the editor in selecting topics, forming the author’s perspective, or conducting final material review. Any content prepared automatically must undergo human verification before publication.

Content Gathering

Automation begins with collecting information from official museum and gallery websites, city event listings and aggregators, museum open data, social media, and the press. The system records the exhibition title, venue, dates, ticket price, source link, and the available official description.

Priority is always given to the official source. If the information in an aggregator differs from that on the museum’s website, the museum’s or gallery’s information is considered primary. Every entry must retain a link to the original source and the date of the last verification.

Automated collection does not equate to automatic publication. The retrieved information is first placed in a draft database and only then used to create content.

Data Processing and Structuring

After collection, the data is automatically standardized into a unified format. Venue names are unified, dates are converted to a single format, duplicate events are removed, and links to images and sources are saved separately.

If a single exhibition is found in multiple sources, the system must merge the entries rather than creating several identical cards. If there are discrepancies in dates, prices, or other facts, the entry is flagged with a «requires review» status.

The system can also calculate additional parameters, such as the number of days remaining until an exhibition ends. This metric is used for the #bezram_lastchance category, but the decision on whether the exhibition will actually be published remains with the editor.

Drafting and Preliminary Formatting

The neural network can prepare a preliminary draft of a publication based on verified data. It must use only facts already in the database and should not add unknown dates, prices, exhibition details, or biographical information.The draft must adhere to the format of a specific section.

Editing and Publication Preparation

The editor verifies all facts, condenses the official text, and adapts it to the language of «Bez Ram.»The editor is also responsible for humor, emotional phrasing, authorial observations, and connecting art with everyday experience. These elements cannot be fully conveyed to an automated service because they define the media’s voice.Images also undergo manual selection. The editor checks the source, authorship, and usage rights for each image, selects the most appropriate frame, and oversees its presentation within the «Bez Ram» brand system.

Scheduling and Publishing

After editorial approval, the finalized materials can be submitted to the delayed posting service. The automation handles the publication date and time but cannot alter the finished text or visual assets without further approval.Publications are distributed according to the channel’s content plan. The system helps maintain the regularity of sections and prevents multiple identical formats from being published consecutively.Before publication, an automatic check of essential elements must be performed: title, text, image or other media file, event date, and information relevance. If any required element is missing, the publication is not sent automatically and is returned to the editor.

Analytics and Feedback

After publication, the system collects available Telegram metrics: views, reactions, poll results, and audience responses. This data is not used to automatically change the content but serves as supplementary information for the editorial team.

1. Delegate Fact Gathering and Draft Generation to the Machine, Not Final Content

Automated services can gather basic information about exhibitions, normalize it into a consistent format, and create a first draft of a publication. This reduces time spent on routine tasks and helps maintain channel regularity. Nevertheless, the final text must always be reviewed by an editor. The human is responsible for phrasing, tone, meaning, and adherence to the «Frameless» style.

2. Strictly Separate Automated and Editorial Tasks

Any data that can be unequivocally verified can be processed automatically. This includes exhibition titles, dates, addresses, ticket prices, venues, and source links. However, the assessment of the exhibition, the author’s voice, recommendations, and phrasing like «go if» remain the responsibility of the editor. The machine can suggest an option, but it should never provide subjective judgment for an objective fact.

3. Responsibly Use Open Data

When automatically collecting information, it is essential to retain the source link and verify the terms of material usage. For images, it is crucial to consider authorship, licensing, and publication permission. If the right to use a photograph or artwork is unclear, that material should not automatically appear in the final post. Priority must be given to the official websites of museums and galleries and to open museum data. Automation should help work with sources more meticulously, rather than turning into uncontrolled copying of other people’s content.

4. Implement Automated Data Validation

Before publishing, the system must check whether an exhibition is current, if the dates are listed correctly, and if required fields are filled out. If the end date has already passed, the event is automatically excluded from current selections. If different sources list different dates, prices, or venues, the entry is flagged for manual review.

5. Orient Automation Toward Reader Benefit

Automation should be used not for the sake of data collection itself, but for solving specific user problems. For example, calculating the number of days until an exhibition closes helps create the frameless_lastchance segment, and grouping events by date simplifies the preparation of frameless_weekends.